IGoR Teaming Profiles
This page is designed to help facilitate connections between prospective proposers, which ARPA-H anticipates will be necessary to achieve the goals of the Intelligent Generator of Research (IGoR) program. Prospective performers are encouraged (but not required) to form teams with varied technical expertise to submit a proposal.
If either you or your organization are interested in teaming, please create a profile via the ARPA-H Solutions site linked below. Your details will then be added to this page, which is publicly available.
Please note that by publishing the teaming profiles list, ARPA-H is not endorsing, sponsoring, or otherwise evaluating the qualifications of the individuals or organizations included here. Submissions to the teaming profiles list are reviewed and updated periodically.
IGoR Teaming Profiles
To narrow the results in the Teaming Profiles List, please use the input below to filter results based on your search term. The list will filter as you type.
| Jonathan Brown | Eo-vision AI | jonathan@eovision.ai | New York, NY | We extract that unread signal. Other AI asks 'what is this?' and classifies disease from pixels. We ask 'what is it made of?' and recover the biology itself. Our model reads the biology of cancers it was never trained on: proof the signal is real, and that each new disease costs us almost nothing while competitors retrain at scale. We turn that signal into a standard measurement and sell it to the hospitals, insurers, and drug developers carrying the losses today. | clinical expertise and access to medical imaging | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Diana Hnedzko | A2 Labs | dhnedzko@a2labs.com | Arlington, VA | Our organization develops scalable digital twins, operational testbeds, and emulated healthcare and critical infrastructure environments for resilient AI and agentic-system development. We specialize in training and evaluating autonomous agents in realistic, uncertainty-rich operational settings, including large-scale multi-user infrastructures, predictive modeling, and high-fidelity simulation and emulation frameworks for decision support, coordination, and operational resilience. | We seek collaboration with teams that can perform as TA3 and TA4. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| William Storey | Advanced Consulting Experts | will@aceadvising.com | Columbus, GA | Advanced Consulting Experts, ACE, is developing GIA, a runtime AI governance control plane for high-stakes agentic workflows. For IGoR, GIA fits as a governance and control layer around AI-guided biomedical research workflows. GIA can help enforce protocol boundaries, classify risk, control tool access, require human oversight, monitor agent behavior, preserve experiment rationale, and generate audit-ready evidence for reproducibility, safety, and trust. | Seeking partners with expertise in computational biology, mechanistic disease modeling, biomedical data engineering, lab automation, protocol design, wet-lab validation, or health research operations. We bring runtime AI governance, agentic workflow control, auditability, protocol boundary enforcement, and human oversight for AI-guided research systems. | TA2: New Science Engine |
| Peyton Tebon | Aeris, LLC | ptebon@aerisllc.com | Louisville, CO | Aeris develops AI-driven agentic workflows, machine learning systems, and data science tools for complex life science challenges. Our team brings hands-on experience in cancer biology, mechanistic pathway analysis, and genomic and transcriptomic data analysis, combined with expertise in laboratory automation, machine-readable protocol development, and translating experimental intent into computable, interoperable formats. | Our team seeks TA4 partners operating validated laboratory infrastructure (cloud labs, CROs, core facilities) with demonstrated reproducibility across sites. Partners with experience in omics, imaging, or functional assays and a commitment to returning data and metadata in open, interoperable formats are especially valued. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Alondra Schweizer Burguete | Akraia | alondra.burguete@akraia.ai | New York City, NY | Akraia develops AI-enabled human microphysiology platforms for mechanistic disease modeling and hypothesis generation in CNS and age-associated disease biology. We generate wet-lab human-derived longitudinal perturbation-response and multi-omics datasets to identify causal biological drivers of disease and support iterative scientific discovery. | We provide a human-grounded experimental substrate that enables AI orchestration layers to become biologically causal rather than purely predictive. We seek partners to build scalable, closed-loop systems for AI-guided biomedical discovery. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Eva Maria Janerus | Alden Scientific | evamaria@aldenscientific.com | Boston, MA | Alden Scientific is an AI company that illuminates current health and simulates future health, disease, and aging by applying machine learning to advanced biological data. Our research focus is developing biomarkers to understand and predict disease and an individual's response to pharmaceutical and lifestyle interventions. | Hospital or healthcare systems with strong track record in patient engagement and recruitment for studies. Therapeutic companies interested in running clinical trials to understand efficacy and biomarkers for patient stratification. Researchers looking to understand biomarkers for help in predicting individual patient responses and suceptibility to adverse events. Disease registries with access to high quality, well-phenotyped, longitudinal research grade plasma samples. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Kelsey MacMillan | Allen Institute for AI (Ai2) | kelseym@allenai.org | Seattle, WA | Ai2 is a nonprofit AI research institute advancing open, foundational AI for high-impact scientific and prosocial problems. Our work spans foundational open models, Embodied AI, Earth systems, and scientific agents (Asta, the focus here).Asta develops agents that read literature, reason over scientific knowledge, and autonomously generate and test hypotheses from data. Supporting capabilities: OLMo, the Semantic Scholar corpus (~220M papers), and evaluation of science agents (AstaBench). | Ai2 is most effective as the open AI research and infrastructure contributor on a multidisciplinary team. Asta brings expertise in agentic systems: orchestrating multi-agent workflows and the data infrastructure they depend on. Ai2 also develops large-scale multimodal models and has some biomedical literature and data modeling experience via partnerships. We have no protocol development or wet-lab capabilities, and seek partners with hands-on biomedical science expertise. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Shray Vats | AlloTec Bio | svats@allotec.bio | Boston, MA | We have developed and continue to refine a methodology combining both Generative AI and physics based methods to determine what residues govern the dynamics and function of protein systems, generate conformation ensembles, and understand how disease causing mutations change their function and underlying ensemble. | We would love to have partners who can test our hypotheses about specific systems experimentally, such as groups with expertise in methods generating protein structures such as NMR, crystallography, cryo-EM, hydrogen deuterium exchange, etc. It would also be great to collaborate with groups that could help us build protein interaction networks using our data to understand how mutations affect downstream systems and drive disease progression. | TA1: Comprehensive Disease Models |
| Carlos Cruchaga | Andia Health | cruchagac@wustl.edu | Saint Louis, MO | Andia Health integrates large scale human multi omics with advanced, explainable AI to accelerate discovery in complex diseases. Its GPND AI framework, validated in 40,000+ samples, identifies mechanisms, predicts co pathologies from blood, and reveals knowledge gaps. With interoperable models, causal pipelines, and secure data governance, Andia Health is built for IGoR’s vision of a reproducible, AI enabled research ecosystem. | Andia Health seeks partners with strengths in scalable experimental systems, high‑throughput perturbation, and automated validation pipelines (TA3), as well as teams skilled in building user‑ready platforms, interfaces, and deployment frameworks (TA4). These capabilities will extend Andia’s TA1–TA2 AI engines into fully operational, testable, and deployable IGoR solutions. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| David de Gruijl | Anto Biosciences | founders@anto.bio | San Francisco, CA | Anto Biosciences builds multi-omic foundation models of the gut microbiome. Using metagenomic and metabolomic data, our 7-billion parameter model (Darwin-7B) maps novel mechanistic pathways driving disease and drug response. We pair this computational engine with specialized wet-lab expertise and a robust partner network to validate targets and accelerate translational research. | We are looking for clinical, academic and industry partners bringing patient cohort access, trial infrastructure, or specific disease expertise. We want to collaborate with innovators who recognize the limits of animal models and are ready to leverage our platform to ground their therapeutic or diagnostic programs in human-specific mechanistic pathways. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Adrian Grzybowski | AnuBio | adrian@anubio.ai | Allen, TX | AnuBio developed TRAILBLAZER, a multicellular phenotypic perturbation foundation model AI that predicts mono and combinatorial drug responses zero-shot at patient resolution, with published validation in immuno-oncology. Current focus areas: virtual phenotypic drug discovery, virtual clinical trials, cold tumor microenvironments, and immune set-point dysregulation across immuno-oncology and autoimmunity for ranking immunomodulator interventions across heterogeneous patient contexts. | We seek TA1 mechanistic-simulation partners to anchor verifiability (agent-based or multiscale simulators of immune-tumor or synovial systems), TA2 collaborators building agentic orchestration with provenance and dissent architectures, TA3 protocol-engineering partners, and TA4 wet labs with immune assay depths capable of organoid plus immune component co-culture. Strong fit with academic medical centers operating validated immunology or immuno-oncology infrastructure. | TA1: Comprehensive Disease Models |
| Caleb McClain | ANUNA (AI+BIO) | caleb@anuna.ai | Dover, DE | Currently focused on SoTA Gen AI model training and agentic systems, specialized data systems, AI software applications for precision health and plant-derived drug discovery and polypharmacy nutraceutical innovation. | We seek partnerships in scientific computing, cloud infrastructure and distributed technology systems, and high-performance compute resources. Additionally, we are seeking scientific partnerships for wet lab, chemical and material analytics, and chemo-bioinformatics with opportunities for shared data economies and real-world analytics through our proprietary technologies. We also seek distribution partnerships for both technologies and therapeutics (both botanical drug and nutraceuticals). | TA2: New Science Engine, TA4: Experiment Marketplace |
| Jason Rodriguez | Applied Research Associates, Inc | jrodriguez@ara.com | Raleigh, NC | ARA specializes in mechanistic and data-driven approaches to physiological modeling. Currently, we are leading an effort designed to extrapolate data from organs on chips to mechanistic and empirical models to determine whole-body physiological response to pathogens, chemicals, and treatments. This effort focuses heavily on feasibility studies and working with labs to design experiments specific to computational modeling. We see ourselves as TA-1 leaders and TA-2 partners. | We are looking for TA-3 and TA-4 teammates. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Myke Cohen | Aptima, Inc. | mykewcohen@gmail.com | Woburn, MA | Aptima advances human‑centered AI for complex analytic workflows, spanning adaptive training (Sidekick‑TA), decision support (PLURITAS), and cross‑disciplinary scientific reasoning. Our recent BioSage effort synthesizes multimodal scientific knowledge using specialized reasoning agents to accelerate discovery and support transparent, explainable hypothesis generation across domains. | Aptima seeks prime organizations forming IGoR teams who need strong support in TA2. We offer an explainable, mechanistically grounded science‑engine capability built on BioSage’s multi‑agent reasoning framework. We aim to collaborate with teams requiring AI‑driven hypothesis generation, experiment‑design reasoning, and human‑AI scientific collaboration at the core of their orchestration layer. | TA2: New Science Engine |
| Pavan Turaga | Arizona State University | pturaga@asu.edu | Tempe, AZ | The Geometric Media Lab at ASU includes expertise in broadly applicable machine learning methods including, agentic models, geometric and topological machine learning, models to promote robustness and reliability, as well as enhancement of interpretability. | Clinical partners, mechanistic modelers, research infrastructure platform developers. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Joshua Dungan | Artificial General Intelligence LLC | jddungan18@gmail.com | Grand Rapids, MI | Accelerating research through proprietary veridical enforcement methods. | I am a single member LLC and I am not looking for a wet lab at this time. However, I firmly believe that my software revolutionizes the way research can be done, and I will need clinical or other researchers and scientists to help test and give feedback or needs assessments after my provisional patent is filed. I need testers and people who can look at AI research and validate or peer review generations made. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Will Johnson | Asimov, Inc | will@asimov.com | Boston, MA | Company: Boston-based synthetic and computational biology firm developing predictive models and optimizing biophysical phenomena. TA2-TA3 (Orchestration): Multi-agent AI co-scientist and Kernel CAD software manage genetic design, synthesis, and protocol automation. TA1 (Modeling): Closed-loop data flywheel, predictive models actively guide genetic design space exploration. TA4 (Execution): high throughput automated experiment engine delivers rich longitudinal datasets. | Augmenting automated lab capacity, BSL capabilities, and experimental throughput. Scaling agentic AI co-scientist tools via frontier AI, compute, or production partners. Co-developing layered protocol architectures with cloud labs & CROs for automation. Filling disease biology gaps via early discovery, target ID, and validated models. Integrating multiscale, mechanistic human disease models (PK-PD). Building a distributed network of validated cloud labs for reproducible runs. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace, TA1: Comprehensive Disease Models |
| Keith Gibson | Autoworklet | gibson.keith.w@gmail.com | Washington, DC | Autoworklet focuses on AI-enabled workflow orchestration, operational automation, and interoperable data execution across complex enterprise environments. Our current research areas include visual-first automation, AI-driven workflow modernization, human-machine teaming, metadata orchestration, decision-support systems, and scalable interoperability frameworks that enable rapid, repeatable execution across distributed organizations, systems, and teams. | Autoworklet is seeking teaming partners with expertise in computational biology, mechanistic disease modeling, AI-ML research, laboratory automation, experimental validation, biomedical data infrastructure, and scalable research operations. We are particularly interested in organizations capable of integrating advanced scientific workflows, interoperable protocols, and distributed execution environments to accelerate reproducible research and operationalize AI enabled discovery at scale. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Ananth Annapragada | Baylor College of Medicine | annaprag@bcm.edu | Houston, TX | Baylor College of Medicine has formed a consortium of 10 partners with deep expertise in the area of neurodegenerative diseases across all 4 TA's of this call. TA.1 Predictive Models TA.2 Orchestration, Hypothesis generation TA.3 Protocol Generation TA.4 Automated assay performance | We invite (1) additional groups with predictive models of neurodegenerative diseases, and 92) assay laboratories with expertise in cell, organoid, biochip, insect, or nematode assays to join our consortium. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Tamer Mohamed | Baylor College of Medicine | tamer_1977@hotmail.com | Houston, TX | We have developed a technology to culture human heart slices which is used to disease model the human heart diseases. We have accss to the human transplantation network from which we can abtain human organs from healthy and disease donors which could be used for disease modeling | We can contribute to TA1 and we are seeking partners for the other TAs | TA1: Comprehensive Disease Models |
| Christina Bernstein | BB Medical Surgical | tina@bbmedicalsurgical.com | San Francisco and Los Angeles, CA | Pediatric and adult airway management devices (passive, single-use, drug delivery) for emergent airway scenarios. | We seek to team with an organization that can help us with cybersecurity reqs, as we want to submit for DoD opportunities for emergency airway management. We also have experience in using physical, real human simulators to build airway devices and would like to create a digital twin version for modeling and prototyping. | TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Anthony English | BioSyft Inc. | anthonyenglish97@gmail.com | Seattle, WA | BioSyft develops deep-learning AI models for in vivo behavioral analysis in preclinical research and drug development. Our work focuses on high-fidelity behavioral phenotyping, computer vision, and machine learning systems that detect nuanced behavioral signatures for automated predictive efficacy and toxicology studies. Our platform standardizes and automates assays that are classically low-fidelity and subjective, allowing us to build virtual control animal models. | BioSyft is seeking collaborators with expertise in toxicology, PK-PD studies, in vitro systems, omics technologies, and advanced AI-ML methods. We are particularly interested in partners generating high-quality translational datasets that can integrate with behavioral phenotyping and predictive modeling workflows. We see BioSyft as a key puzzle piece within the larger interoperable research ecosystem envisioned by IGoR. | TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| Hongzhang He | Captis Diagnostics | simonhe@captisdx.com | Pittsburgh, PA | Captis Diagnostics focuses on developing research-use-only (RUO) tools for the exploration of extracellular vesicles (EVs) in basic, translational, and clinical research. Our technologies enable the isolation and analysis of EVs from a variety of biological samples, supporting studies across multiple disease areas, including cancer, neurodegenerative disorders, and organ transplantation | TA1 and TA2 | TA4: Experiment Marketplace, TA4: Experiment Marketplace |
| Yongjie Zhang | Carnegie Mellon University | jessicaz@andrew.cmu.edu | Pittsburgh, PA | High fidelity, reduced order modeling, machine learning, digital twins for cardiovascular systems and brain neuron computation | clinical partners or teams with complementary expertise | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Amelia Yu | Carnegie Mellon University | ameliay@andrew.cmu.edu | Pittsburgh, PA | CMU's AI Science Foundry is an AI-guided automated experimentation facility containing 80+ major instruments in a 15,000 ft² Biological & Chemical and a 2,300 ft² Metals & Alloys programmable cloud lab (PCL). This large collection of co-located research tools for biology, chemistry, and hard materials is connected by a scalable, flexible, programmable Accelerating Scientific Autonomous Platform across two physical locations, and designed in a modular grid for rapid new instrument integration. | TA1: Comprehensive Disease Models and TA4: Experiment Marketplace | . |
| Chris Decker | CDISC | cdecker@cdisc.org | Asheville, NC | CDISC is the global nonprofit developing data standards for clinical research, now required by FDA and PMDA across 90+ countries. CDISC is adding a semantic layer to our standards to enable AI and accelerate study design, data transformation, and analysis. With 450+ members across 31 countries, the standards drive interoperability across the clinical research ecosystem. | CDISC is looking to partner with technology and disease organizations to help us drive semantically linking the information in a trial from the endpoint through the analysis to enable researchers to accelerate their work. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Jesse Meyer | Cedars-Sinai | jessegmeyer@gmail.com | Los Angeles, CA | We are mass spectrometry and AI experts capable of semi-automated and large scale proteomics, lipidomics, and polar metabolomics. | Seeking partners with disease models and AI layers. | TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Dwight Baker | Cellanome | dwight.baker@cellanome.com | San Diego, CA | Cellanome's R3200 is an integrated cell biology platform combining programmable CellCage enclosures, longitudinal live-cell fluorescence imaging, and scRNA-seq to characterize individual cells across time. CellCages capture and retain targeted cells for continuous phenotypic monitoring and downstream sequencing, enabling time-resolved phenotypic and transcriptomic characterization of single cells and cell-cell interactions at scale across any cell type with reproducible workflow protocols. | Cellanome seeks teaming partners for ARPA-H IGoR as a TA3 - TA4 performer. The R3200 provides a reproducible, instrument-locked single-cell protocol execution node capable of serving as the primary cell biology experiment platform across a broad range of cell types and experimental designs within the IGoR marketplace. Seeking a prime performer with TA1 mechanistic disease modeling and TA2 agentic AI orchestration capabilities. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Jennifer Fisher | CFD Research | jenniferlfisher7@gmail.com | Huntsville, AL | CFD Research develops advanced computational biology and AI-ML software solutions. Our expertise spans mechanistic and systems biology modeling, multi-omics analytics, bioinformatics, AI-ML model development, digital twin platforms, and scalable software engineering. CFD Research also maintains laboratory space to support translational research, prototyping, and validation of computational models and AI-generated hypotheses. | CFD Research is interested in both prime and subcontracting opportunities for the IGoR program. We are seeking collaborators across all Technical Areas, particularly experimental validation partners, AI-ML teams, laboratory automation groups, and large-scale multimodal data generation partners. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Larry Bartolotti | CGI | lvbatb@gmail.com | Fairfax, VA | CGI Federal offers Project Manager (PM) and Program Management Office (PMO) leadership for IGoR, providing a dedicated PM and cross team software architect, ARPA H aligned governance, milestone-dependency control, quarterly deliverables and biannual reviews, IMS-RAID management, DevSecOps pipelines and testing-QA, dashboards and decision records—keeping all performers aligned, compliant, and on schedule. Plus IV&V, cybersecurity, and regulatory compliance. | Seeking research led partners with biomedical AI and wet lab strength to lead TA1 and TA2, plus lab automation and protocol standards expertise for TA3, and validated labs for TA4. Looking for cloud and data platform providers and collaborators aligned to open standards, PMO integration, IV&V, security, compliance, and marketplace operations. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| christopher Geib | Charles River Analytics | geibc26@gmail.com | Boston, MA | We have valuable offerings in the TA2 area. | We are looking to join a larger team. | TA2: New Science Engine |
| Kenta Terasaki | Chimera Research | kentaterasaki@gmail.com | Houston, TX | Chimera Research is developing the recursive flywheels for autonomous research in drug discovery. Our work is focused on building the closed loop of hypothesis research, biomolecular simulation, benchmarking and wet-lab validation through generated SOPs. The results recursively improve simulators for better candidate generation for a scientist’s specific research. By connecting these engines into one traceable workflow, we aim to accelerate scientific discovery through autonomous research. | We're seeking two types of partners. First, organizations with drug discovery models that can be integrated modularly into our system, where our recursive flywheel infrastructure refines the model for domain-specific use cases. Second, wet lab operators in the assay screening and drug discovery space who are interested in executing our generated SOPs to help improve our simulators. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Russell Bowler | Cleveland Clinic | condohoabowler@gmail.com | Cleveland, OH | Cleveland Clinic is building AI- and omics-enabled systems biology programs in complex disease, with strengths in COPD, Alzheimer’s-neurodegeneration, aging biology, network medicine, digital twins, drug repurposing-screening, iPSC-organoid models, multimodal clinical-imaging-omics data integration, and translational validation through disease-focused labs, core facilities, and clinical cohorts. | Cleveland Clinic seeks partners with complementary capabilities in cloud and robotic lab execution, interoperable protocol architectures, laboratory automation standards, calibration and metadata schemas, experiment marketplace operations, cross-site reproducibility and IV&V, and scalable software infrastructure to connect mechanistic disease models, AI experiment design, automated validation, and model-ready data return. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Karl Handelsman | Codon Capital | karl@codoncapital.com | San Francisco, CA | We have started dozens companies in both pre-clinical therapeutics and synthetic biology | technical founders with a vision | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Kelly Klepinger | Cognizant | kelly.klepinger@cognizant.com | Teaneck, NJ | Cognizant's Life Sciences practice combines FDA regulatory, GxP + research data governance expertise with enterprise agentic AI. We have deployed AI-native research ELN platforms in federal research with established ATOs + bring 35+ global pharma + biotech engagements — including proven change management from regulated environments where compliance forcing functions drove FAIR data adoption that federal labs have yet to face. Babak Hodjat, our Chief AI Officer, leads our agentic AI capability. | We seek a prime or co-prime role with partners bringing mechanistic disease modeling (TA1) + validated distributed wet lab execution (TA4). We provide what most IGoR teams are missing: the expertise to govern + structure primary research data so every downstream component — AI orchestration, interoperable protocols, experiment marketplace — actually works. Federal ATO experience + all of the top 10 pharma companies. Teams needing this foundation should reach out. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Barry Bunin | Collaborative Drug Discovery CDD | bbunin@collaborativedrug.com | Burlingame, CA | Collaborative Drug Discovery secure private and open modes for data and models. Superior analysis and partitioning sharing of all molecular and biologicals with atomistic detail and functional specificity for a range of heterogeneous bioactivity data outputs from a range of experiments by scientists, instruments, and agents.Widely adopted by humans with well documented API as a robust foundation for projects to really engage diverse experts working together faster around common goals. | Although CDD has led dozens of projects, here we would prefer to team and follow others, perhaps experimentalists generating data (our expertise is capturing the data with unique chemistry AI, chemically aware representation of biologics, and extreme usability for people and agents). So we are open to teaming with those with operational excellence, project management, biological, chemical, and experience working with ARPA-H. CDD already works with 750 biotech and academics | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Igor Shuryak | Columbia University | ishuryak@gmail.com | New York, NY | Mechanistic modeling and causal machine learning for oncology and radiation biology. Core methods: heterogeneous LQ dose-response, SINDy and KAN-augmented ODE discovery within nonlinear mixed-effects (NLME) ensembles, and causal survival forests, DML, and TMLE estimators linking mechanistic features to heterogeneous treatment effects. Applied to clinical registries (RADCURE, NCDB), epidemiologic cohorts (LSS, CEDR), and radioligand therapy precision dosimetry. Empire AI postdoctoral fellowship. | Partners with experimental and infrastructure capabilities complementary to mechanistic and causal modeling. Specifically: partners with AI orchestration, active learning, or experimental design platforms, TA3 partners with experimental protocol standardization and qualification expertise, TA4 partners operating qualified or automated wet laboratories. Open to disease-area collaborators in oncology, neurodegeneration, and other disease domains where mechanistic modeling adds value. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Brian Alper | Computable Publishing LLC | balper.computablepublishing@gmail.com | Franklin, NC | We lead the standards development effort to extend the HL7 FHIR standard (for health data exchange) to support research data exchange. The Evidence Based Medicine on FHIR (EBMonFHIR) Implementation Guide provides the structures needed for interoperable sharing of research protocols and research results. | As we are not a prime for this teaming effort, we are seeking to collaborate with any team that wants to use the EBMonFHIR standard to define the structure for data exchange for an interoperable research ecosystem. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| MEHUL SHAH | CTIS, Inc. | mhshah@ctisinc.com | ROCKVILLE, MD | CTIS as a Health IT modernization solution provider have been supporting federal health programs for over 30 yrs. We develop AI-ML-NLP, cloud, and innovative solutions across public health, and government environments. | Data partners, Scientific team, Scientific modeling | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| ALLEN RUSZKOWSKI | CVAC Systems, Inc. | allen.ruszkowski@gmail.com | Murrieta, CA | Initial funding from DARPA for U of Hawaii to validate the technology we manufacture to build a super soldier. The Wall Street Journal reported Novak Djokovic started using in at the US Open in 2010. We are receiving reports using it reversing ALS symptoms. | Help getting the clinical studies initiated and completed. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| SUNIL Jain | CYBERINQ LLC | cyqubits@gmail.com | Baltimore, MD | Tools for Proteins Conformational State Exploration | Protein Researchers - willing to experiment and develop a new paradigm for conformational states exploration. | TA2: New Science Engine, TA4: Experiment Marketplace |
| Yaoyu Yang | Cypher AI | yaoyu@cypherbio.ai | Cambridge, MA | Cypher AI develops AI native infrastructure for biomedical research execution by translating scientific protocols into structured interoperable procedures, integrating qualified lab and service providers, guiding wet lab execution, tracking sample, work, and data lineage, and providing data management solutions. Our focus is connecting experiment design, protocol standardization, lab operations, and reproducible data feedback loops. | Cypher AI seeks teaming partners in mechanistic disease modeling, causal biology, computational biology, lab automation, robotics, and validated wet lab execution. We are especially interested in TA1 and TA4 partners who can bring disease models, high value biomedical use cases, qualified lab networks, reproducible assay execution, and gold standard data generation. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Shahin Mohammadi | Cytognosis Foundation | mohammadi@cytognosis.org | Daly City, CA | We are building a multimodal cellular intelligence platform that integrates molecular, cellular, and phenotypic dysregulation into a multiscale, dimensional map of psychiatric disorders. Our team co-led the first single-cell atlases of schizophrenia and bipolar disorder and has extensive experience building virtual cell models to predict the causal effect of genetic and chemical perturbations on the transcriptomics, morphology, and electrophysiology of iPSC-derived NGN2 neurons. | We bring TA1 and TA2, the disease model, and the engine that designs the most informative experiments. We seek TA3 and TA4 partners to close the loop. Because causal models are built and tested by perturbation, we need interventional labs and open protocol standards: pooled CRISPR, Perturb-seq, optical pooled screening, live-cell imaging, and electrophysiology in iPSC-derived neurons, glia, and organoids, with reproducible cross-lab concordance. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Steve Levine | Dassault Systemes | steven.levine@3ds.com | San Diego, CA | Provider of physical AI agents, AI driven multiscale-multiphysics human digital twins, In Silico Clinical Trials and clinical data management solutions | Clinical expertise and data, advanced visualization, HPC or data analytics | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| Peter Grillo | Databricks | peter.grillo@databricks.com | Washington, DC | Databricks Health and Life Sciences focuses on scalable data and AI platforms supporting biomedical research, translational science, and clinical analytics. Current areas include multimodal data integration, governed lakehouse architectures for research environments, ML and AI workflows for drug discovery and biomarker development, real world evidence analytics, genomic and imaging data pipelines, and agentic AI systems supporting scientific knowledge discovery and research productivity. | Databricks seeks partners with complementary expertise in mechanistic disease modeling, experimental biology, laboratory automation, protocol interoperability, validation frameworks, and large-scale scientific program execution. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Alvaro Buitrago | Dimenso Technologies Inc. | alvaro@dimenso.ai | Cambridge, MA | Dimenso builds AI infrastructure for real-time biomedical experiment execution. Using smart glasses, voice, computer vision, and protocol intelligence, we capture what scientists actually do at the bench, structure it into reproducible, analysis-ready data, detect deviations, and feed ELNs and LIMS. Our focus is standardized, traceable, AI-readable protocols and verifiable lab execution data. | We seek partners building mechanistic disease models, AI experiment-planning systems, autonomous and cloud labs, and qualified wet-lab networks. Dimenso can provide the execution capture layer: real-time protocol guidance, deviation tracking, structured experimental records, audit trails, and interoperable data outputs that help teams generate reproducible, gold-standard biomedical data across distributed laboratories. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Adam Kevelson | Domino Data Lab | adam.kevelson@dominodatalab.com | San Francisco, CA | Domino Data Lab is an Enterprise AI and Machine Learning Operations (MLOps) platform that allows organizations to build, deploy, and manage AI models at scale. It serves as a central hub where data scientists, IT teams, and business leaders can collaborate, share resources, and ensure compliance with strict industry regulations. | As a software platform provider, Domino is interested in teaming with research organizations, complementary technologies in Industry, or Services organizations who support deployment of AI MLOps solutions. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Roger Odegard | Draper (The Charles Stark Draper Laboratory, Inc.) | r.odegard@draper.com | Cambridge , MA | As a nonprofit engineering innovation company, Draper exists to solve critical national security and health security challenges, bringing together elite scientists, engineers, and mission partners to develop the next generation systems and solutions. Draper provides decades of experience with systems engineering and integration, microphysiological systems (MPS), physiological response, AI and ML enterprise solutions, and large scale program management expertise for IGoR. | We have identified partners with extensive mechanistic disease modeling expertise. We are searching for additional partners for all TAs that will complement our existing network of academic, nonprofit, industry, and CRO organizations. If you extensive experience in the TA3 area, please reach out. | TA2: New Science Engine, TA4: Experiment Marketplace |
| Tom Harrington | DrivenData | tom@drivendata.org | Boston, MA | DrivenData is a leader in bespoke AI model building, benchmarking, and data engineering for medical research. Past and current project work includes data science and AI development for ARPA-H, NIH, SNOMED, Go2 Foundation for Lung Cancer, Haystack Informatics, and Wellcome. Core capabilities span custom AI model development and in-depth performance evaluation and benchmarking on our proven platform, coupled with engineering ML-ready data pipelines for integrated research systems. | DrivenData experts are team ready to collaborate with a Prime Contractor to assist with design, development and implementation of complex data pipelines, ML and AI modeling, and AI benchmarking and evaluation components that will be needed to integrate TA2 Science Engine and TA1 Disease Models with TA3 Interoperable Procedures and TA4 Experiment Marketplace. | TA2: New Science Engine, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Arjav Shah | Drosera Biotechnologies | arjav@drosera.bio | Cambridge, MA | Drosera is an MIT spinout developing automation-native materials for biomolecule isolation. Our modality-agnostic materials platform replaces magnetic beads and resin columns, with tunable surface chemistry that supports diverse ligands (affinity, ion-exchange, hydrophobic) for selective capture of proteins, nucleic acids, and other targets. Delivers 10x more reproducible results, 15x faster processing, 95%+ recovery, and drop-in compatibility with robotic liquid handlers. | Drosera is seeking prime performers and TA leads assembling IGoR teams who need an automation-native sample prep partner. Particularly interested in protocol architects defining calibration artifacts and standardized workflows (TA3), cloud labs and CRO marketplace nodes needing reproducible consumables (TA4), and standardized upstream purification to reduce batch effects (TA1). We contribute faster, more reproducible drop-in consumables, & QC metadata for standardized protocol stacks. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace, TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Dmitri Krylov, PhD | DXComposer.ai | dmkrylov@gmail.com | Falls Church, VA | We are an innovative small business focused on AI diagnostics and medical data. Our expertise is in data pre-processing and AI model training. It includes patented technology. Our leadership previously worked at the NCBI on world largest biomedical dbs. | We will partner with Academia and large companies with complimentary expertise. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Ilan Ben-Meir | Dynamical Systems Group | ilan@dynamicalsystemsgroup.com | East Greenbush, NY | DSG is a systems engineering firm with nearly a decade of experience operationalizing emerging technologies for high-reliability organizations. We design mathematical models of complex socio-technical systems (including incentive structures, governance frameworks, and coordination mechanisms for multi-stakeholder systems). We validate our models through simulation before commitments are made, enabling HROs to safely deploy innovative solutions in situations where failure is not an option. | Expertise in wet lab research. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Solange Massa | Ecoatoms | solange@ecoatoms.com | Reno, NV | Ecoatoms has developed A.N.I.M.A., an onboard computer that uses a plug-and-play peripheral system for experimental reproducibility in space and on Earth. This core innovation powers their numerous automated hardware experiments and equipment for modular onboard labs, enabling high-throughput biomedical research and manufacturing across various space vehicles with minimal crew effort. | Ecoatoms is seeking CROs and research organizations to integrate our A.N.I.M.A. system for fully integrated, interoperable experimental setups. | TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Carmen Kivisild | Elnora AI, Inc | carmen.kivisild@elnora.ai | Salt Lake City, UT | Elnora AI builds an AI agent that generates and optimizes preclinical lab protocols. The agent turns scientific intent into structured, layered protocols that are human-readable and machine-executable, builds per-organization knowledge graphs from successful and failed experiments, designs follow-on experiments, and integrates into lab workflows via MCP, APIs, and LIMS. Focus: protocol standardization, agentic experiment design, and reproducible cross-lab execution. | Elnora covers TA2 and TA3. Need TA1 and TA4 partners. TA1: groups with mechanistic, multi-scale disease models in systems biology, hybrid AI and mechanistic approaches, or multi-omics integration, in IGoR priority diseases like neurodegeneration, chronic autoimmune, and oncology. TA4: CROs, university core facilities, robotic and automated wet labs, and distributed laboratory networks able to execute standardized protocols at gold-standard quality. Academic and industry teams welcome. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Barry Rothenberg | Embrient, Inc. | barry@embrient.com | San Diego, CA | Embrient Inc. provides physical reproducibility infrastructure for distributed live-cell biology. Our $2.1M NIH Fast-Track SBIR specifically targeted cell-culture reproducibility, funding Air Veil's static-environment core to maintain culture conditions during routine access. The broader platform addresses lab-to-lab variability through atmospheric pressure, lighting, gas control, telemetry, robot automation, and other patented & proprietary environmental standardization technologies. | Embrient seeks IGoR primes and consortia needing TA3 & TA4 support for physical execution equivalence across distributed live-cell labs. Ideal partners include AI orchestration companies, cloud labs, CRO networks, autonomous lab platforms, disease-model teams, and protocol & data infrastructure groups. We can contribute Air Veil-enabled culture nodes, environmental equivalence specifications, telemetry and API integration, QC gates, and cross site validation. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| David Gordon | Emory University | David.ezra.gordon@emory.edu | Atlanta, GA | Our group is focused on three main priorities. (1) Developing integrative co-scientist engines for literature and data integration, hypothesis generation, and experimental recommendation. (2) Building workflows to map context-specific cellular biochemical and signaling networks. (3) Applying proteomic and genetic perturbation approaches to map cellular functional pathways and establish causal relationships within them. | We are actively seeking teaming partners in the following areas. (1) Application of spatial transcriptomics and MALDI imaging to tissue sections, and associated analytical workflows. (2) Modeling of organ–organ communication. (3) Robotic and cloud laboratory infrastructure. (4) Cancer tissue repositories, biobanks, and associated patient cohorts. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Benny Budiman | Emory University | benny.budiman@emory.edu | Atlanta, GA | Emory University's research spans the full translational arc — from molecular and computational discovery through clinical and population-level science. Core strengths include AI for healthcare, biomedical informatics, biomedical engineering, immunology and infectious disease, oncology, neuroscience, and cardiovascular and chronic disease. Emory Healthcare, the Winship Cancer Institute, and partnerships with Georgia Tech and Morehouse School of Medicine extend this reach across the region. | For TA3, we are seeking partners with active engagement in laboratory automation and data standards — SiLA 2, Allotrope, COMBINE, Pistoia Alliance, or comparable open-protocol communities — and a track record of contributing to interoperable specifications. For TA4, we are seeking laboratory partners with validated, automated experimental capabilities, demonstrated cross-site reproducibility, and the ability to execute standardized protocols and return model-ready data and metadata. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Anant Madabhushi | Emory University & Georgia Tech | maria.nicholson@emory.edu | Atlanta, GA | Our organization focuses on developing AI-enabled, multimodal agentic systems to accelerate biomarker and drug discovery for complex diseases. Our team combines expertise in artificial intelligence, medical imaging, multi-omics, and clinical medicine to build interoperable research pipelines that integrate imaging, molecular, clinical, and biomedical literature data with automated hypothesis generation and validation. | We are seeking teaming partners with complementary expertise in AI, multi-omics, radiology, clinical research, clinical trials, drug discovery, and translational medicine. We are particularly interested in collaborators with access to diverse datasets, wet-lab validation capabilities, clinical trial expertise, or scalable computing infrastructure to support the development and validation of multimodal agentic discovery pipelines. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Si-ping Han | Epli.ai | si-ping@epli.ai | Los Angeles, CA | Epli.ai is an interactive AI workspace that allows agents to plan and execute complex tasks as multi-branched causal graphs. This creates intrinsically verifiable workflows that align in detail to user intent, and use discovered context to generate new instructions on the fly. We are working with a consortium of labs from UCLA, MD Anderson and the Terasaki institute to develop a proposal focused on cancer immunology. Expertise include structural biology, single cell biology, and organoids. | We are seeking partners who can contribute multi-scale, mechanistic modeling approaches, AI based modeling or workflow orchestration capabilities, database and cloud infrastructure solutions, and expertise in multi-scale disease biology. | TA4: Experiment Marketplace, TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Ozge Whiting | EQLabs, Inc | owhiting@eqlabsai.com | Providence, RI | EQLabs builds a lab AI execution and research data infrastructure platform for IGoR TA2 and TA3. VERA captures protocol intent, bench execution, instrument outputs, raw files, deviations, sample lineage, and analysis into permissioned, evidence-linked research memory. It reasons across disease models, protocols, results, and audit findings to flag knowledge gaps and recommend next experiments, turning every run into a governed, auditable, machine-readable data package. | We seek TA1 and TA4 partners. TA1: mechanistic disease-modeling teams, organoid or MPS groups, systems biology, and translational researchers with validated assays. TA4: validated labs, core facilities, CROs, and cloud or automated labs that execute standardized protocols and return high-quality data. With our lab AI platform, your models and assays gain governed, auditable, agent-ready data packages, shareable across the team, sponsors, and program managers with full provenance. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Scott Riggs | findwhatmatters.ai | scr@findwhatmatters.ai | San Francisco, CA | We integrate Bayes opt, DL surrogate modeling, and multi-agent AI with professional expertise in cell-free (synthetic cells) and semiconductor process engineering. IGOR’s architecture is uniquely informed by this experimental background, allowing us to mathematically represent and enforce complex domain-specific heuristics within the optimization loop. This capacity to translate physical constraints into robust model training is essential for grounding AI scientists to accelerate lab discovery. | Domain expertise, running experiments. We are looking for a lab, who wants to run experiments. | TA2: New Science Engine, TA4: Experiment Marketplace |
| Zoya Gluzman-Poltorak | Forta Bio | Zoya@forta.bio | Livermore, CA | Forta Bio develops FortaGuideAI, an AI engine for cell-type-specific oligo design using a 10¹⁵-molecule aptamer-oligo library and a closed-loop Designer-Judge-Learner architecture. Experimental validation is conducted via high-throughput in vitro screening and in vivo selection. Current disease focus: oncology, immunology, autoimmune. Targets: glioma, bone marrow, T-cells, endothelial cells, kidney, CNS, lung | Seeking partners needing an AI-driven experiment design engine (TA2) and wet-lab validation loop (TA3). Forta Bio contributes closed-loop hypothesis generation and experimental feedback for oligo-based therapeutics. Ideal partners have mechanistic disease modeling (TA1) or lab network capabilities (TA4) and seek a proven AI-wet lab integration for oncology or cell-targeting applications. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Heath Dorn | Fulcrum Defense Inc | hdorn@fulcrumdefense.ai | Henderson, NV | Fulcrum is an AI agent orchestration infrastructure for complex, multi-system environments requiring human-in-the-loop governance. Our research focus is MCP-native multi-agent coordination, shared context architecture, and auditability across distributed AI workflows. We apply these capabilities to accelerate research pipelines where fragmented tools, siloed data, and coordination overhead are the primary bottlenecks. | We seek teams with established mechanistic disease modeling capabilities, wet-lab execution infrastructure, and protocol standardization expertise. Ideal partners hold existing NIH ARPA-H relationships and can lead biological research design. We provide the AI orchestration layer: multi-agent coordination, human-in-the-loop workflows, shared context architecture, and distributed task management across heterogeneous research systems. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace, TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Edik Blais | ggomics | edikblais@gmail.com | San Bruno, CA | ggomics integrates multi-omic data into genome-scale network reconstructions to model dynamic responses to complex perturbations and deliver hypothesis-generating insights into mechanistic pathways related to disease biology ggomics leverages multi-scale models to simulate signaling (ODEs) and metabolism (FBA) within cells over time and between cells with spatial crosstalk and interactive microenvironments ggomics partners: University of Virginia School of Data Science and Biocomplexity | ggomics is open to teaming up with potential partners especially those with expertise in TA3 and TA4 as well as disease-specific leaders in TA1 and TA2 | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Ashwin Lokapally | GiwoTech Inc. | ashwin.loks@gmail.com | Cambridge, MA | GiwoTech develops AI-native tools to decode complex protein behavior that drives disease. Current research focuses on: (1) foundation models for protein–protein interactions and “undruggable” targets, (2) physics-informed neural network for atomistic molecular simulations, and (3) self-improving simulation workflows that learn from the most informative conformational states. These capabilities power models of disease pathways to accelerate target discovery and design of precision therapeutics. | Seeking partners in TA3 and TA4: labs or platforms with robust automated experimentation, LIMS, ELN integration, and experience running highly standardized protocols and groups able to build scalable marketplaces for routing, tracking, and QC of experiments. For TA1 & TA2, we welcome collaborators with rich multimodal disease datasets and expertise in mechanistic models to couple with our AI-native platform, enabling fully closed-loop hypothesis generation and validation across diseases. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Zeke Maier | Google Public Sector | zekemaier@google.com | Reston, VA | Google Public Sector provides foundational cloud infrastructure and frontier AI to accelerate scientific discovery. We provide scalable compute (TPUs, GPUs), data analytics (BigQuery), and MLOps (Colab Enterprise, Model Garden). We enable research via Gemini Enterprise and SOTA Science AI models (Co-Scientist, TxGemma), and Gemma fine-tuning. We empower biomedical research through scalable, secure AI platforms designed to build and orchestrate complex biological models. | We seek to partner as a technology enabler with prime bidders. We are looking for multidisciplinary consortia that possess deep biological expertise and wet-lab capabilities, but require a robust tech backbone. We want to empower teams needing scalable cloud computing, secure cross-institutional data architectures, and advanced AI orchestration. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Chirag Patel | Harvard Medical School | chiragjpx@gmail.com | Boston, MA | Meta-science, AI for biological discovery, exposomics, genomics | Foundation modeling | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Justin Diamond | Hetzerk | justindiamondmusic@gmail.com | Naples, FL | Advanced AI and distributed computation research and infrastructure development across biology, chemistry, physics, and cognitive sciences. | Research or partner organizations with more experience with ARPA. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace, TA1: Comprehensive Disease Models |
| Nicholas Schork | HonorHealth | schorknicholas@gmail.com | Scottsdale, AZ, AZ | Next-generation human biology studies rooted in patient-oriented research studies. | Partners with new health assessment and monitoring technologies (e.g., wireless devices, use of microneedle based assays) or extensive experience withe existing technologies (e.g., mass spec, survey instruments, etc.) | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Marc Salit | Hypothetica, Inc. | marc@hypothetica.ai | McLean, VA | Hypothetica is building standards-based decentralization of experimental science. AI is formulating hypotheses, designing experiments, and analyzing data. But we need innovation to go from vision to execution of experiments in the physical world. Lab automation and big capex are being used to bring a “body” to the “mind” of the AI-scientist -- we are premised on creating scalable general purpose solutions through disaggregation of experimental workflows with programmable execution. | We want to bring our experience and vision for an interoperable ecosystem of experimental to a vital teamed project that changes how we can leverage AI to do more and better science. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| James Kozloski | IBM Research | jkozloski@gmail.com | Yorktown Heights, NY | IBM Research, with Cleveland Clinic's Lerner Research Institute, builds AI for mechanistic, multiscale disease modeling, treating disease as a dynamical system. Focus areas: biomedical foundation models for omics and perturbation analysis, physics-informed neural operators and AI closure methods coupling cellular to tissue scale, stochastic inference, agentic orchestration that designs experiments under decision gates, and selective quantum acceleration. Validated on patient-derived data. | We pair AI and mechanistic modeling with established clinical and patient-derived experimental grounding. We seek partners who extend computational and physical-science sides of the loop: laboratory automation and robotics for portable, machine-executable protocols, optimal experimental design, sequential decision-making, and uncertainty quantification, and complementary mechanistic modeling in tissue biomechanics, transport, fluid dynamics, and imaging. Composable, interoperable contributions. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Samira Asgari | Icahn School of Medicine at Mount Sinia | samira.asgary@gmail.com | New York, NY | I lead a computational human genomics and statistical genetics group at Mount Sinai focused on immune-mediated and infectious diseases. My lab discovers new disease biology and potential drug targets by leveraging large-scale EHR-linked biobanks, multi-omics integration, causal and statistical modeling, and translational interpretation of human genetic findings. | We are seeking partners building AI-guided systems for iterative experimentation and disease modeling. I am especially interested in teams aiming to connect human genetic evidence with experimentally testable disease models, including large-scale multi-layer analysis of human genomic and molecular data, perturbation screens, primary-cell or organoid models, automation, and scalable data infrastructure. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Ratna Thangudu | ICF | ratna.thangudu@icf.com | Rockville, MD | We develop AI-enabled solutions for biomedical and healthcare research, with expertise in scientific knowledge integration, multimodal data analysis, literature and data synthesis, agentic workflows, and researcher-facing decision support systems. Our work includes experience supporting the ARPA-H Biomedical Data Fabric (BDF) program, connecting heterogeneous data sources, publications, and domain knowledge to accelerate discovery and scientific reasoning. | We are interested in partnering with organizations pursuing IGoR, particularly teams with strengths in mechanistic disease modeling, systems biology, computational biology, experimental design, laboratory automation, and translational research. We believe our strongest contribution aligns with TA2 (New Science Engine) and are interested in collaborations that combine scientific modeling and experimentation with AI-driven reasoning and orchestration capabilities. | TA2: New Science Engine |
| James Johnson | Independent | avprules96@gmail.com | Snyder, OK | Therapeutic Convergence Framework now covering ~100k ailments. UTEP parametric cure equation. Human on Chip v7 whole human body simulator. Nanomedicine platform designs. Various web applications (PISCES, CRISPRGen, TreatmentProtocols) | I am an independent researcher with experience working with AI. I follow the data and I do not force my supposition while working toward the goal, cures. I will go back to the drawing board as many times as I have to. | TA2: New Science Engine, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| Pooja Walia | Independent Researcher | poojawalia0607@gmail.com | Seattle, WA | Healthcare AI governance and AI-as-a-medical-device safety. Active areas: layered governance for clinical AI separating life-critical from advisory pathways, two-level human oversight design, FHIR-based AI provenance tracking, and federal docket engagement with FDA, CMS, NIST. IEEE peer-reviewed publications in healthcare critical-infrastructure security and AI-driven AMR detection. ICLR 2026 and ICML 2026 reviewer. IEEE 802 balloter. Active GitHub contributor to NIST FederalProfile-8259A. | Seeking academic medical centers, biomedical research institutes, and AI-ML labs needing a governance, safety, or regulatory lead on IGoR proposals. Bring federal docket engagement -3 comments to FDA, CMS, NIST May 2026. 6 NIST GitHub PRs, IEEE peer-reviewed publications, ICLR 2026 and ICML 2026 reviewer record, and IEEE Senior Member standing. Available as co-investigator, governance subteam lead, or oversight advisor on research-infrastructure tooling and AI-safety pathways. | TA3: Interoperable Experimental Procedures |
| Jason Meyer | Indiana University School of Medicine | jasonmeyer76@gmail.com | Indianapolis, IN | Our organization develops human stem cell–based platforms to model and repair the central nervous system (CNS). We engineer iPSC-derived neural, glial, retinal, and brain multicellular systems integrated with microfluidics, electrophysiology, advanced imaging, CRISPR engineering, and AI-enabled analytics to study neurodegeneration, neuroinflammation, connectivity, and regeneration. Our work supports therapeutic discovery and translational modeling across diverse CNS disorders. | We are seeking teaming partners with expertise in scalable automation, high-throughput data infrastructure, cloud-based AI analytics, and commercialization of advanced biomedical platforms. We are particularly interested in collaborators capable of industrializing CNS microphysiological systems through robotics, large-scale multimodal data integration, regulatory strategy, and deployment of clinically and commercially scalable technologies for neuroscience and regenerative medicine. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Thomas Bozada | Insilica | tj@insilica.co | Rockville, MD | Insilica develops AI-enabled tools for mechanistic biomedical research, toxicology, disease modeling, and pathway analysis. We have worked with academia, government, and industry to support evidence integration, adverse outcome pathway mapping, structure-activity prediction, and computational prioritization for complex biological questions. | We seek partners with complementary wet-lab and translational capabilities: disease models, reproductive biology or organoid expertise, and lab automation. Insilica is open to leading a TA2-centered proposal or contributing as the AI-knowledge infrastructure partner within a broader TA1 through TA4 consortium. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Luca Emili | InSilicoTrials | luca.emili@insilicotrials.com | Boston, MA | InSilicoTrials is an FDA and EMA endorsed company accelerating drug development through AI and predictive technologies. For IGoR, we deliver agentic orchestration of preclinical research, including mechanistic disease modeling, ADME Tox prediction, PK PD simulation, and dosing optimization — integrated into a unified cloud platform that connects distributed labs and drives hypothesis-to-experiment cycles up to 10x faster. | We're seeking partners for two areas: TA3 teams expert in interoperable protocol architectures, standardized experimental procedures, and cross-lab reproducibility and TA4 validated wet labs, CROs, or cloud labs able to execute standardized preclinical protocols across cell tissue culture and multicellular systems, returning structured, model-ready data. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Peter Walker | Intelligenesis LLC | pete.walker@intelligenesisllc.com | Columbia, MD | IntelliGenesis develops agentic AI pipelines and counterfactual reasoning frameworks for LLMs, designed as scientific discovery engines that mirror formal hypothesis-testing methodology. Our systems identify knowledge gaps, generate structured hypotheses, and recommend targeted experiments — capabilities directly transferable to biomedical discovery. We also develop federated, zero-trust data infrastructure supporting scalable, secure AI deployment across distributed research environments. | IntelliGenesis brings LLM-driven hypothesis generation, agentic orchestration, and zero-trust data architecture. We seek partners with expertise in mechanistic disease modeling, computational biology, and wet-lab experimental execution who can ground our AI reasoning frameworks in validated biological systems — enabling end-to-end pipelines from knowledge gap identification to gold-standard experimental data return. | TA2: New Science Engine, TA4: Experiment Marketplace |
| Jenhan Tao | Intertwined Biosciences | jenhan@intertwined.bio | Cambridge, MA | Intertwined Biosciences develops AI-native therapeutic discovery platforms and engineered macrophage cell therapies for chronic inflammatory and fibrotic disease. Our research integrates comparative mammalian biology, macrophage engineering, CRISPR-based functional screening, and machine learning to identify and translate naturally evolved disease-resilience mechanisms into regenerative therapeutics, initially focused on advanced liver fibrosis and cirrhosis. | Intertwined Biosciences is seeking teaming partners with expertise in laboratory automation systems, high-throughput screening, liquid handling, and scalable experimental workflows for cell engineering and functional genomics. We are particularly interested in collaborators who can help integrate automated experimental platforms with CRISPR screening and single-cell sequencing. Intertwined brings expertise in AI, machine learning, and computational biology for therapeutic discovery. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Ram Prasad | InvictusLabs | invictuslabs.ai@gmail.com | Greater Philadelphia, PA | InvictusLabs is on the mission to leverage the convergence of data, connectivity, and advances in computing and AI to optimize Intrinsic Capacity and Extend Human Healthspan. We are developing a comprehensive, highly personalized digital-twin platform that models an individuals physiological and resilience dynamics. This will deepen our understanding of human physiology, predict responses and adaptations to behavioral and environmental stimuli, and enable proactive, preventive interventions. | We created an Agentic AI-driven Care Transformation platform with Autonomous & Semi-autonomous AI Agents for every stage of patient journey alongwith disease-agnostic clinical AI Supervisory Agent for real-time clinical AI oversight that monitors, evaluates, and ensures safety of autonomous clinical AI systems. This foundation is transferable to TA2 and TA3 in research domain. Looking to partner with performers with strong computational biology (TA1) and laboratory networks (TA4) capabilities. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Robert Fine | IVRHA (International Virtual Reality and Healthcare Association) | bob@coolbluemedia.net | Washington, DC, DC | We are building a virtual reality headset for use within a wide variety of healthcare applications and settings. We are also exploring new applications that can be developed by running LLMs on device. | Hardware and software engineering expertise. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| William Garneau | Johns Hopkins | will.garneau@gmail.com | Baltimore, MD USA, MD | Use of real world data to improve care for persons with substance use in a rapidly changing illicit drug supply | Data science expertise using large data sets | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Anthony Leung | Johns Hopkins | Anthony@leunglab.org | Baltimore, MD | The Leung lab (JHU BSPH) studies the macrodomain ADP-ribosylation regulatory axis — viral and host enzymes that remove or read ADP-ribose modifications regulating immunity, stress response, and translation. We maintain ADPriboDB, the curated database of ADP-ribosylated proteins. Active programs include macrodomain inhibitor and chemical-probe discovery, alphavirus host–pathogen biology in human cell line and organoid systems, and stress-granule biology. | We are assembling a JHU-anchored team for an AI-driven closed-loop discovery platform centered on the macrodomain ADP-ribosylation regulatory axis. Core members are in conversation across TA1–TA4. Seeking additional collaborators with: software architecture for open-source and API-first systems (TA3 interoperability), qualified TA4 marketplace labs (cell-culture, organoid, biochemistry), and project management for multi-team coordination. | TA1: Comprehensive Disease Models |
| Ahmed Hassoon | Johns Hopkins University | ahmed.alhassoon@gmail.com | Baltimore, MD | AI co-scientist: we are funding by NIH and supported by Anthropic to develop an AI co-scientist capable of conducted a study from hypothesis, study design, study analysis, interpretation, and writing the manuscript. We finished iteration one. And ready for small scale deployment within the NIH community. | TA4 | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Jeff Mumm | Johns Hopkins University | jsmumm@gmail.com | Baltimore, MD | We are advancing an AI-assisted, robotics-automated research ecosystem – deployable as an out-of-the-box system across multiple labs – designed to meet challenges inherent to discovering and optimizing multifactorial therapeutics for complex polygenic diseases. The platform operates in parallel and iteratively on three fronts: cross-species polygenic disease modeling in human organoids and HTS-ready organisms, and rational high-throughput multifactorial therapeutic discovery and optimization. | We have assembled a multi-institutional team with expertise in AI-ML-assisted experimental design and high-dimensional data analysis, nanotechnology-enabling cell-specific delivery, cross-species HTS assay development, organoid & organismal disease modeling. We seek additional-expanded expertise in Design of Experiments theory, AI-assisted 3-, 4-, and 5D data segmentation, population genetics of polygenic human disease, HTS-ready disease modeling, and medicinal chemistry. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| Alex PAUNESCU | Johnson Johnson | paunescu.a@gmail.com | Clinton, NJ | Consulting in continuation of my work at J&J | Correlating business towards a larger goal | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| David Rastall | Jonhs Hopkins | rastall@gmail.com | Baltimore, MD | Johns Hopkins has very large datasets of both live (in human) disease data, basic research data, and EHR slash medical process data and applications and are building out AI simulation environments. | We are looking for teams with technical expertise in novel AI and data architectures. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Rachel Clipp | Kitware | rachel.clipp@kitware.com | Carrboro, NC | Kitware, Inc. is an open-source research and development company with experience in medical modeling and simulation, AI across multiple domains, including healthcare, and develops software solutions to address the data organization and evaluation needs for academics, industry, and government customers. is a leader in mechanistic modeling for disease. We are the lead developers of and maintain the Pulse Physiology Engine, a whole-body computational model. | We are looking to join a team as a subcontractor. We are looking for a team that has experience a large proposal and program and can address the needs of TA3 and TA4 in particular with interest in our participation in TA1, TA2, and TA3. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Darcy Ziegler | KUNGFU.AI | darcy.ziegler@kungfu.ai | Austin, TX | KUNGFU.AI delivers production-grade AI for health and government missions. Our core focus areas include agentic AI orchestration, knowledge graphs, deep learning-based data fusion, NLP, computer vision, and anomaly detection. Past performance includes a DHA biosurveillance project for multi-source pandemic detection and response, a federated learning CV model on 1.6M mammograms across global hospital networks for FDA submission (Clairity), and opioid risk models with bias metrics for CMS. | KUNGFU.AI seeks teams with mechanistic disease modeling expertise, wet-lab execution capabilities, and clinical and biomedical domain depth to complement our AI and ML engineering and agentic orchestration capabilities. Ideal partners are pursuing IGoR TA1 or TA3 slash TA4 (disease models and the protocol or lab marketplace) where KUNGFU.AI contributes the AI orchestration and knowledge gap identification layer. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Junhao Wen | Laboratory of AI and Biomedical Science (LABS), The Trustee of Columbia University of the City of New York | junhao.wen89@gmail.com | New York, NY | Our lab develops AI and computational biology methods to model human aging and complex disease using multi-scale data, including multi-organ imaging, genomics, proteomics, metabolomics, and clinical records. We focus on mechanistic disease modeling, causal biological relationships across organs and molecular systems, biomarker discovery, and AI-guided hypothesis generation for rigorous, reproducible biomedical research. | We seek teaming partners with expertise in mechanistic multi-scale disease modeling, AI-driven experimental design, reproducible protocol development, and laboratory validation. Ideal partners can help encode causal biology across scales, identify knowledge gaps, design optimal experiments, standardize protocols for broad lab adoption, and generate high-quality, gold-standard data through validated laboratory networks. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Chris Mungall | Lawrence Berkeley National Laboratory | cjmungall@lbl.gov | Berkeley, CA | Multi-scale modeling, disease modeling, agent-based co-scientists for hypothesis generation, systematized languages for experimental protocols, high throughput experimental capabilities in structural biology and synthetic biology | Seeking to support teams and provide IV&V | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Syed Ahmed | Lifeline AI | Abe@projectlifelineai.com | Houston, TX | Lifeline AI’s AMINA (Autonomous Multimodal In Silico Neuro-symbolic Architecture) is an AI-driven therapeutics engine that drastically cuts the time and cost of drug discovery. Operating as a closed-loop cyber-physical system, AMINA uses negative constraint vectors to learn from failure, generating highly de-risked therapeutic assets for rapid ex silico validation to address critical unmet clinical needs. | Lifeline AI is seeking robotics and laboratory automation partners to bridge the gap between AI-driven design and physical execution. We require collaborators capable of integrating our AMINA therapeutic blueprints directly into automated, robotic synthesis and microfluidic platforms. Our goal is to connect our computational engine to a physical synthesis loop, creating a fully autonomous, cyber-physical pipeline for rapid drug discovery. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Christopher Canova | Lila Sciences | ccanova@lila.ai | Cambridge, MA | Lila Sciences is building scientific superintelligence. Our reasoning model, IRIS, closes the design-build-test-learn loop by orchestrating actions inside our state-of-the-art autonomous labs, running every step of the scientific method with a human-in-the-loop. | Seeking collaborators with disease model domain expertise and translational medicine capabilities. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Kacey Ronaldson | Link Biosystems | kacey.bouchard@linkbiosystems.com | Irvington, NY | Link Biosystems develops low-shear, pumpless 3D perfusion bioreactors with integrated electrical stimulation for reproducible manufacturing of iPSC-derived organotypic tissues. | Seeking partners whose capabilities complement ours for AI orchestrated, distributed research ecosystems, computational systems biology and mechanistic disease modeling groups, AI ML orchestration and self-driving lab software teams. | TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| Eli Bogart | M2 Foundry | ebogart@gmail.com | Somerville, MA | Research focus areas include application of agentic AI methods to complex system simulation, effective human-AI teaming, and AI-enabled tools for accelerating scientific research. Our computational biology team has experience with multiple approaches to computational modeling of biological systems in health and disease and their applications to early-stage drug discovery. | We especially seek partners with expertise in specific disease areas and experimental approaches, high-throughput experimentation capabilities, and-or experimental standardization and interoperability. However, we are eager to discuss collaboration on any aspect of the program. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Nirav Amin | Manifold AI | namin@manifold.ai | Newton, MA | Manifold is an AI Data Platform that enables large scale collaboration across multimodal data. | Manifold provides the platform layer where data and agents can be shared. Teaming partners would run the experiments and generate the data that would the platform's ability to orchestrate AI agents that rapidly feedback from insights to reproducible analyses. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Yevheniy Medvediev | MatGen | yevheniy@matgenlabs.com | Boston, MA | MatGen builds mechanistic, multi-scale computational models of disease biology. Core capabilities span multi-omics integration and target ID, GNN, transformer, and other ML models of biological systems, structural and molecular modeling, and AIML systems for hypothesis generation and experiment prioritization across modalities and indications. This maps to IGoR TA1 (disease models) and the computational core of TA2. | Seeking performers with complementary, non-overlapping capabilities to complete an IGoR team: validated wet-lab execution across multiple modalities and a qualified-laboratory network (TA4), lab automation and robotics, protocol standardization (TA3), and distributed-systems and data engineering. MatGen contributes the TA1 disease-modeling and the TA2 computational and AI layer. We want a prime or co-performers who need that depth resident on the team. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Zamal Ahmed | MD Anderson Cancer Center | ZAhmed@mdanderson.org | Houston, TX | Our research program decodes intracellular signal-transduction pathways, emphasizing protein interactions and modifications driving tyrosine kinase cascades. Using live-cell FLIM and super-resolution nanoscopy, we capture dynamic macromolecular assemblies to design structure-based allosteric inhibitors. We also study genomic stability and DNA repair to exploit vulnerabilities in replication fork protection, aiming to overcome tumor resistance to therapies like PARP inhibitors. | A multi-disciplinary team to transition structural oncology insights into clinical solutions. AI Drug Designers will model transient allosteric pockets to accelerate small-molecule discovery. Translational Oncologists will evaluate compounds in patient organoids for phase-I trials. Biomedical Engineers will construct microfluidic tumor platforms for live-cell nanoscopy, while Spatial Multi-Omics Experts map cellular genomic shifts to block escape pathways. | TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| Danielle Walker | MedAcuity | dwalker@medacuity.com | Westford, MA | MedAcuity delivers expert software engineering, systems architecture, and verification for regulated life sciences and robotics. Our focus includes designing secure, interoperable distributed software architectures, standardizing data protocols for heterogeneous hardware and developing embedded control systems for laboratory automation and advanced robotics. We ensure end-to-end data integrity, robust cybersecurity, and rigorous V and V for complex, mission-critical systems. | We seek prime contractors, academic institutions, or AI and ML research organizations leading iGOR proposals, specifically those building the AI-driven orchestration, foundational biological models, or mechanistic disease frameworks, TAs 1 and 2. We want partners needing a proven, compliant engineering co-developer to translate complex algorithmic outputs into standardized protocols, secure cloud networks, and seamless, automated physical laboratory integrations, TAs 3 and 4. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Chandana Haque | Medra | chandana@medra.ai | San Francisco, CA | Medra is a San Francisco-based AIxBio company building its Physical AI Scientist platform, an autonomous robotic wet lab that independently designs, executes, and analyzes biological experiments for drug discovery. Earlier this year, Medra announced Medra Lab 001, the largest autonomous lab in the US with 100 robots in operation and its collaboration with Genentech to accelerate and enable closed-loop drug discovery. | Seeking disease models and biological platform partners to power learning loops and build biological data sets at scale. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Ian Gonzalez | Michigan Neuroscience Institute (University of Michigan) | igonzale@umich.edu | Ann Arbor, MI | MNI’s IGoR framework integrates closed-loop AI with differential equation models to map causal biology. We focus on Alzheimer’s and repeat expansion diseases using automated Drosophila behavioral platforms and human iPSC and organoid systems, strictly bypassing in vivo vertebrate models. Our infrastructure supports petabyte-scale connectomics and spatial transcriptomics. | We seek industry and academic partners to expand our distributed marketplace of validated labs (TA4) and automated protocol execution (TA3). Ideal partners provide robotic iPS and organoid culture platforms, automated behavioral assays, or interoperable computational architectures for our AI orchestration layer (TA2) to accelerate rapid, high-speed drug repurposing. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Kevin Dai | Mimetic | kevin@mimetic.ink | Pittsburgh, PA | Mimetic is building automated platforms for microphysiological system development. Focus on tissue engineering, bioprinting, lab automation hardware, and AI-powered design & protocol generation. | We are looking for academic and industry partners to support computational disease modeling (TA1) and validated labs (TA4) with focus areas in immunotherapy and oncology. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Jeremy Goecks | Moffitt Cancer Center | jeremy.goecks@moffitt.org | Tampa, FL | Basic and applied biomedical data science research with focus on artificial intelligence and machine learning methods. | Experts in federated machine learning and interest in lab-in-the-loop validation | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| June Lee, MD, PhD | National Society of Medical Scientists (NSMS) | Dr.JuneLee@nsmsusa.org | Bethesda, MD | National Society of Medical Scientists (NSMS) develops autonomous AI-driven research ecosystems integrating mechanistic disease modeling, digital twins, causal inference, multimodal biomarkers, autonomous experiment design, robotic laboratory orchestration, and clinical translational science. Our AURORA architecture combines AI agents, interoperable protocols, distributed research networks, and real-world clinical data to accelerate scientific discovery and therapeutic development. | NSMS seeks academic, clinical, biotechnology, pharmaceutical, CRO, laboratory automation, robotics, data infrastructure, and AI partners with expertise in disease biology, omics, experimental validation, protocol standardization, autonomous laboratories, high-throughput screening, and multi-site research execution. We welcome organizations interested in co-developing scalable, interoperable, AI-enabled research ecosystems aligned with all IGoR technical areas. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Natasha Shtraizent | NebulAi | natasha.shtraizent@gmail.com | New York, NY | NebulAi is an AI-computational biology company developing a high-fidelity model of cancer dormancy and recurrence at patient-grade resolution. The product in development is CURE.SIM platform that enables scientists to simulate cancer cell adaptation in the context of normal organ tissue and tumour microenvironment without requiring complete temporal single-cell or metabolomic data. It will also enable collaborative data enrichment with academic and clinical partners. | We are looking to connect with: quantum computing labs for metabolomics-to-Boolean translation (TA2), ML and AI orchestration teams, building new agents to support virtual biology experimental design and protocol standardization (TA3), and clinical networks within a hospital for validation of the simulations with patient samples and with wet labs core facilities for experiment validation and implementation (TA4). | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Manish Kulkarni | Netra Systems, Inc. | mailmdk@gmail.com | Pleasanton, CA, CA | Ophthalmic imaging and diagnostics | Ophthalmic imaging and diagnostics | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Rene Anand | Neurxstem Inc. | rene.anand@neurxstem.com | Heath, OH | Neurxstem Inc., a pioneer in precision brain health technology, is addressing some of the most pressing public health crises of our time—Alzheimer’s disease, Parkinson’s, autism, opioid addiction, and age-related cognitive decline. Using its patented human brain model platform, NNOP™, Neurxstem is delivering the world’s first lab-based tools that accurately replicate the root causes of major human brain diseases, providing a new path toward early detection, prevention, and intervention. | Harmonization of big data with clinical data. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Mihir Pershad | Noka Bio, Inc | mihir@nokabio.ai | Wilmington, DE | Noka AI develops AI-driven platforms for systems biology, metabolic modeling, and multi-omic data integration to accelerate predictive biotechnology and disease modeling applications. Our work focuses on computational biology, virtual cell modeling, AI-enabled bioprocess optimization, and translational modeling frameworks for industrial biotechnology, therapeutics, and precision health applications. | We are seeking partners with expertise in disease biology, multi-omics data generation, experimental validation, AI or ML for biology, computational modeling, and translational biomedical research. We are particularly interested in collaborators working on disease models, mechanistic biology, clinical datasets, and scalable infrastructure for AI-enabled life sciences research. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Vito Quaranta | Northeastern University | v.quaranta@northeastern.edu | Boston, MA | AI-Systems Biology of Human Disease | Our team has deep expertise in two areas: 1. AI-ML modeling from large, possibly longitudinal datasets 2. Chemistry of xenobiotics that could act as environmental cause of human disease | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Gabe Richman | Omic Inc. | gabe@omicmd.com | Seattle, WA | Omic builds AI-driven infrastructure for autonomous biomedical research across three integrated products. Omic.ai is an agent-based research platform that designs experiments, interprets results, and iterates across literature, omics, and structural data. AttestDB is a claim-native knowledge graph database providing provenance, contradiction resolution, and belief revision for AI agents. VibeSci is a distributed compute network for citizen-driven scientific workloads at scale. | We are seeking consortium partners anchoring wet-lab execution and disease modeling for IGoR. Strong fit with teams operating cloud or distributed laboratories, academic medical centers building mechanistic disease models, and groups developing standardized experimental protocols. Omic contributes the AI orchestration, provenance, and interoperability layer ensuring reproducibility, inter-laboratory concordance, and continuous disease-model refinement from returned experimental data. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| Donghoon Lee | Omphalos Lifesciences Inc | donghoon.lee@omphaloslifesci.com | Dallas, TX | Omphalos Lifesciences pioneers proprietary AI-driven, human-in-the-loop executable biology technology for scalable, mechanistic, multiscale biological simulation. We construct, simulate, debug, refine, and 3D-render digital cell, digital human, and disease models that integrate molecular, cellular, tissue, organ, and system-level mechanisms to support quantitative hypothesis testing, therapeutic discovery, and model-guided experiment design. | We seek TA2, TA3, TA4 partners with complementary strengths across AI, experimental biology, laboratory automation, data generation, validation, and translational research. Please contact us if your organization has scalable technology or infrastructure in these areas. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Brian Abent | Open Enzyme | brian.abent@gmail.com | Humacao, PR | Open-source, fully-public AI-augmented therapeutic discovery platform. Canonical disease: gout and hyperuricemia. (1) Chokepoint-first causal disease modeling across complement, NLRP3, urate-disposal, and microbiome axes. (2) Agentic literature synthesis plus reproducible computational priors (comp-NNN) before wet-lab spend. (3) Multi-modality engineering: koji, LBP, siRNA, TCM x rigor. (4) Home-fermentable distributed reproducibility layer for community validation. | Validated wet-lab partners across our gated bottlenecks: A. oryzae transformation (signal-peptide and protease-deletion strains), epithelial-transwell trafficking assays (ABCG2 Q141K), THP-1 NLRP3 readouts under MSU challenge, RNA-seq and flow cytometry capacity. Also clinical and biobank collaborators for genotype-stratified analyses (UK Biobank, FinnGen, East-Asian cohorts), TCM extract sourcing and QC, LBP chassis engineering, regulatory plus clinical-trial design for repurposing tracks. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Jeremy Linsley | Operant BioPharma | jeremylinsley@operant.bio | SAN FRANCISCO, CA | Operant runs a closed-loop optogenetic microscopy platform on human iPSC-derived neurons with live-cell biosensors including GEDI and AI-driven adaptive control. We are developing BioRL-Gym, a portfolio of verifiable-reward biology environments for AI agents, anchored on oxidative-stress-driven neurodegeneration in Parkinson disease. Core tech: CODA light-gated protein degradation, real-time single-cell perturbation and measurement during longitudinal imaging at scale. | Seeking partners across all four technical areas. TA2 multi-agent AI orchestration with human-in-the-loop augmentation. TA1 and TA4 computational protein design groups. TA3 and TA4 autonomous wet-lab platforms. TA3 software architects for interoperable experimental protocols. Organoid groups for Phase II multicellular expansion. Operant contributes a wet-lab and disease-model anchor with a reference closed-loop environment running today. Flexible on lead or sub-performer positioning. | TA1: Comprehensive Disease Models, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Adam Richardson | Panome Bio | adam.richardson@panomebio.com | St Louis, MO | Panome Bio is a WashU-affiliated CRO specializing in untargeted, single-sample multi-omics—metabolomics, lipidomics, and proteomics. Unlike global (large-library) approaches, untargeted profiling captures unknown, undiscovered molecules, so each dataset holds genuinely new biology. We already apply ML to our data and engineer gold-standard protocols and reproducible, machine-readable data—produced across multiple sites and structured to be AI- and automation-ready for downstream modeling. | Panome Bio seeks to join a team as a subcontractor delivering TA3 and TA4: standardized, reproducible protocols and validated, high-throughput multi-omics data. We are not the AI experts—we are the wet-lab partner that understands them, structuring protocols and data to be machine-, robot-, and AI-ready. We seek a prime and collaborators strong in TA1 disease modeling and TA2 AI orchestration, plus data engineering and lab automation, for interoperability with your models. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Erlyn Rachelle Macarayan | PatientsLikeMe | emacarayan@patientslikeme.com | Boston, MA, MA | PatientsLikeMe focuses on patient-centered real-world data, digital engagement, and evidence generation across chronic and complex diseases. Our work integrates longitudinal patient-reported outcomes, patient experience insights, recruitment analytics, and digital research workflows to support disease understanding, study design, trial execution, and translation of biomedical evidence into practice. | PatientsLikeMe seeks teaming partners with expertise in mechanistic and computational disease modeling, AI and ML orchestration, interoperable experimental protocols, laboratory automation, multi-omics data integration, causal inference, and secure research infrastructure. We are especially interested in partners who can connect patient-centered real-world evidence with experimental systems and model validation. | TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| Sanjiv Desai | Peraton | sanjivdesai2000@gmail.com | Reston, VA | Peraton develops advanced AI - ML, cloud, and data-driven solutions across public health, biomedical, and government environments. Current focus areas include scalable AI infrastructure, model orchestration, scientific workflows, mechanistic and non-mechanistic modeling, agent-based modeling & simulation platforms, Agentic AI, and secure cloud-native architectures supporting operational AI and research ecosystems. | Peraton is interested in potential partners with expertise in AI infrastructure for scientific research, biomedical AI, accelerated computing, autonomous experimentation, computational biology, biological foundation models, and synthetic biology. We are particularly interested in organizations that complement Peraton's strengths in systems integration, cloud environments, workflow automation, modeling & simulation ecosystems, and operational deployment of AI research platforms. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Daniel Reda | Perturb Bio, Inc. | daniel@perturb.bio | Dover, DE | We build a simulatable digital twin of the failing human heart: a mechanistic, closed-loop model of dilated cardiomyopathy (the leading transplant indication) in iPSC-cardiomyocytes. TA1: a running causal model from gene regulation to electrophysiology. TA2: active-learning choice of the next experiment. TA3+TA4: a named, costed iPSC-CM wet-lab node with a layered, QC-gated protocol stack. Cardio-oncology (anthracycline heart injury) is our entry point. | As prime, we're seeking: TA1 mechanistic and multiscale modelers to extend the twin from cell to organ and whole-heart scale, TA3+TA4 reproducibility and measurement-standards partners (minimum-performance-specification and calibration for distributable assays), and a second validated iPSC-cardiomyocyte lab for cross-lab concordance. Open to mechanistic-modeling, lab-automation, and standards groups, and to cardio-oncology and heart-failure clinical collaborators. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Vladimir Makarov | Pistoia Alliance | vladimir.makarov@pistoiaalliance.org | Wakefield, MA | The Pistoia Alliance is a pharmaceutical and biotech industry pre-competitive collaborative consortium with over 200 member organizations including 17 out of 20 largest pharma firms. We are actively developing projects in Ai and data standards, covering the objectives 2 and 3 of this RFP. (AI orchestration layer for finding knowledge gaps and optimal experimental design and a layered protocol architecture for experimental reproducibility). | We seek teaming partners in areas 1 and 4, and contributors to areas 2 and 3. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Sean Manion | Praxis Science | stmanion@gmail.com | Pittsburgh, PA | Scientists building tech for science. Praxis Science (PraxSci) is building a bridge between traditional science (TradSci) and tech-enabled decentralized science (DeSci). Building communities of scientists to define the requirements for the specialized tech they need, subfield by subfield rather than generic one size fits all models. Programmable governance for communities to define their terms, processes and workflows. A human loop to endure appropriate curation and weighting of evidence. | Larger tech capabilities that can conform to amd support a science first model | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Yihang Shen | Princeton University | ys9596@princeton.edu | Princeton, NJ | We develop new AI algorithms for solving complex biological questions. Have experience in developing disease models, and wet-lab protocols. | We seek people who have experience in AI agent or have the capabilities to lead TA4 marketplace execution or others complement with our expertise. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Noelle Germain | Quiver Bioscience | noelle.germain@quiverbioscience.com | Cambridge, MA | Quiver Bioscience is a CNS-focused drug discovery company developing AI-native tools to accelerate target identification, compound optimization, and toxicity prediction. Our platform integrates human neuronal models and optogenetics-based functional assays with multimodal biological data to identify novel therapeutic targets across neurological indications and predict safety of drug candidates at early stages. | Quiver seeks partners with capabilities aligned to IGoR TA3 and TA4: groups experienced in developing reproducible, layered protocol architectures for complex neuronal assays, and validated laboratories able to execute standardized CNS experiments at scale. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Rebecca Boyles | RENCI | rboyles@renci.org | Chapel Hill, NC | Our team’s work includes the creation and integration of structured biomedical knowledge culminating in DisMech - a broad collection of causal “pathographs”. Furthermore, we have developed OpenScientist, an agentic AI co-scientist capable of semi-autonomously investigating complex queries to generate verifiable insights. UNC provides validated laboratory capabilities featuring integrated molecular profiling and genomics sequencing, high-throughput screening, and airway-on-a-chip models. | We seek partners with expertise in broad-based numerical disease models or laboratory informatics (TA3), as well as laboratory partners capable of providing well-scoped methods with predictable costs. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Abigail Cember | Rhino Federated Computing | abby@rhinohealth.com | Boston, MA | We are a computing infrastructure and ML-ops enterprise focused on federated learning and adjacent privacy-preserving computing approaches at the meta-enterprise scale. Our R&D efforts currently center on agentic AI, federated RAG, federated (bio)chemical property prediction, enabling development of multi-modal foundation models for disease states, and interoperability and harmonization of complex (multi-modal, multi-source, multi-owner) data collections. | We bring expertise in AI and ML orchestration, distributed systems architecture and data engineering, and seek to partner with subject matter experts on the remaining components enumerated on the program page: disease biology, computational biology and mechanistic modeling, wet-lab experimentation, laboratory automation and robotics, experimental protocol standardization. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Aaron Adler | RTX BBN Technologies | aadler@bbn.com | Cambridge, MA | RTX BBN Technologies (BBN) has expertise in semantic web and orchestration technologies, experiment rational capture, control through open standards, and various AI techniques and approaches. BBN has a long history of producing breakthroughs on *ARPA programs and plans to leverage our prior work on DARPA SD2 and prior experience developing architectures and infrastructure for large collaborative efforts (e.g., NSF GENI). | We plan to lead a team and are looking for disease models and subject matter expertise. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine, TA4: Experiment Marketplace |
| Adam Gormley | Rutgers University | adam.j.gormley@gmail.com | Piscataway, NJ | Self-driving labs and agentic workflows for biomaterials, nanomedicine, and drug & gene delivery. We are also developing cloud infrastructure in AWS that connects cloud labs and AI agents to automate science. | Joining a strong team who needs help with lab automation, SDLs, and AI agents for biomaterials, drug & gene delivery, and nanomedicine | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Susheel Varma | Sage Bionetworks | susheel.varma@sagebase.org | Seattle, WA | Sage Bionetworks is a non-profit research organization with a mission to enable and accelerate biomedical research through data sharing, collaboration, model evaluation and ethical data governance. Notably, our data sharing platform hosts PBs of data, largely focusing on -omics data. We host a number of NIH data sharing portals, numerous model benchmarking efforts and are awardees under the ARPA-H BDF program to develop data curation tools. | While we have extensive experience with omics data, we are looking for partners with strong experience in the processing and harmonisation of clinical data. We would also be interested in partners with subject matter expertise and experience with FDA filing, and potentially partners with analytical tools to augment our own | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Travis Vigue | San Juan Framing and Finishing LLC. | travisrvigue@gmail.com | P, CO | San Juan Framing and Finishing LLC is a research entity focused on decentralized high throughput computational frameworks for bioinformatics, synthetic biology, and resilient edge infrastructure. Our core program, Anchor, provides a containerized, secure, air gapped bioinformatics pipeline specializing in six frame ORF translation, pegRNA thermodynamic validation, and structural variant detection. We build modular, hardware independent tools to scale synthetic biology and rapid diagnostics | seek possessing high throughput wet lab validation capabilities to complement our in silico computational engine. Ideal collaborators include organizations with expertise in CRISPR based prime editing, synthetic DNA synthesis, or clinical genomic diagnostic workflows. We require partners capable of generating large scale synthetic datasets for model benchmarking and real world verification of our pipeline outputs. We value partners committed to secure, reproducible research practices | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Gully Burns | SciKnowIO Consulting | gullyburns@gmail.com | San Carlos, CA | Agentic scientific knowledge engineering tools | Experimental scientists and data generation | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Selva Kumar | Selva LLC | selva.kumar@selvallc.com | Alpharetta, GA | Selva LLC has been focusing mainly on digital-twin for any process. | Those who can provide medical data on disease. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Jeremy Elser | Ship of Theseus LLC | jeremy@ship-of-theseus.com | Philadelphia, PA | Ship of Theseus has developed a bench science orchestration software layer [TA2] built on Palantir Foundry, which is deployed among our internal CRO partners. The software focuses on meta-data extraction and data capture quality control to maximize retained value of scientific experimental data. AI operates on this robust model to manage and command science strategy by designing experiments, analyzing results, and drafting management reports and regulatory briefings. | Disease model experts (TA1), high throughput experiments (TA3) and distributed marketplace of validated laboratories (TA4) | TA2: New Science Engine, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures, TA1: Comprehensive Disease Models |
| AVIDEH ZAKHOR | Signetron Inc. | avideh.zakhor@signetron.com | Berkeley, CA | Signetron has extensive experience in developing intelligent, autonomous agentic AI systems. | Seeking to team up with entities which experience in disease modeling and distributed laboratory network. | TA2: New Science Engine |
| Matthew Kuhn | Skybound Medtech | matt@skyboundmedtech.com | Houston, TX | Skybound Medtech (Houston, TX) is a dual-use medtech venture studio developing hardware platforms bridging space medicine and terrestrial care: volumetric 3D bioprinting, portable emergency cardiopulmonary life support, ingestible biosensing & drug delivery systems, neuroendocrine modulation implants, and vestibular modulation. Expertise in multi-system accelerated-aging physiology and device autonomy in austere environments. | Skybound seeks teaming partners targeting accelerated-aging diseases (sarcopenia, neuro-ocular degeneration, vestibular decline, immune dysregulation) who can leverage Skybound's multi-system physiology expertise for disease selection and TA1 grounding. | TA4: Experiment Marketplace |
| Peter Lund | Somos | peter.lund@somosxr.com | Portland, OR | We build trusted tools and environments for certified information exchange. Multi-agentic, self regulating knowledge graphs with requirements, rules, and receipts. | Medical and wet lab partners primarily. | TA2: New Science Engine, TA4: Experiment Marketplace |
| Norma Cantu | Southwest Research Institute | norma.cantu@swri.org | San Antonio, TX | Our goal is to integrate experimental and computational approaches to generate decision ready data that de risk development and accelerate promising therapies toward the clinic. We develop laboratory workflows and experimental plans that are easy to share and reproduce. We also conduct and analyze in vitro assays, delivering clean, well structured digital datasets that can be readily used by advanced computer models and AI tools to improve understanding of treatment mechanisms. | We seek partners with strong capabilities in disease modeling (TA1) and AI driven experiment design (TA2). Ideal teammates will co develop shared protocols and metadata schemas, support automated, closed loop experimentation, and actively participate in cross team interoperability efforts, enabling seamless integration between computational models, AI orchestration engines, and our experimental platforms. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Jules Bergmann | SRI International | jules.bergmann@sri.com | Arlington, VA | SRI brings neuro-symbolic AI, time-series causal analytics, ontology-driven biological knowledge representation, symbolic reasoning, and causal inference optimized for multi-scale, dynamic experimentation. Core capabilities include explainable AI reasoning, custom and adaptable protocols, basic and translational R&D, hypothesis generation and ranking, in silico experimentation, provenance-aware automation, and executable models of cell signaling and disease mechanisms. | SRI seeks primes with in-silico disease modeling platforms, high-throughput or automated laboratory networks to provide the necessary ground truth experimental protocols. SRI values teams committed to interoperability who possess the agility and ARPA experience required to successfully execute high-impact breakthrough research. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Simon RASALINGHAM | SRI Ventures Limited | simon@rasalingham.com | London | SRI Ventures builds epistemic-critique infrastructure for agentic AI-Scientist systems: compositional-NLP assumption auditing, knowledge-gap identification, and evaluation rubrics for autonomous-science pipelines. | SRI contributes as TA2 sub-performer with TA1+TA3 support. Seeking a US-led prime operating a closed-loop or autonomous-science platform: agentic AI-Scientist orchestration, with ARPA-H or DARPA-adjacent execution history. Ideal partners lack an in-house epistemic-critique layer and would integrate our assumption-audit APIs above their generator. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Tariq Khokhar | System Inc | tariq@system.com | New York, NY | We develop the System Graph: a computable knowledge graph encoding mechanistic and statistical findings extracted at scale from the literature and expert-curated databases (e.g. GWAS Catalog, BioGrid, CTD), grounded to standard ontologies (e.g. UMLS, SNOMED, ICD-10). Research focus areas: multi-scale mechanistic disease representation, algorithmic knowledge-gap detection, and evidence-grounded AI reasoning that anchors model outputs to verified findings to reduce hallucination. | System intends to contribute TA1 and TA2 We are seeking a prime, plus partners covering TA3 and TA4 We prefer a sub-performer role on a team building closed-loop, cross-lab experimental capability. Ideal partners share a complex-disease focus tractable by mechanistic modelling and an interest in contributions back to open science commons. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Gita Parekh | Tachmed | gita.parekh@tachmed.com | London UK, Phoenix Arizona, AZ | Tachmed is developing AI-enabled electrochemical biosensor platforms for decentralized healthcare and rapid translational research. Current focus areas include interoperable assay development, standardized electrochemical workflows, remote patient monitoring, connected diagnostic infrastructure, AI-assisted assay optimisation and scalable multi-analyte sensing using blood, saliva, urine, and other biofluids across chronic disease and infectious disease applications. | Tachmed is seeking partners with expertise in mechanistic disease modelling, computational biology, AI orchestration systems, laboratory automation, organoid, cell culture models, protocol standardization and distributed experimental infrastructure. We are particularly interested in collaborators capable of supporting interoperable protocol execution, automated experimental workflows, AI-driven hypothesis generation, and large-scale reproducible data generation across multiple laboratory sites. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Johnny Yu | Tahoe Therapeutics | johnny@tahoebio.ai | South San Francisco, CA | Tahoe Therapeutics builds foundation models and agentic AI workflows on frontier-scale biological datasets, including the Tahoe-100M single-cell perturbation atlas. We combine deep learning with high-throughput experimental biology to advance perturbation prediction, mechanism-of-action discovery, and closed-loop AI–lab research. | Tahoe seeks DOE-NIH national lab teaming partners with complementary biological datasets—multi-omics, imaging, structural, or clinical—and HPC-AI compute. We aim to bridge unique cross-modality data into unified foundation models for agentic biological superintelligence workflows. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| H. Tsvi Goldenberg | Talzera | tsvi.talzera@gmail.com | San Diego, CA | Talzera has developed a deterministic defense for autonomous AI, including the high-reasoning Mythos agents. Our VACE kernel is an out-of-band circuit breaker for bio-automation networks like IGoR. It instantly neutralizes agentic intent drift, de novo biological mimicry, and distributed mutation attacks pre-execution. We secure the AI last mile, mathematically enforcing human T0 authorization against rogue actions. | Talzera seeks strategic partners integrated with ARPA-H programs to scale our deterministic defense infrastructure. We require access to bleeding-edge, high-reasoning autonomous agents to continuously stress-test VACE against novel rogue AI behaviors and mutation attacks. Finally, we seek funding partners and consortiums to accelerate deployment of our circuit breaker across distributed bio-automation networks, securing the AI last mile for national defense. | TA3: Interoperable Experimental Procedures, TA2: New Science Engine |
| Justin Zimmerman | Tempus AI, Inc. | justin.zimmerman@tempus.com | New York, NY | Tempus AI stands at the intersection of AI, clinical genomics, and multi-omics. Our research focus centers on high-throughput, automated biological testing in our US-based CAP and CLIA labs, specializing in Whole Exome Sequencing (xE), Whole Transcriptome Sequencing (xR), and advanced DNA methylation profiling. We leverage an integrated library of 8M+ clinical-genomic records to accelerate biomarker discovery, characterize complex disease mechanisms, and build precision medicine solutions. | We seek prime contractors or consortia targeting complex human diseases to anchor their TA4 Experiment Marketplace. Tempus provides unmatched clinical-grade infrastructure to run standardized, reproducible protocols (WES, WTS, methylation) with market-leading turnaround times. | . |
| Evan Maltz | Tessel Biosciences | evan@tessel.bio | Cambridge, MA | Tessel Bio is a drug discovery company focused on building clinically predictive in vitro and in silico disease models. Our high-throughput organotypic models of lung, gut, kidney, and BBB tissue inform our digital twins and mechanistic models for target discovery and ADME-Tox prediction. These models, combined with an active learning framework, significantly improve the speed and efficiency of our small molecule and CRISPR screens (up to 30x). We are also a current ARPA-H CATALYST performer. | We seek TA3 partners with expertise in layered protocol architecture, automation and robotics, and standardizing protocols. We seek TA4 partners operating cloud or self-driving labs capable of executing these protocols and returning model-ready data. We bring mechanistic digital twins, active learning algorithms, and wet lab capacity across diverse assays and cell types. Experience integrating LLMs into end-to-end workflows is a plus. We are flexible in leading or supporting a consortium. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Lang Li | The Ohio State University | langli09262006@gmail.com | Columbus, OH | Our research focus is cancer metastasis. Our team include cancer physician scientists, biomedical engineers, and AI and data scientists. We are strong on disease modeling dedicated for cancer metastasis, AI tools for cancer metastasis knowledge gap discovery, biotechnology platforms such as organ-on-a-chip, CRISPR and multi-omics, and informatics capacity in data integration, data dissemination, and experiment protocol standardization. | We are seeking collaborators who are strong on quality and reproducibility improvement and automation in biological experiments and marketing. These are largely in TA3 and TA4. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Xia Ning | The Ohio State University | ningx005@gmail.com | Columbus, OH | We focus on AI for drug discovery and development. We have developed generative AI tools for structure-based and ligand-based drug design, generative AI tools and foundation models for lead optimization, generative and agentic tools for constrained retrosynthesis planning, structure-activity relationship models, and overall drug discovery agents. We have moved from AI-designed molecules to in vitro and in vivo evaluation and validation, with several promising ones in the pipeline. | We seek automated experimental platforms that are capable of automating synthetic reactions, necessary in vitro, in vivo experimentation, or virtual cell experimentation, that can evaluate and validate AI-designed drug candidates. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Qin Ma | The Ohio State University | maqin2001@gmail.com | Dublin, OH | Bioinformatics and Computational Biology, single-cell and spatial AI, immuno-informatics | laboratory automation and robotics | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Zihai Li | The Ohio State University Comprehensive Cancer Center | zihai.li.piio@gmail.com | Columbus, OH | The Pelotonia Institute for Immuno-Oncology (PIIO) focuses on bench-to-bedside research that harnesses the immune system to prevent, detect, and treat cancer. Key areas include cancer immunotherapy, cellular therapies, immunogenomics, innate immunity, and translational clinical trials, with strong emphasis on interdisciplinary collaboration, biomarker discovery, and accelerating novel therapies from discovery to patient care. | The organization seeks collaborative partners with complementary expertise in multiomics, immunology, AI, biostatistics, and clinical translation. Ideal partners bring advanced technologies, scalable data generation analysis, and experience in biomarker discovery, modeling, and commercialization. Emphasis is on interdisciplinary collaboration, data sharing, and accelerating translation of discoveries into clinically actionable tools. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Laura Brattain | The University of Central Florida | lauraucf87@gmail.com | Orlando, FL | Biomedical AI and Robotics | Computational biology and mechanistic modeling | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Shalini Prasad | The University of Texas at Dallas | shalini.prasad@utdallas.edu | Richardson, TX | Assay development and establishing repeatable performance across assays designed agentic systems | Specific disease indications that need the biomedical assay development frameworks and AI design partners | TA3: Interoperable Experimental Procedures, TA2: New Science Engine, TA4: Experiment Marketplace, TA1: Comprehensive Disease Models |
| Casandra Philipson | Transfyr | casandra@transfyr.ai | Cambridge, MA | Transfyr is building the physical AI infrastructure for scientific observability to make science understandable, transferable, and reproducible (TA3, TA4). Most AI Scientists are trained on lossy published literature, we use a multimodal sensor stack to capture science in the lab as it happens. Layers of physical intelligence and computer vision power self-evolving models to provide ground truth for a deeper mechanistic understanding and seamless knowledge transfer between humans and machines. | We seek partners developing TA1 (Mechanistic Disease Models) and TA2 (New Science Engine) capabilities, and can support reproducibility testing across multiple sites for TA4 (Experiment Marketplace) partners through our deployable sensors and agentic AI-powered tools that enable automated insights generation in a protocol and technology-agnostic manner, or directly serve as part of the TA4 experimental network through our testbed laboratory in Cambridge, MA. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Joanne Elliott | Triple Ring Technologies | jelliott@tripleringtech.com | Newark, CA | Triple Ring Technologies is a leading partner in developing science-driven products across medtech and life sciences. Our interdisciplinary team, including many PhDs, excels in advancing technologies and collaborating with academic researchers. Our facilities infrastructure and equipment is designed to support numerous projects including imaging, biochemical and functional assay development. We have engaged with ARPA-H, both as sub and multiparty awardees. Fully ISO 13485 certified. | We partner with innovators to solve tough problems and support development of breakthrough products from concept to commercialization. We develop complex integrated HW and SW systems for automated analysis. We seek teaming partners from academia or industry who can provide expertise in their technical areas but need support in generating clear procedures and operational guidelines to test, and integrate specific protocols into a standardized and reproducible system. We can provide QMS support. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Zhen Xiao | Truvante LLC | zhen.xiao@truvante.com | Lorton, VA | Truvante LLC's focus is on digital twin development and application for children's health that benefits from comprehensive lifespan health journey model building. Truvante provides expertise in biomedical research and data science with staff also highly experienced in children's health, oncology, neuroscience, stakeholder engagement, science dissemination, communication, team building. | Truvante LLC is WOSB seeking a prime contractor to enhance the team's solution in TA1 Comprehensive Disease Models, and TA2 New Science Engine. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Lifu Huang | UC Davis | warrior.fu@gmail.com | Davis, CA | The PLUM Lab at UC Davis focuses on AI for scientific discovery, including large language models, multimodal foundation models, agentic AI systems, scientific knowledge extraction, hypothesis generation, experiment planning, and human-AI collaboration. Our research develops trustworthy AI methods for integrating literature, biomedical knowledge, and experimental evidence to accelerate discovery, reasoning, and decision-making in complex scientific domains. | We are seeking collaborators with complementary expertise in systems biology, disease modeling, biomedical experimentation, laboratory automation, self-driving and cloud laboratories, protocol standardization, and translational medicine. We are particularly interested in partners who can support closed-loop hypothesis validation, experimental execution, and integration of AI-driven scientific reasoning with real-world biological discovery workflows. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Julia Schaletzky | UCB | jschaletzky@berkeley.edu | Berkeley, CA | Target ID, Drug Discovery, High throughput screening, chemical optimization, Preclinical Drug development | Collaborations where our Drug Discovery resources could be helpful | TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Kitai Kim | UCLA | kitaikim68@gmail.com | Los Angeles, CA | The UCLA Human Stem Cell and Genome Engineering Center develops AI-guided and automation-enabled platforms for stem cell engineering, genome editing, tissue modeling, and disease discovery. UCLA serves as a fully automated development hub for AI-driven protocol generation, iPSC reprogramming, colony selection, genome editing, tissue differentiation, bioprinting, and imaging. Distributed validation is performed through partner institutions using semi-automated execution workflows. | We seek collaborators with expertise in disease modeling, AI and computational biology, tissue engineering, imaging, bioprinting, and interoperable laboratory technologies. Our proposed IGoR framework develops AI-guided workflows at UCLA and validates protocol portability through semi-automated execution at partner institutions, including UAB and USC. We welcome partners interested in distributed reproducible experimentation and mechanistic disease discovery. | TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Peter Koulen | UMKC | koulenp@umkc.edu | Kansas City, MO | Neuroscience and translational research | collaborations | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| John Sondek | UNC Chapel Hill | john.sondek@gmail.com | Chapel Hill, NC | Alzheimer's disease, neuroinflammation | zebrafish model | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| Konstantin Popov | UNC Chapel Hill | kpopov@unc.edu | Chapel Hill, NC | AI, structural bioinformatics, drug discovery, lab automations. Neurodegenerative disorders, cancer, inflammation and immune diseases. | Self driving labs, robotics, big data processing and analysis | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Adam Bradley | Uncharted Software | abradley@uncharted.software | Toronto, Ontario, Canada | Uncharted Software has 25 years delivering advanced R&D platforms for DARPA, IARPA, and allied defense agencies. Our 70-person team spans software engineering, ML-AI research, data science, and UX design. We specialize in AI orchestration, knowledge graphs, human-AI collaboration, and explainable reasoning. Recent programs: ASKEM, CriticalMAAS, INCAS, RSDN. | Seeking a prime or consortium partners with biomedical domain expertise, mechanistic disease modeling, and validated wet-lab infrastructure. We would contribute to TA2 (AI orchestration, hypothesis generation, experiment design, explainability, human-AI interface) and cross-TA integration architecture. Ideal partners: academic medical centers, cloud labs, and computational biology groups. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Jonathan (Jack) Reid | Unicorn Biotechnologies | jack.reid@unicornb.io | Newark, NJ | Unicorn Biotechnologies builds self-driving labs. We integrate engineered cell lines, autonomous instruments, orchestration software, and AI scientist tooling into closed-loop systems that decouple human labor from experimental biology. Our platform runs cell and molecular biology workflows end to end, generating reproducible, provenance-rich, AI-ready data across distributed US and UK sites, and closing the loop from hypothesis to experiment to model. | We bring autonomous laboratory execution (TA4), a layered protocol architecture (TA3), and AI orchestration (TA2). We seek partners with mechanistic, multiscale human in vitro disease models (TA1), and AI-for-science groups building hypothesis-generation and reasoning systems (TA2). | TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| John Tainer | Univ of Texas MD Anderson Cancer Center | jatainer@gmail.com | Houston, TX | We apply experimental biophysics to predict and control causative disease models. Through closed-loop automated wet-labs, we develop, test, and validate NEXUS architecture as a multiscale causal hypergraph mapping intracellular molecular stress (GRB2, EEPD1) to aberrant cell-cell signaling (cGAS-STING) and tissue outcomes. This foundation in active experimental validation and AI inference reveals novel therapeutic targets for oncology, viral infections, and tissue fibrosis. | To fully realize our multiscale causal disease model, we seek partners with complementary expertise in: 1) Automated wet-lab infrastructure and high-throughput multi-modal readouts (spatial transcriptomics, live-cell imaging), 2) Advanced machine learning for causal inference and graph neural networks, and 3) Physiologically relevant disease models (3D co-cultures, organoids) focused on oncology, viral pathogenesis, and autoimmunity for robust experimental validation. | TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| Stephanie Fraley | University of California San Diego | sifraley@ucsd.edu | San Diego, CA | We focus on building the Integrome Digital Twin, a mechanistic TA1 model of outside-in signaling by the extracellular matrix in human tissues. We map this signaling using cutting-edge proximity proteomics to develop ECM signaling logic models and validate these models with designer hydrogels and adult human stem cells. Our approach transforms clinical archival tissue into functional maps of receptor logic underlying diseases for predictive drug discovery. | We are seeking teaming partners to support integration of an Active Learning loop utilizing AlphaFold 3 and Gemini-based reasoning as an orchestration layer to identify knowledge gaps in the Integrome Digital Twin. This will form the basis of TA2. We are also seeking collaborators for TA3 (ensuring reproducibility across sites) and TA4 (distributed network of validated laboratories) activities. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Alvaro Velasquez | University of Colorado Boulder | alvarovelasquezucf@gmail.com | Boulder, CO | Our research focus is on the discovery of novel scientific theories by introducing logical self-argumentation whereby AI can discover and invalidate competing hypotheses efficiently | We seek partners in TA1 for modeling diseases using AI. We have AI expertise on learning representations of phenomena from multi-modal data, but we are missing the medical expertise. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Farnoush Banaei-Kashani | University of Colorado Denver | farnoush.banaei@gmail.com | Denver, CO | Scientific Discovery and Creative Reasoning with AI Agents | Complementary expertise | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA4: Experiment Marketplace |
| Shuxing Zhang | University of Hawaii Cancer Center | shuxing@hawaii.edu | Honolulu, HI | We develop real world big data and AI-based computational methods and frameworks to model complex biological systems and human diseases at multi-scale level, including molecular structures, cellular responses, imaging, multi-omics, and clinical trials and patient medical and health records. We have intensive experience in AI-guided therapeutics discovery and development, biomarker discoveries, and population-aware clinical trials, especially with access to multiethnic patient cohorts. | We are seeking expertise with matured technologies of microphysiological systems (MPS) to simulate real human whole body physiology and pathophysiology, established systems to integrate interoperable technologies, AI-integrated quantum computing, and deployable marketplace. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Jeffrey Thompson | University of Kansas Medical Center | jeffrey.a.t@outlook.com | Kansas City, KS | Multimodal AI and mechanistic modeling for fibrotic lung disease, with idiopathic pulmonary fibrosis as the index condition for development. Core methods: knowledge discovery, causal inference, federated learning, and hybrid cloud enabling large-scale model training on regulated data. Agile cybersecurity architecture is overseen by an internationally recognized team. Incorporating longitudinal pulmonary function, imaging, molecular, and public data with methods architected for extensibility. | Seeking partners with experimental and infrastructure capabilities complementary to our mechanistic modeling and causal AI core. This includes partners with experience in protocol standardization and cross-facility portability and partners operating qualified or automated wet laboratories to harmonize with KU's available lab infrastructure. Enthusiastic about building a national network of collaborators jointly studying conditions where causal mechanistic modeling adds interpretive value. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Elana Fertig | University of Maryland | elana.fertig@gmail.com | Baltimore, MD | computational biology and bioinformatics, immunogenomics modeling | TA1 collaborators. | TA2: New Science Engine |
| Wei Li | University of Maryland Baltimore | wli2@som.umaryland.edu | Baltimore, MD | The Wei Li lab focuses on understanding how coding and non-coding elements in the genome function in human physiology and disease, and further identifying novel molecular targets to inform precision medicine. We are particularly interested in applying new genomics (Perturb-seq), gene editing (CRISPR-Cas9, Cas13, base editor), and AI methods to address challenges in biomedical and biological big data problems. | Academic and industrial partners that complement with our expertise. | TA2: New Science Engine |
| Geoffrey Siwo | University of Michigan | siwog@umich.edu | Ann Arbor, MI | We are developing automated approaches for the discovery of short unconventional regions in the human genome that could be targeted for fine-tuned modulation of gene expression using short, easy to deliver oligonucleotides to enhance or suppress expression of pre-specified targets beyond the capabilities of approaches such as siRNA or CRISPRa or CRISPRi or epigenome editing.  | We are seeking partners with mechanistic disease models interested in modulating the expression levels of specific genes, especially where upregulation rather than knockdowns are desired. We are also seeking partners with wet lab capacity to perform AI-generated experimental protocols at scale across multiple genes and different doses of perturbations.  | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Ravi Allada | University of Michigan | rallada@umich.edu | Ann Arbor, MI | Sleep, circadian rhythms, Drosophila genetics | TA2 and TA3 | TA4: Experiment Marketplace, TA1: Comprehensive Disease Models |
| Arvind Rao | University of Michigan Ann Arbor | ukarvind@umich.edu | Ann Arbor, MI | Multimodal disease-state modeling using spatial transcriptomics, H&E pathology embeddings, multiplex immunoprofiling, single-cell & multi-omics data, and mechanistic AI. We focus on therapy resistance, lineage plasticity, tumor–immune & stroma spatial reprogramming, biomarker discovery, and classical as well as quantum-classical hybrid operator-learning methods for uncertainty-guided experiment prioritization. | We seek IGoR prime or consortium partners with strengths in AI orchestration, agentic science workflows, cloud- or distributed lab execution, protocol standardization, perturbation biology, spatial omics & proteomics, disease biology, biomedical knowledge graphs, data infrastructure, and ARPA-H or DARPA prime experience. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| Katalin Susztak | University of Pennsylvania | katalinsusztak@gmail.com | Philadelphia, PA | Kidney precision medicine and AI, coled with Jure Leskovec (Stanford), and a cloud compute partner. We build mechanistic, multiscale models of chronic kidney disease on one of the largest proprietary kidney multiomics datasets (genetics, single cell and spatial, proteomics, methylation, longitudinal clinical data) plus kidney foundation models. Strengths: causal target discovery, eQTL and caQTL colocalization, graphML orchestration. | Seeking TA3 and TA4 partners to complete a kidney-focused team. TA3: layered protocol architecture, lab-automation standards, and software that makes assays machine executable and reproducible across sites. TA4: automation grade and cloud labs or CROs with demonstrated cross-site concordance ( single cell, spatial, proteomic, or organoid capacity adaptable to kidney preferred. Also open to cloud andcompute and data-governance enablers. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Ben Orsburn | University of Pittsburgh | orsburn@pitt.edu | Pittsburgh, PA | We perform routine high throughput single cell proteomics and associated multi-omics. This system is broadly applicable and validated on a large number of human cell types. | Our group functions as a collaborative cog in research machines that need the highest quality protein and proteomic data. | TA3: Interoperable Experimental Procedures, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace, TA2: New Science Engine |
| Mark Miedel | University of Pittsburgh | mmiedel@pitt.edu | Pittsburgh, PA | We use human liver MPS for ADME Tox and MASLD disease progression and therapeutic response modeling. Our work integrates imaging, multiomics, functional assays, QSP, and AI ML-enabled systems biology (PMIDs 26962875, 31201557, 35736460, 40614771). We develop standardized, reproducible MPS workflows, including the Pittsburgh Reproducibility Protocol (PMID 40233763), and participate in the NCATS TraCe program. | We are interested in teaming with collaborators that bring expertise in AI utilization, MPS automation based on standard protocols, automated experimental workflow systems, cross-site experimental execution and validation networks, and scientific software engineering for scalable biological research infrastructure. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA2: New Science Engine, TA4: Experiment Marketplace |
| Mitchel Colebank | University of South Carolina | MJCOLEBANK@sc.edu | Columbia, SC | The development and deployment of mechanistic, multiscale computational models of the cardiovascular system in combination with robust uncertainty quantification for data assimilation and digital twins. | Seeking experimental collaborators and those with expertise in sensor design or those in need of someone with a background in mechanistic, multiscale modeling and data assimilation | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Ari Kahn | University of Texas - Texas Advanced Computing Center (TACC) | akahn@tacc.utexas.edu | Austin, TX | TACC operates a national-scale AI and HPC infrastructure for biomedical research, including federated data systems, workflow orchestration (Tapis), and multi-modal modeling. With UT Dell Medical School, we develop closed-loop AI research architectures spanning mechanistic disease modeling, automated hypothesis generation with citation-grounded verification, interoperable protocol design, and distributed laboratory validation for rare monogenic disease. | Seeking quantitative mechanistic disease modeling groups (multi-scale, systems biology, or physics-based variant-to-phenotype modeling) to deepen TA1, and additional automated or robotic wet-lab facilities for distributed experimental validation under TA4. Interested in partners with rare disease, genomics, or autonomous experimentation capabilities who can interoperate with standardized protocol and data-exchange frameworks. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Martin Tristani | University of Utah | marti.tristani@gmail.com | Salt Lake City, UT | University of Utah (prime) is building a closed-loop, AI-guided discovery ecosystem to answer why some hearts recover while others fail, in the context of heart failure and cardiometabolic disease. We span TA1-TA4. Strengths: longitudinal EHR (1.6M patients), human myocardial recovery multi-omics (LVAD biobank), cardiac regeneration biology (zebrafish), iPSC-cardiomyocyte and organoid platforms, explainable AI, mechanistic disease modeling, and Utah's Sovereign AI Factory (NVIDIA + HPE). | We welcome partners as TA leads (notably TA2 AI orchestration) or sub-performers, with expertise in: AI guided scientific reasoning and discovery orchestration, cloud labs and CROs, scalable lab execution, IV&V, protocol interoperability and standards, advanced iPSC cardiomyocyte and organoid systems. | TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Josh Bongard | University of Vermont | josh.bongard@gmail.com | Burlington, VT | We build closed-loop robot scientists for autonomous biological discovery, focused on motile organoids—self-assembling, ciliated constructs that swim, sense, and respond to stimuli. Our active-learning AI discovers interventions (chemical, electrical, thermal, vibroacoustic) that push these living systems toward desired behaviors, executed autonomously on an integrated multimodal platform. We also build AI that generates models directly from data, guiding the first AI to better interventions. | We seek team leads building IGoR systems that would benefit from our distinctive capabilities: motile organoids as a tractable model for closed loop biological discovery, end to end AI designed biology ---from data driven model generation to autonomous intervention discovery--- and bioelectric stimulation as a programmable modality for steering living systems. We contribute as a focused TA1 or TA2 component, not as lead. Strong fit for teams treating these as core capabilities, not add ons. | TA2: New Science Engine |
| Gary An | University of Vermont Department of Surgery | docgca@gmail.com | Burlington, VT | Our group has over 25 yrs experience using agent-based models for dynamic knowledge representation: the instantiation of cellular-molecular mechanisms in modular multiscale simulation models (not AI) that allow represented hypotheses to be evaluated, interrogated, verified or expanded upon. Their multiscale structure integrates in vitro (TA3-TA4) validated modules into comprehensive disease models that can serve as NASEM-compliant cellular-molecular-based (eg not physics-based) digital twins. | Not looking to lead a team but can bring TA1 (dynamic knowledge representation) and TA2 (ML-augmented simulation exploration workflows) along with extensive clinical expertise in casting modeling-experimental capabilities into specific disease processes to a TA3-TA4 group with experience in developing research infrastructure. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Stephen Turner | University of Virginia School of Data Science | turner@virginia.edu | Charlottesville, VA | UVA's School of Data Science and Biocomplexity Institute together work on mechanistic, multiscale disease modeling and AI orchestration for scientific reasoning. Capabilities including, COPASI and SBML for biochemical simulation, Neurosymbolic and mechanistic disease models, differentiable digital twins and their agentic orchestration, graph grammars, formal methods for validation and verification. Strongest fit TA1, with substantive contribution to TA2. | Seeking TA3 and TA4 partners, plus a prime willing to integrate the full closed loop. TA3: groups experienced with layered protocol architectures, declarative experiment specification, calibration standards, and laboratory automation interfaces, comfortable with open standards and RFC processes. TA4: cloud labs, autonomous self-driving labs, CROs, and core facilities able to execute standardized cell and tissue-culture experiments reproducibly across multiple modalities. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Wenqi Shi | UT Southwestern Medical Center | wenqi.shi@utsouthwestern.edu | Dallas, TX | Our group develops agentic LLM systems for biomedical research, with focus on coding-centric AI co-scientist that autonomously design, conduct, validate computational experiments. Core areas include retrieval-augmented generation for evidence synthesis, multi-agent reasoning over heterogeneous biomedical data, reproducible computational protocols, and fairness-aware clinical AI. We bridge machine learning and experimental science to accelerate validated discovery in complex diseases. | We seek partners with complementary strengths across IGoR's technical areas, particularly mechanistic disease modelers encoding causal multiscale biology, and wet-lab groups able to execute standardized, replicable protocols and return high-quality experimental data. We also welcome laboratory-automation and informatics partners to operationalize a distributed lab marketplace. Our contribution centers on the AI orchestration layer linking models, gaps, and experiment design. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| David Voros | Verily Health, Inc | dpvoros@verily.health | Coppell, TX | Verily Health integrates technology and life sciences to accelerate evidence generation. Our research focuses on AI ML-driven biological discovery, multi-omic data orchestration, and precision health. We specialize in building modular, model-agnostic software architectures that anchor generative AI to mechanistic reality. Our work emphasizes human-centered design and Team Science architectures to ensure AI-augmented workflows enhance, rather than replace, scientific agency. | We seek partners specializing in TA1 (mechanistic modeling knowledge graphs) and TA3 TA4 (lab automation decentralized execution). Ideal collaborators provide deep domain expertise in specific disease areas or novel reasoning architectures, such as multi-agent dissent and verification systems. We aim to partner with academic or industry teams capable of translating high-level scientific hypotheses into granular, executable protocols across heterogeneous, distributed laboratory environments. | TA2: New Science Engine |
| Roshan Bhave | VeriSIM Life | roshan.bhave@verisimlife.com | San Francisco, CA | VeriSIM Life brings deep expertise in hybrid mechanistic AI platforms for disease biology and drug development with a track record of FDA-collaborative translational science. Our platform integrates causal, multiscale biological models (molecular to organ) with ML-driven knowledge gap detection, directly mapping to TA1 disease model and TA2 orchestration requirements. Seeking experimental partners for TA3 protocol architecture and TA4 laboratory execution. | We seek at least two validated laboratory partners to lead TA3 protocol architecture and TA4 marketplace execution as part of an IGoR prime performer team. Ideal collaborators bring multi-modal wet lab capability across imaging, omics, and functional assays, and experience with standardized or automated protocol execution. Cloud labs, CROs, organ-on-chip platforms, and academic core facilities are encouraged to reach out. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Rebecca Heise | Virginia Commonwealth University | rlheise@vcu.edu | Richmond, VA | We have rodent and cell models of acute lung injury, ventilator associated lung injury, and acute respiratory distress syndrome. We also have in vitro cell-hydrogel based models of lung diseases such as chronic obstructive pulmonary disease, pulmonary fibrosis, and asthma. | We are interested in being a Sub in TA4 if there is a group planning on focus for lung injury, COPD, pulmonary fibrosis, or asthma. | TA4: Experiment Marketplace |
| Xuan Wang | Virginia Tech | xuanw@vt.edu | Blacksburg, VA | Our lab at Virginia Tech develops scalable and reliable multi-agent foundation model systems for decision-making in complex multimodal real-world environments, motivated by high-stakes domains such as science and healthcare. Current work spans language-model agentic frameworks, foundation model architecture search, multi-agent coordination, tool-augmented reasoning in VLM agents, and biomedical informatics AI. | Seeking collaborators in biomedical research, translational medicine, computational biology, laboratory automation, robotics, experimental protocol standardization, and distributed experimental infrastructure. We are particularly interested in partners developing mechanistic disease models, high-throughput experimental platforms, reproducible wet-lab workflows, and interoperable AI-enabled scientific discovery systems aligned with the ARPA-H IGoR vision. | TA1: Comprehensive Disease Models, TA2: New Science Engine, TA3: Interoperable Experimental Procedures, TA4: Experiment Marketplace |
| Nathaniel Ambler | VT-ARC | nambler@vt.edu | Arlington, VA | VT-ARC’s Decision Science Division advances human and machine decision-making through applied decision and information sciences, AI-ML, data science, human-centered design, systems-mission engineering, experimental design, metrics, probabilistic modeling, NLP, data fusion, visualization, and decision-support tools. | VT-ARC seeks prime or co-performer teams with strong disease biology, computational biology, mechanistic modeling, wet-lab validation, lab automation-robotics, and standardized protocol execution. We are best positioned as a TA2-TA3 support partner providing AI-ML analytics, experiment design, interoperability requirements, systems engineering, HCD, evaluation, and decision-support integration. | TA2: New Science Engine, TA3: Interoperable Experimental Procedures |
| Randall Bateman | Washington University | batemanr@wustl.edu | St. Louis, MO | Consortium for Biomedical Research & AI in Neurodegeneration: C-BRAIN (c-brain.org) Mission: To design and implement AI as a collaborative partner for scientists, accelerating discovery in neurodegeneration research to improve human health. C-BRAIN launching the AI Biomedical Research Scientist Initiative with three factors driving this revolution: 1) Advanced AI Technologies, 2) Unprecedented volumes of actionable biomedical data, 3) World-class scientific expertise to train AI systems. | TA3 and TA4 leadership and capabilities. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Nir Ben-Chetrit | Weill Cornell Medicine | nib2033@med.cornell.edu | New York, NY | We model, perturb, and reprogram tumor microenvironments to identify interventions that convert dysfunctional immunity into durable tumor control. We specialize in tumor immunization for in situ vaccines, radiation-based immune remodeling, spatial and multimodal profiling, and ex vivo TME platforms that preserve tumor-immune-stromal interactions in human cancers with high phenotypic fidelity. These TME platforms enable scalable drug perturbation, genetic screening, and model-ready validation. | We seek partners who can build AI systems that identify knowledge gaps, model disease mechanisms, predict perturbation responses, and prioritize experiments. We bring high-fidelity ex vivo TME platforms for drug and genetic perturbation, functional validation, and model-ready data generation. Ideal partners add multimodal data integration, experimental orchestration, protocol generation, and marketplace infrastructure to close the loop from model to experiment. | TA1: Comprehensive Disease Models, TA4: Experiment Marketplace, TA3: Interoperable Experimental Procedures |
| Maria Rodriguez Martinez | Yale University | maria.rodriguezmartinez@yale.edu | New Haven, CT | We develop interpretable AI and mechanistic models for immune-mediated disease, cancer, and protein-driven pathology. We integrate multi-omics, single-cell and spatial data, immune receptor repertoires, and protein modeling to build causal disease models, identify knowledge gaps, and prioritize experimentally testable hypotheses. | We seek TA3 and TA4 partners with expertise in protocol standardization, laboratory automation, perturbational assays, organoid and cell-based models, clinical cohorts, CRO and core-facility execution, and distributed wet-lab validation. Ideal partners can translate AI-generated hypotheses into reproducible protocols and return high-quality experimental data for iterative model refinement. | TA1: Comprehensive Disease Models, TA2: New Science Engine |
| Maja Losic | Tahoe Therapeutics | maja@tahoebio.ai | South San Francisco, CA | Tahoe Therapeutics develops foundation models and agentic AI workflows on frontier-scale biological datasets. Our Tahoe-100M single-cell perturbation atlas, the largest of its kind, pairs deep learning with high-throughput experimental biology to build toward biological superintelligence: AI systems that can reason over cellular states, mechanism of action, and intervention. Focus areas include multi-omics foundation models, perturbation prediction, and closed-loop agentic AI–lab discovery. | Tahoe seeks teaming partners with complementary biological data and compute, particularly DOE and NIH national labs holding large-scale multi-omics, imaging, structural, or clinical datasets suitable for cross-modality bridging into unified foundation models. We are interested in partners contributing unique data sources for agentic biological superintelligence workflows, and institutions with HPC and AI compute for frontier-scale training and orchestration. | TA2: New Science Engine, TA1: Comprehensive Disease Models |