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.
| 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 |
| 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 |
| 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 |
| 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 |
| Jessica 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 |
| 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 |
| Steve Levine | Dassault Systemes | steven.levine@3ds.com | San Diego, CA | We are leaders in AI-powered multiscale Digital twins of human organs and using them for Physics Informed AI Reduced Order Models (also known as PINNs) | We look for Clinical centers eager to modernize patient centric care and the clinical trial process | TA2: New Science Engine, 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 | Perturb Bio builds an AI-orchestrated closed-loop research engine for drug safety pharmacology. The cardiac safety vertical integrates active-learning experimental design with automated cloud-lab execution in human iPSC-derived cardiomyocytes, generating mechanistic cardiotoxicity profiles across transcriptomic and morphological modalities. | (1) Validated automated-biology execution labs to demonstrate protocol portability beyond our current CRO partner. (2) Academic or CRO disease-model experts for Phase 2 generalization to a second indication (nephrotoxicity or hepatotoxicity). (3) Pharma safety-science teams interested in serving as blinded calibration-engagement validators. | TA2: New Science Engine, TA1: Comprehensive Disease Models |
| 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 |
| 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 |
| 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 |
| 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 |
| Simon RASALINGHAM | SRI Ventures Limited | simon@rasalingham.com | London | SRI Ventures Limited develops epistemic-critique infrastructure for AI-driven research systems. Current focus: compositional NLP-based assumption auditing of mechanistic models structured knowledge-gap identification, and evaluation rubrics for agentic AI-Scientist pipelines. Published methods include CrossTrace and ClaimCheck benchmarks (Lo et al. 2025 Bouras 2026. Wazni et al. 2024) with quantified gains on GPT-4o and Claude Opus 4.5. | Seeking a US-led prime with strong TA1 TA3 TA4 capability building agentic AI-Scientist or AI orchestration systems for IGoR TA2. Ideal partners lack an in-house epistemic-critique layer and require assumption-audit APIs knowledge-gap identification and shared QA infrastructure. Academic-industry consortia with established ARPA-H relationships preferred. SRI contributes as sub-performer on TA2 with TA1 support. | TA2: New Science Engine, TA1: Comprehensive Disease Models, TA3: Interoperable Experimental Procedures |
| 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 |
| 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 |
| 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 |
| 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 |
| Elana Fertig | University of Maryland | elana.fertig@gmail.com | Baltimore, MD | computational biology and bioinformatics, immunogenomics modeling | TA1 collaborators. | 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 |
| 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 |
| 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 |
| 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 |