CATALYST Teaming Profiles
Thank you for showing an interest in ARPA-H’s Computational ADME-Tox and Physiology Analysis for Safer Therapeutics (CATALYST) program. This page is designed to help facilitate connections between prospective proposers. If either you or your organization are interested in teaming, please submit your information via the portal linked below. Your details will then be added to the list below, which is publicly available.
CATALYST anticipates that teaming will be necessary to achieve the goals of the program. Prospective performers are encouraged (but not required) to form teams with varied technical expertise to submit a proposal to the CATALYST solicitation.
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.
Interested in learning more about the CATALYST program?
CATALYST Teaming
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.
| Contact | Organization Name | Location | Description of Research Focus Area | Description of Teaming Partner | Technical Areas | |
| Amir Nasajpour | Entropic Biosciences, Inc | anasajpour@entropicbiosciences.com | Los Angeles, CA | Entropic is a nationally recognized first-in-class platform technology by the National Inventors Hall of Fame and USPTO that makes 3D organoids and tissue at an unprecedented rate in less than 14 hours. We use this platform to address the in vitro drug screening and regenerative medicine market, which is projected in 2030 at $86B. | We are looking to leverage our first-in-class technology to build 3D organoids and tissues for ex vivo datasets for models to develop and generate datasets to inform the In silico human physiology models | TA2: Living systems tools for model development |
| Arezoo Ardekani | Purdue University | ardekani@purdue.edu | West Lafayette, IN | I have developed several high-fidelity computational models of transport processes related to subcutaneous injection of therapeutics and drug absorption, compartment models for drug bioavailability, in silico models of spring-driven autoinjectors, and computational models of tissue response to drug injection. Together with colleagues here at Purdue, we have worked on different aspects of in silico models of human physiology and drug delivery and published more than 70 journal articles. | We are seeking TA2 area with pathophysiology model capabilities | TA3: In silico human physiology and pathophysiology models |
| Jason Rodriguez | Applied Research Associates, Inc | jrodriguez@ara.com | Arlington, VA | 1) Developing within-host models of disease dynamics/immune response and mechanism of actions for countermeasures for DTRA. 2) Building virtual avatars with physiological signatures as part of the DARPA Triage Challenge. 3) A model of respiratory risk assessment used by inhalation toxicologists to evaluate lung dosimetry. The latter applies to the within-host and physiological modeling for an end-to-end capability for host response, cascading impacts, and medical countermeasure modeling. | We are looking for TA-1 and TA-2 teammates. Our TA-3 capabilities are under active investments from multiple organizations and internal R&D funds, and many of our products are open source or freely available, so we represent the ability to leverage other portfolios investments for a more complete physiological modeling package. | TA3: In silico human physiology and pathophysiology models |
| Andrzej Przekwas | CFD Research Corp | andrzej.przekwas@cfdrc.com | Huntsville, AL | CFD Research has 20 years of experience in multiscale computational medicine, biology and pharmacology. Our open access, CoBi multiscale modeling tools enable first ever translation of in vitro MPS-based drug development data to in vivo human pharmacology. CoBi-QSP enables linking whole-body compartmental, spatial organ/tissue, and signaling pathway models. | In the CATALYST program we plan to either prime or significantly contribute to TA2 and TA3. We are discussing potential collaboration with US academia with personalized PBPK/PD/ADME/BxK/Tox mechanistic and AI/ML capabilities. We are looking for potential Product Sponsor(s). | TA2: Living systems tools for model development, TA3: In silico human physiology and pathophysiology models |
| Harsha Teja Garimella | CFD Research Corporation | harshatejagarimella@gmail.com | Huntsville, AL, AL | CFDRC has 20 years of experience in computational medicine, biology and pharmacology. Our open-access, CoBi multiscale modeling tools enable translation of in vitro MPS-based drug development data to in vivo human pharmacology. It enables linking whole-body compartmental, spatial organ/tissue, and signaling pathway models. We established QSP platform (ML-solver-analytics) for biologics and nano-formulations for neurodegenerative and autoimmune diseases. Plan to prime or contribute to TA2/TA3. | We are discussing potential collaboration with US academia with personalized PBPK/PD/ADME/BxK/Tox mechanistic and AI/ML capabilities. We are looking for potential Product Sponsor(s). | TA2: Living systems tools for model development, TA3: In silico human physiology and pathophysiology models |
| Emma Wyllie | Datavant | EmmaWyllie@datavant.com | Phoenix, AZ | Datavant is a leader in privacy-preserving data exchange, connecting health data for 500+ institutions and 300 million patients, across 10 billion records. Their HIPAA-compliant solution combines with our ecosystem of data partners to support 800+ live connections. With advanced medical record retrieval and tokenization, Datavant enables the largest de-identified real-world data exchange, supporting everyone from pharmaceutical companies to large research institutions like the NIH. | We can facilitate data linkage and supplementary real-world data (RWD) inclusion to any project, and so would be seeking partners to provide the broader platform and toolkit required for this initiative. | TA1: Data discovery methods for predictive drug safety models |
| Ravi Iyengar | Icahn School of Medicine at Mount Sinai | ravi.iyengar@mssm.edu | New York City, NY | Systems Pharmacology: Please see our most recent paper in Nature Communications, Multiscale mapping of transcriptomic signatures for cardiotoxic drugs. (Nat Commun. 2024 Sep 11;15(1):7968. doi: 10.1038/s41467-024-52145-4). The data and our analyses are available on a preliminary website (predictox.org). We have expertise in integrating transcriptomics and dynamic models for toxicity predictions (ref, Front Pharmacol 2023 doi: 10.3389/fphar.2023.1158222) | Folks with expertise in integrating advanced AI algorithms with Ordinary differential equations (ODE) & Partial differential equations (PDE) models -- Folks from Google developing the weather models using this approach. | TA3: In silico human physiology and pathophysiology models |
| Jed Lampe | University of Colorado | jed.lampe@cuanschutz.edu | Aurora, CO | My team is uniquely positioned to develop comprehensive in vitro and in silico models of drug metabolism and disposition throughout the human lifespan, as drug disposition varies dramatically as a function of age. In particular, we have proven expertise in developing drug disposition models in special population groups, such as pregnant persons, neonates, and developing infants. We are currently extending these models to predict drug pharmacokinetics and disposition in the elderly as well. | We are currently looking for industrial partners that will work with us to implement these novel models to support IND applications by providing them with timely information on drug disposition and pharmacokinetics in a variety of populations groups to support more accurate, faster, cheaper, and safer clinical trials. | TA2: Living systems tools for model development, TA3: In silico human physiology and pathophysiology models |
| John Collins | Biopico Systems Inc | collins@biopico.com | Irvine, CA | The current interest of Biopico Systems Inc is developing high throughput preclinical multiorgan models for drug testing. We are currently focused on gut-brain/blood-brain-barrier models to integrate for toxicological and pharmacological testing. Specifically, we aim to study senescence-based mechanisms in Alzheimer’s disease and radiation-induced senescence caused by space radiation and cancer treatments. We are also keen on advancing senotherapeutics development to counteract these conditions. | We are actively seeking drug developers who have screened molecules and have candidate drugs ready for testing in our in vitro model systems. Additionally, we are open to suggestions and collaborations that are relevant to our proposal. We welcome any opportunities for participation that could further enhance the success of this project. | TA2: Living systems tools for model development |
| Riccardo Barrile | University of Cincinnati | riccardo.barrile@uc.edu | Cincinnati, OH | Our expertise lies in the development of vascularized Organ on Chip models, specifically focusing on the brain, lung, and intestine. | We are seeking expertise in in silico prediction, digital twin development, and pharmacokinetic analysis to enhance our research and development efforts. | TA2: Living systems tools for model development |
| Yanguang Cao | University of North Carolina at Chapel Hill | yanguang@unc.edu | Chapel Hill, NC | We are focusing on developing in vitro tools (such as microphysiological systems and cellular 3D models) and in silico models (including context-specific physiologically-based pharmacokinetics (PBPK), pharmacodynamics, and quantitative systems pharmacology) to facilitate drug development and the early clinical translation of efficacy and toxicity. | TA1: AI/ML-driven drug discovery and early phase clinical translation; Seeking Product Sponsor and drug development collaborators | TA2: Living systems tools for model development, TA3: In silico human physiology and pathophysiology models |
| Nobuhiko Hamazaki | University of Washington | hamazaki@uw.edu | Seattle, WA | We are working on the modeling of human post-implantation development in vitro using human pluripotent stem cells. We recently established a stem-cell-based embryo model called RA-gastruloid (Hamazaki et al., 2024). The RA-gastruloid model can robustly recapitulate the Heart/Neural/Somite/Renal/Gut development with the embryonic morphologies. | We are seeking a partner(s) who is working on the analysis and prediction of the effects of the drug. | TA2: Living systems tools for model development |
| Min Yang | University of Washington | yangmin@uw.edu | Seattle, WA | We study chromosomal instability during the error-prone stage of early human embryogenesis. Dissecting the cellular fitness during embryogenesis informs not only pregnancy outcomes and developmental conditions, but also cancer research by modulating cellular fitness mechanisms. We have developed robust in vitro stem systems, including high throughput 2D and 3D stem cell models to study the relative fitness of cells with varying levels of genomic instability. | Partners who can provide products (either FDA-approved or novel drugs) to conduct drug screenings on our system to identify effectors that facilitate pregnancy, rescue Turner/Down syndrome phenotypes, or influence cell competition in general (applicable to cancer drug development). | TA2: Living systems tools for model development |
| Lena Neufeld | MIT - Massachusetts Institute of Technology | nlena@mit.edu | Cambridge, Massachusetts, MA | Our lab focuses on developing biomaterials for delivering small molecules, nucleic acids, and cell therapies. We address translational challenges through pre-clinical and first-in-human studies of new drug delivery and sensing technologies. Additionally, we develop machine learning tools to enhance drug formulation and delivery, and we use ex vivo/in vitro tissue models to study drug transport and tissue behavior. | Our group seeks team partners who bring complementary expertise in drug delivery, machine learning, or tissue modeling. We value innovative collaborators, driven by translational research, and experienced in pre-clinical and clinical development. Ideal partners will have strong capabilities in regulatory navigation, and scaling solutions for human use, with a shared goal of advancing next-generation therapeutics and technologies. | TA2: Living systems tools for model development |
| Falgun Shah | Merck | falgun.shah@merck.com | west point, PA | pharmaceutical drug discovery and development | Organ safety derisking and prediction of side effect | TA3: In silico human physiology model |
| Cory Funk | Fulcrum Neuroscience | cfunk@fulcrumneuro.com | Seattle, WA, WA | Our digital twin capabilities extend into research, generating deep insights into disease pathology and variability in diverse populations. This research is driving novel biomarker characterization and innovative strategies for stabilizing brain energy metabolism, including new drugs. | We are looking for potential partners for development of pre-clinical models | Product Sponsor, Novel drug development activity |
| Francisco Nogueira | Accumulus Synergy | Francisco.nogueira@accumulus.org | San Francisco, CA | Accumulus Platform is a transformative data exchange platform to enable enhanced collaboration and efficiency between any two or more organizations throughout drug development life cycle (pre-clinical to post approval) and paving the way for a global digital dossier in the cloud | Pharma companies, Biotech, CRO's, Academic Centers and Regulators | TA1: Data discovery methods for predictive drug safety models |
| Jeremy Cramer | CHERRY BIOTECH | jeremy.cramer@cherrybiotech.com | PARIS (FRANCE) 14 rue de la Beaune, Montreuil | Cherry Biotech is a biomedical company which aims to better Predict drug's effect on Humans and replace Animal Experimentation via MultiOmic AI/ML Data Processing from our Organ on a Chip Platform. Uniquely in a standard multiwell plate, CUBIX platform enables to recreate in vitro immunocompetent vascularized human multi organ models and their complex tumor microenvironments mimicking in vivo phenotype. MultiOmic data generated are processed through AI/ML to better assess drug toxicity/efficacy. | Based on our skills in instrumentation, microphysiological model development, and multiomic data processing (phenomic, metabolomic, etc). We are looking for a team with expertise in clinical data collection, including anatomy-pathological data. The approach of retrospective comparative analysis of clinical data with our model will enable predictive models to be strengthened and validated. | TA3: In silico human physiology model |
| François-Henri Boissel | NOVA IN SILICO | francois.boissel@novainsilico.ai | Lyon, France | Nova In Silico has vast experience building in silico human physiology models in multiple therapeutic areas. Notably, Nova In Silico is also developing a high-performance in silico trial platform which (i) makes disease models easy to audit, (ii) makes simulations very efficient to run (10x faster than competing environments) and (iii) makes collaboration seamless between subject matter experts (disease experts, biologists, modelers, etc.). | We would need a partner which can address TA1: "data discovery methods for predictive drug safety models". | TA3: In silico human physiology model |
| Raghu Rayannagari | Singularity IT Solutions LLC | raghu@singularityitsolutions.com | West Chester, PA | Singularity IT Solutions is focused on cutting-edge research in Artificial Intelligence, Machine Learning, and Data Engineering, particularly for healthcare, cybersecurity, and cloud-based applications. We are exploring advanced generative AI models, real-world data integration for personalized medicine, and optimization of algorithms to accelerate drug discovery and cancer research. Additionally, we investigate secure cloud architectures for scalable data processing. | At Singularity IT Solutions, we seek teaming partners with complementary technical expertise in AI, cloud, and data engineering, alongside proven industry experience. We're looking for innovation-driven organizations aligned with our values of integrity, collaboration, and security. A focus on long-term partnerships, regulatory compliance, and cultural fit is essential, as we work to create high-quality solutions for critical sectors like healthcare and government. | TA1: Data discovery methods for predictive drug safety models |
| Ya Wang | Texas A&M University | ya.wang@tamu.edu | College station, TX, TX | Machine-learning (ML) enhanced physiologically based pharmacokinetic (PBPK) modeling to predict real-time delivery of brain-targeting nanomedicine. | We are interested in exploring new modeling approaches to reduce the R&D cycle for neurotherapeutic drug development. | TA3: In silico human physiology model |
| Sana Syed | Duke University | syedsana@gmail.com | Durham | Predicting biologic response using precision medicine in pediatric and young adults with inflammatory bowel disease (IBD) | Radiology AI, experience with building a company, have software experience to create an intuitive human facing interface that reads out or visualizes results from complex AI-driven biomedical image (radiology & pathology) and tissue 'omics analysis including multimodal generative AI and foundation models. | TA1: Data discovery methods for predictive drug safety models |
| Mahsa Dabagh | University of Wisconsin-Milwaukee | mahsa.dabagh2@gmail.com | Milwaukee, WI | My lab is developing in silico models of human tissue and vasculature. Our first ultimate goal is to apply the developed models for preclinical testing and virtual clinical trials to accurately predict drug safety and efficacy in humans and to estimate toxicity and safety profiles for drug candidates. Our ultimate second goal is that our models will offer adaptive plans in anticipation of patient response. | Collaborating with groups which collect biomedical data using sensors or other technologies and also groups which have (in vivo or ex vivo experiments) to validate the findings of our in silico model. | TA3: In silico human physiology model |
| Joerg Martini | SRI International | joerg.martini@sri.com | Palo Alto, CA | We work on optical calorimetry and spatially resolved thermometry that is compatible with microscopy of cells and organoids. Our work resolves sub-milliKelvin temperature shifts with millisecond time resolution. The optical concept can be used to probe temperature distributions and their temporal development at the micron level. This technology is capable of revealing the metabolic effects of novel drugs on individual cells, 3d-cell constructs, or organoids as well as measuring binding events. | We can contribute to TA2 with novel capabilities to characterize metabolic pathways and binding/enzymatic reactions with high throughput measurements. We are looking for a prime who is interested in utilizing these capabilities. We are very used to the process of proposal submission with ARPA-H and there are many other capabilities within SRI International that might be missing pieces in your proposal. | TA2: Living systems tools for model development |
| Gregor Neuert | Vanderbilt University | gregor.neuert@vanderbilt.edu | Nashville, TN | Our research explores how different environmental and drug profiles impact cells compared to acute treatments. We developed the InVitroProfiler, a novel cell culture platform that analyzes pharmacokinetic/pharmacodynamic (PK/PD) relationships in vitro. This system advances drug development by mimicking human-relevant PK profiles, allowing us to study drug effects on cellular behavior without relying on animal models, offering more predictive preclinical testing. | We seek partners in drug development to apply our technology to various drugs and in-vitro systems, focusing on toxicity and efficacy studies. Our current work centers on blood cancers and suspension cultures, but we are open to other drugs and disease phenotypes. We also seek computational partners to test drugs or generate data for constraining computational and predictive models. | TA2: Living systems tools for model development |
| Molly Gallagher | Johns Hopkins University Applied Physics Laboratory | molly.gallagher@jhuapl.edu | Laurel, MD | The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is well-equipped to address the needs of the ARPA-H CATALYST program through its expertise in biological systems, digital twin technologies, organ-on-a-chip systems, data analytics, and systems engineering. JHU/APL's capabilities in these areas can contribute significantly to the program's goal of revolutionizing the drug development process by reducing costs and improving outcomes. | The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is seeking pharmaceutical product partners. JHU/APL has extensive experience in molecular modeling, digital twins, organoid and organ-on-a-chip technologies, but is not a pharmaceutical product developer. | TA2: Living systems tools for model development, TA3: In silico human physiology model |
| Theodore Alexandrov | University of California San Diego | talexandrov@health.ucsd.edu | San Diego, CA | Our lab at the Department of Pharmacology, UCSD, develops technologies for spatial and single-cell metabolomics, which can generate metabolic drug response profiles for millions of single cells, in a high-throughput fashion, providing data for training toxicology and metabolic response models. Moreover, we are developing Deep Learning models for such predictions based on the large in-house datasets available to us. | We would be excited to collaborate with a partner or academic lab having in-depth expertise in toxicology and in-house libraries of drugs and drug candidates with recorded toxicology profiles. We are particularly interested in applications and approaches focusing on hematotoxicology. | TA2: Living systems tools for model development |
| Jacqueline Summers | Health TIE | Jacqueline@healthtie.org | Anchorage, statewide, AK | Health TIE is an Alaska-based healthcare innovation hub focused primarily on deployment in four different areas: 1) Behavioral Health 2) Substance Use Disorders 3) Elder/Senior caregiving 4) Intellectual and Developmental Disabilities | Teaming partners who are interested in testing ideas in remote and rural areas | TA2: Living systems tools for model development |
| Nicholas Nystrom | Peptilogics | nicholas.nystrom@peptilogics.com | Pittsburgh, PA | Peptilogics is revolutionizing the discovery process for novel peptide therapeutics for patients with serious and life-threatening diseases. Peptilogics’ Nautilus™ platform has been shown to achieve SOTA performance across ADMET properties, produce binding ligands for a previously undrugged target where HTS has failed, and improve potency by 4400x over expert human-designed lead candidates. Our experience designing the Human BioMolecular Atlas Program (HuBMAP) is strongly aligned with CATALYST. | Mutual benefit would accrue with partners with wet lab capabilities designed for rich data collection and rapid turnaround (TA3). Mutual benefit would also accrue with partners who have relevant historical data that has not been curated or processed for AI/ML systems or interoperability with complementary datasets. | TA1: Data discovery methods for predictive drug safety models |
| Peter Gompper | Rubitel | peter@rubitel.com | San Francisco, CA | Rubitel is currently conducting research on preanalytical sample quality -- crucial for diagnostic accuracy and positive patient outcomes. Poor quality leads to medical errors -- the 3rd leading cause of death in the US -- and without data on preanalytical sample quality, standards (i.e., from The Joint Commission, NCQA, AHRQ, CLIA, CAP and ISO) are that are nearly impossible to demonstrate compliance with. | We are seeking partners for human factors studies in preparation for the implementation of a new technology which aims to monitor sample quality in real time to meet compliance requirements and support the quality-focused reimbursement strategies of HCPs, clinics, laboratories and R&D organizations. | TA1: Data discovery methods for predictive drug safety models |
| Andrew Su | Scripps Research | asu@scripps.edu | San Diego, CA | My bioinformatics lab focuses on biomedical data discovery and integration. We have participated in many large relevant collaborations including the NCATS Translator program, the NSF Proto-OKN program, the NIAID Data Ecosystem, and the NIH Big Data to Knowledge program. More broadly, Scripps Research has extensive capabilities in drug discovery and translational research through our Calibr-Skaggs Institute for Innovative Medicines. | Open to discussions | TA1: Data discovery methods for predictive drug safety models |
| Saikat Basu | South Dakota State University | Saikat.Basu@sdstate.edu | Brookings, SD | Our expertise lies in TA3. We can develop physiologically realistic computational fluid dynamics models of anatomical pathways based on medical imaging data and of drug transport therein. Our primary focus in this domain is on targeted respiratory drug delivery. | We are looking for collaborators in TA1 and TA2 | TA3: In silico human physiology model |
| Jelena Vukasinovic | Lena Biosciences | jvukasinovic@lenabio.com | Atlanta, GA | Fit-for-purpose tissue models and prognostic assays for small molecule drug-induced liver injury context of use | Computational toxicology/multimodal data readiness with the expertise in QSAR/hazard ID and/or IVIVE | TA1: Data discovery methods for predictive drug safety models |
| Jesse Dill | Ginkgo Bioworks | jdill@ginkgobioworks.com | Boston, MA, MA | Ginkgo Bioworks develops and applies high-throughput cellular screening workflows to support R&D and manufacturing goals for its collaborators. We have particular expertise in high-throughput engineering and screening of mammalian cells, from pooled to arrayed workflows. Additional capabilities of interest are iPSC engineering and differentiation, immune response profiling, protein and RNA design and construct screening, high-content imaging, functional genomics, and organoid based assays. | Interested in finding teaming partners for TA3 and TA1. | TA2: Living systems tools for model development |
| Rachel Clipp | Kitware | rachel.clipp@kitware.com | Carrboro, NC | Kitware, Inc. is a leader in research and development and open source software platforms. We have developed and maintain the open source whole-body computational physiology model, Pulse Physiology Engine. We specialize in computational model developments and digital twin development for in silico trials. We also have extensive experience with software development, maintenance, and build and release cycles. | Kitware is looking for a partner with drug development expertise and experience with drug modeling. We are also open to collaborating with a variety of other expertise, including statistics and population modeling. | TA3: In silico human physiology model |
| Igor Balaz | Neovivum Technologies LLC | igor.balaz@df.uns.ac.rs | Novi Sad, Serbia | We have two focus areas. First: developing a computational platform for advancing cancer treatment using our innovative multi-scale QSP tumor and drug-treatment simulator, integrated with an ML engine for high-throughput in silico testing of drug delivery systems and stand-alone drugs. Second: a deep learning framework that combines data from biomarker mapping, omics data, cell viability assays, and drug properties to uncover insights into organ-drug interactions. | We seek to partner with organizations that have access to large medical datasets and expertise in database management and data integration. Ideal partners will have experience curating publicly available bioinformatics databases and leveraging diverse data sources, with emphasis on ontology and knowledge graph development and integration. | TA3: In silico human physiology model |
| Patrick McLendon | BlueHalo | patrick.mclendon@bluehalo.com | Dayton, OH | In vitro MPS/in silico toxicology and ADME, with specialized focus in AI/ML-based data engineering. Digital healthcare, clinical data infrastructure, data harmonization and integrations, expertise in DevSecOps with data governance | Ideal teaming partners would have expertise in humanized in vivo/ex vivo models, high throughput capabilities. Partners with ability to pull large/expanded clinical data sets and/or expertise with GxP are also highly sought.. | TA3: In silico human physiology model |
| Harriet Kamendi | Kandih BioScience | hkamendi@kandih.com | Silver Spring, MD | AI Driven Predictive Toxicology Dashboard | Partners that can provide us with validation data such as centers for medicare and medicaid (health data); CDC mortality data; FDA adverse event data | TA3: In silico human physiology model |
| Case Lorance | NEXI Biotech | Loranceconsulting@gmail.com | Tampa, FL | Designing functional models of the brain. | AI Driven Insights and Visualization | TA3: In silico human physiology model |
| Zhongyue Yang | Vanderbilt University | zhongyue.yang@vanderbilt.edu | Nashville, TN | My research focuses on building Mutexa, a computational ecosystem aiming to minimize and ultimately replace screening-based protein drug development. We created databases enabling easy curation of enzyme structure and function data (IntEnzyDB and Open Enzyme Database: https://intenzydb.accre.vanderbilt.edu), and in silico-predicted antimicrobial lasso peptide structure data (LassoPred: https://lassopred.accre.vanderbilt.edu). | Our primary expertise lies in constructing integrated enzymology database for protein-protein and protein-drug complexes, and we look for teammates who have experiences with pre-clinical data. | TA3: In silico human physiology model |
| Julia Komissarchik | Glendor, Inc | julia@glendor.com | Draper, UT | Glendor is on a quest to safeguard patients’ privacy by de-identifying Protected Health Information (PHI) from multimodal medical data (images, reports, videos, photos, voice) while empowering BAA-free data sharing. Glendor PHI Sanitizer - automatic in situ PHI de-identification software that is easily integrated into the existing data workflows. | We can provide easily integrated automatic tools for PHI de-identification and are seeking partners that are looking to strengthen patient's protection and HIPAA compliance of the existing and newly built data workflows. | TA1: Data discovery methods for predictive drug safety models |
| Aishwarya Balajee | Zifo | aishwarya.b@zifornd.com | Cary, NC | Zifo is a scientific data, digital and informatics services company. Zifo supports top global biopharma and biotech companies in their digital journeys. Zifo provides services including but not limited to scientific data management, data architecture, data engineering, data science AI/ML, bioinformatics, cheminformatics, GxP validation etc. Our team members are skilled in science and technology, specifically addressing biopharma and biotechs' data needs in the drug discovery and development. | We are looking to partner with Teams that can support TA 2 (Living systems tools model development) as well as looking for Product Sponsors. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Wendy Goodson | Ginkgo Bioworks | wgoodson@ginkgobiowork.com | Boston, MA | Ginkgo Bioworks develops and applies high-throughput cellular screening workflows to support R&D and manufacturing goals for its collaborators. We have particular expertise in high-throughput engineering and screening of mammalian cells, from pooled to arrayed workflows. Additional capabilities of interest are iPSC engineering and differentiation, immune response profiling, protein and RNA design and construct screening, high-content imaging, functional genomics, and organoid based assays. | Interested in finding teaming partners for TA3 and TA1. | TA2: Living systems tools for model development |
| Ryan de Ridder | Avery Digital Data, Inc. | ryan@avery.tech | San Diego, CA | Avery solves high-throughput experimentation and functional data generation for biological engineering by automating the Design-Build-Test-Learn workflows using scalable semiconductor chip technology. This unlocks low-cost high-throughput programmable bioengineering workflows and massive experimental data generation. | Avery would like to team up with Product Sponsors or companies addressing TA2 and TA3 | TA1: Data discovery methods for predictive drug safety models |
| Donghoon Lee | Omphalos Lifesciences | donghoon.lee@omphaloslifesci.com | Dallas, TX | We develop digital humans for virtual drug testing that biologists can efficiently analyze, modify, and extend. Our platform integrates vital organs essential for pharmacokinetics, simulating pharmacodynamic responses to assess drug efficacy, toxicity, and delivery across dosing regimens. We prioritize the organs of interest aligned with our teaming partners' objectives for high-resolution details at the tissue, cell, and molecular levels. | We seek drug developer partners with both clinical study and preclinical trial data to develop and validate our digital human model and its components. While open to customizing our model to specific disease areas, we prefer collaborations centered on pathologies of vital organs and systemic diseases such as cardiovascular, renal, hepatic, and hematopoietic conditions. | TA3: In silico human physiology model |
| Duxin Sun | University of Michigan | duxins@med.umich.edu | Ann Arbor, MI | Why does 90% of drugs fail despite significant improvement of each step of the process? Are current strategies including AI-driven approaches falling into "survivorship bias" trap? Why GLP tox is not predictive of clinical adverse events (AE)? We are developing Screening Tool for Assessing Reporting (STAR)-guided AI/ML model from five key features, in vitro/in vivo and phase 0+ experiments to predict clinical dose/efficacy/safety to streamline process, select best drugs, and improve success/effi | CRISPR screen to identify/confirm on-/off drug targets with high throughput capability. Spatial single cell transcriptomics imaging. Organ-on-a-chip with >20 organs and high throughput capability. Antibody generation capability against small molecules. Downloadable database for gene expression in different tissue and cell types, or clinical AEs, or concentration, or drug's tissue/cell selectivity. Validated ML models for on-/off-targets and drug-target interaction for >30,000 targets. | TA3: In silico human physiology model |
| Steven George | University of California, Davis | scgeorge@ucdavis.edu | Davis, CA | We have been developing organ-on-chip (or complex in vitro models) technologies for >15 years with contributions in modeling the airways, the microcirculation, the heart, the bone marrow, and the cancer microenvironment. Our current focus area(s) include human bone marrow with an emphasis on granulopoiesis. Our model maintains hematopoiesis for up to three weeks, and we can collect function neutrophils that egress, thus providing a model that could simulate drug toxicity including neutropenia. | Our lab provides expertise in experimentally modeling human neutropenia and the microcirculation (TA2); thus, our expertise would partner with groups providing expertise in the TA1 and TA3. Our lab could generate experimental data that could be compared to existing clinical data and be used to validate in silico models focused on 1) simulating bone marrow toxicity and, in particular, neutropenia; and/or 2) drug absorption in the microcirculation or drug-induced vascular injury (DIVI). | TA2: Living systems tools for model development |
| Zhe He | Florida State University | zhe@fsu.edu | Tallahassee, FL | Health Informatics; Biomedical Informatics: AI | Healthcare Systems for AI solutions | TA1: Data discovery methods for predictive drug safety models |
| David Blanchard | JHUAPL | david.blanchard@jhuapl.edu | Laurel, MD | The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is well-equipped to address the needs of the ARPA-H CATALYST program through its expertise in biological systems, digital twin technologies, organ-on-a-chip systems, data analytics, and systems engineering. JHU/APL's capabilities in these areas can contribute significantly to the program's goal of revolutionizing the drug development process by reducing costs and improving outcomes. | The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is seeking pharmaceutical product partners. JHU/APL has extensive experience in molecular modeling, digital twins, organoid and organ-on-a-chip technologies, but is not a pharmaceutical product developer. | TA3: In silico human physiology model |
| Valon Llabjani | Revivocell Inc. | valon@revivocell.com | New York, NY | Revivocell Inc., based in the UK and US, develops AI-powered in vitro human relevant organ models using our patented NANOSTACKS™ technology to predict drug safety and efficacy. Our focus includes liver diseases (MASLD), Drug induced liver injury (DILI), neurotoxicity, and seizure liability. By integrating AI/ML and MEA sensors, we provide reliable preclinical data that aligns with FDA/EMA standards, reducing the need for animal testing and improving success rates in clinical trials. | We seek partners with expertise in pharmacokinetics (PK) modeling, AI/ML algorithms, and data analysis to enhance our in in-vitro platforms. We’re also looking for pharmaceutical companies to validate our AI-powered organ models in IND-enabling studies, particularly for drug safety, liver disease, and seizure liability. Regulatory expertise to ensure alignment with FDA and EMA standards is also valued to drive successful drug development. | TA2: Living systems tools for model development |
| Colleen Clancy | UC Davis | ceclancy@ucdavis.edu | Sacramento, CA, CA | We propose to revolutionize industrial drug discovery via a digital twin-based approach to mirror each step of the industrial process in a virtual model. Digital twins comprises components for each system scale that includes computational workflows with models and simulators, AI and ML based analysis tools, real-world and synthetic data for model creation, and predicted data. The approach enables real-time prediction, monitoring, and analysis from initial compound screening to clinical trials. | Looking for drug discovery partners to work in parallel to allow testing of virtual digital twin format for accuracy in safety and efficacy. Also looking for partners in PKPD to incorporate into the digital twin. | TA1: Data discovery methods for predictive drug safety models |
| William Busa | EvE Bio, LLC | bbusa@evebio.org | Durham, NC | EvE Bio is a non-profit Focused Research Organization dedicated to "mapping the pharmome:" physically screening drugs against thousands of human gene products to systematically identify drugs' off-targets. Our efforts include technology development for highly multiplexed target activity assays to make pharmome mapping better, faster, and cheaper, and better able to fulfill the data needs of AI/ML drug discovery systems. | In silico human physiology model developer whose capabilities include AI/ML benefiting from rich data revealing previously unknown off-target side effect mechanisms (ID of molecular off-targets). | TA2: Living systems tools for model development |
| Chloe Xie | Kennesaw State University | yxie11@kennesaw.edu | Marietta, GA, GA | Kennesaw State University X-Lab offers a dynamic environment where undergraduate and graduate students collaborate with faculty mentors to conduct cutting-edge research across diverse disciplines. Our multidisciplinary team aims to revolutionize healthcare through innovative science, including bioengineering, drug discovery, dynamics simulations. | Whoever is interested in running a high-risk high-reward pilot project in KSU X-Lab. | TA2: Living systems tools for model development |
| Jyotika Varshney | Verisim Life Inc. | jo.varshney@verisimlife.com | San Francisco, CA | VeriSIM Life, a well-funded biotech startup, offers AI-driven solutions for drug discovery and development. Our proprietary Translational Index predicts clinical success of drug compounds, addressing various development challenges in PK-PD and Tox. Our AtlasGEN Generative Chemistry engine explores chemical space to efficiently optimize candidates. Our team combines deep knowledge and experience in life sciences, computational chemistry, math modeling, and AI, to revolutionize drug development. | We are looking for a partner with expertise and capabilities in advanced living system tools. We are eager to partner with those working with innovative biological models, such as organoids, microfluidic devices, or other cutting-edge in vitro platforms that closely mimic human physiology. By integrating these experimental approaches with our AI-driven technology, we aim to further enhance the accuracy and efficiency of drug development processes for this project. | TA3: In silico human physiology model |
| Gus Rosania | University of Michigan | grosania@umich.edu | Ann Arbor, MI | My research is on prediction of small molecule off-target biodistribution, chemical stability, redox potential/free radical generation, and organelle-related (lysosomal/mitochondrial) toxicity -using in silico, in vitro and animal models. | Clofazimine’s volume of distribution is 100,000+ Liters. Cannabidiol’’s is 20,000+ L. We found where clofazimine goes. But, where does CBD go? Nobody knows. If you think it is important to predict and model how drug molecules behave in cells, team up with us! | TA3: In silico human physiology model |
| Zhoumeng Lin | University of Florida | linzhoumeng@ufl.edu | Gainesville, FL | Our lab focuses on development of PBPK models for drugs, environmental chemicals, and nanoparticles in animals and humans. We also apply machine learning and AI approaches to build AI-assisted QSAR models to predict ADME properties, carcinogenic and non-carcinogenic toxicities of drugs in animals and humans. In the past several years, we have curated a database on nanoparticle PK and toxicity in mice. We have also curated a database for carcinogenic and non-carcinogenic toxicities of chemicals. | We are looking for collaborators with expertise in TA2 and product sponsors. | TA3: In silico human physiology model |
| Guangbo Chen | Medical College of Wisconsin/Versiti Blood Research Institute | guangbo@mcw.edu | Milwaukee, WI | We developed a high-throughput screening system using spleen from transplant donors. While many in vitro assays can capture some aspects of immune response, they do not recapitulate a chain of immune reactions resulting in antibody production. We established human spleen organoids. HSO demonstrates features of a germinal center reaction. We screened for vaccine adjuvant activity of 19 cytokines in 3 conc across 5 donors. The results demonstrate HSO's utility for immune functional assays. | We are looking for collaborators. | TA2: Living systems tools for model development |
| Jenny Yang | Nook Biosciences | jenny@nookbio.com | San Francisco, CA | We are uncovering how the gut's metabolic processes impact drug efficacy and toxicity. With end-to-end automation—from lab work to AI analysis and clinical validation—we’re building the largest proprietary database of drug-gut interactions in a diverse patient population, focusing on how the microbiome drives individual variability in drug response. Our platform provides instant, actionable insights that can double drug efficacy rates and significantly expand the addressable market. | We are seeking partners across the full pipeline, including those for data generation (microbiome sample collection, metagenomics, metabolomics), data science (bioinformaticians, ML developers), and clinical validation (hospitals, and institutions with patient cohorts). | TA1: Data discovery methods for predictive drug safety models |
| Maksym Krutko | imec USA | krutko01@imec.be | Boston, MA | Imec, the world's leading independent nanoelectronics R&D hub, is developing organ-on-a-chip technology to replicate human physiology on silicon. Imec's organ-on-chip technology platform encompasses microfluidics, multi-electrode arrays, biosensors, lens-free imaging, and data analytics, broadening the scope of current applications. Focus areas include barriers like gut-on-chip and blood-brain barrier on chip as well as brain-on-chip and heart-on-chip. | Imec is actively looking for partners to further develop disease-on-chip models beyond current scope of TA2 (Living systems tools for model development) and TA3 (In silico human physiology models) with opportunities for broader collaboration. | TA2: Living systems tools for model development |
| Matthew Lawrence | Virscio | mlawrence@virscio.com | New Haven, CT | Virscio is a translational research company accelerating the development of innovative therapeutics through validation and application of the most informative preclinical models to screen candidate interventions. Virscio conducts humane, sustainable nonhuman primate research augmented by advanced tissue pharmacodynamics achieved through histopathology and molecular analyses to generate the data necessary to drive development decisions of our many clients and collaborators. | The ultimate objective behind Virscio translational initiatives is predicting clinical efficacy and safety to the greatest extent possible through the most strategic and thoughtful use of animal and in vitro resources, analytic tools, and data analysis. We are seeking partners with capabilities in sequencing, bioinformatics, gene regulation, systems biology and in silico protein design to join us in realizing this objective. | TA2: Living systems tools for model development |
| Jingwei Lu | Synlico Inc. | info@synlico.com | South San Francisco, CA | Synlico is at the forefront of transforming medicine by leveraging causality to make cellular processes explainable, predictable and engineer able. Our unique approach lies in unraveling the causal relationship between cell modulation and tissue behavior in patients using AI and single cell bioinformatics. Synlico leverages a causality- and prediction-focused approach to navigate the complexities/heterogeneity of oncology and other diseases. | We are looking for partners with access on large/small patients' scRNA-seq data on different/particular disease indications and seeking to identify the causal relations between genes and the cell behavior in patients. We are also happy to collaborate with partners on the AI/Statistics side that focusing on causal discovery and causal inference. We look forward to integrate with partners' expertise with Synlico's computational platform and apply on drug discovery using patients' scRNA-seq data. | TA1: Data discovery methods for predictive drug safety models |
| ANNIE KATHURIA | JHU | akathur1@jh.edu | Baltimore, MD | Tissue Engineering-3D organoids. | University Collaborators | TA2: Living systems tools for model development |
| Niki Santo | Swaza Inc | niki@swaza.life | New York, NY and Mountain View, CA, NY | We are developing a scalable molecular discovery platform called KAIO, which combines two advanced AI technologies: MagGPT and MagBERT. MagGPT is a generative molecular design engine using transformer architecture to generate new molecular structures. MagBERT, also transformer-based, excels in molecular simulation tasks like docking and quantum property predictions. Together, they accelerate discovery in healthcare and materials science, reducing development time and costs. | We are seeking collaborators who can partner on validating the platform’s effectiveness in preclinical drug discovery settings. Access to Molecular Datasets: Partners that can provide extensive and high-quality molecular datasets are critical for improving the robustness and accuracy of Swaza's platform. This includes academic institutions or biotechnology companies with significant data repositories. | TA3: In silico human physiology model |
| Maxwell Sherman | Serinus Biosciences Inc | max@serinus.bio | New York City, NY | Serinus Biosciences fuses AI/ML with proteomics, genomics, and systems biology to map how chemical and genetic perturbations alter protein-protein interactions and larger protein assemblies across disease, tissue, and cellular contexts. We use these maps to identify novel anti-cancer targets, discover drugs to inhibit pathological protein assemblies, a identify off-target wards of experimental therapeutics. Collectively, our team members have brought 7 drugs from early discovery to FIH trials. | We seek to assemble an interdisciplinary team to develop experimental and in silico models that span from individual proteins to the whole human body. This includes 1) TA1 performers that can curate extensive clinical data; 2) TA2 performers with patient-derived advanced culture systems; and 3) TA3 performers experienced in modeling tissue and organ functions. | Product Sponsor, Novel drug development activity |
| Ben Larman | Infinity Bio | ben.larman@infinitybio.com | Infinity Bio Inc is the leading provider of antibody reactome profiling services. | We're looking for partners with well-characterized sample sets that can be used to generate antibody reactome profiles, such that data can be used to develop predictive models of human immune responses. | TA2: Living systems tools for model development | |
| Constantinos Katevatis | IQVIA | constantinos.katevatis@iqia.com | Durham, NC | IQVIA is a leading global provider of AI solutions, RWD, and advance analytics for government, healthcare, and the life sciences industry. Our technology supports RWD generation across the pharma product life cycle, including R&D applications. We have deployed Trustworthy AI – what we call Healthcare-grade AI – solutions to improve patient care and outcomes for over 20 years. Data generated can be linked in compliance with global regulations (e.g., GDPR, HIPAA, etc.). | We bring RWD and AI expertise in support of TA1. We are open to discussions for partners that can support TA2, TA3, as well as other data providers and/or additional ML expertise for TA1 to cover the breadth of this initiative. | TA1: Data discovery methods for predictive drug safety models |
| Qiang Zhang | Emory University | qiang.zhang@emory.edu | Atlanta, GA | Our expertise lies in dynamic modeling of cellular and molecular pathways and whole-body physiology integration. Examples include thyroid system, female reproductive system, humoral immunity, antioxidant response and redox signaling. We also conduct PBPK modeling studies at both individual and population levels. | TA1 area with ML/AI capability to inform model structure and parameters; TA2 area with microphysiological systems that can simulate systems on a chip, such as HPT axis, HPO axis, and lymph node. | TA3: In silico human physiology model |
| John Sadowski | Planned Systems International | Jsadowski@atlintl.com | Cincinnati, OH | Planned Systems International (PSI) is a global IT solutions provider specializing in Federal Health IT. PSI has developed and enhanced the U.S. Military Health System Data Repository which integrates patient data from DoD hospitals and associated health clinics across the world. PSI is also the enterprise test agent for the VA and supports the refinement of VA Enterprise Architecture on multiple contracts. | We are looking for partners with biological laboratory capabilities and experience with in silico biological modeling. | TA1: Data discovery methods for predictive drug safety models |
| Matt Coban | Mayo Clinic | coban.mathew@mayo.edu | Jacksonville, FL | We focus on pathophysiology, structural biology, computational chemistry, and drug design. We will leverage available public data, augmented by enterprise Mayo Clinic, via natural language processing and produce novel molecular dynamics metrics as features in a multimodal AI (including generative) for ADMET predictions. We intend to model the entire proteome, potential interactions between molecules and all proteins for off-target effects and employ dynamics to model time-dependent behaviors. | We seek teams with expertise in various -omics (e.g. metabolomics, microbiomics), molecular allergenicity/immunogenicity, in vitro pharmacokinetics (HLMs, IVIVC), and environmental/dietary impacts on drug response could greatly strengthen our current team. Mayo Clinic has a broad range of capabilities across the Mayo Clinic enterprise, but the above question addresses some of our key strengths, and we think we can build a stronger more diverse team by finding partners with such experience. | TA2: Living systems tools for model development |
| Jana Jensen | Excelsior Sciences | jjensen@deerfield.com | New York City, NY | Modular chemistry to create a new chemical language, redefining data generation and analysis for drug discovery. This language is based on building blocks derived from existing drugs which serve as tokens for large language models to learn from. Our fully automated platform for synthesis and testing can generate a full matrix data set on building blocks and whole molecules enabling the prediction of ADME-Tox properties; 96 compounds can be made and tested in 21 assays in a matter of weeks. | We have a full suite of ADME assays developed for our automated system. We are seeking partners who are developing in vitro tox assays that we can adapt for our platform. | TA1: Data discovery methods for predictive drug safety models |
| Evan Maltz | Tessel Biosciences | evan@tessel.bio | Boston, MA | We have developed a high-throughput organotypic culture model of the human lung epithelium for novel target discovery, drug discovery, and our internal pipeline. Our pipeline uses patient-derived cells to measure the effects of small-molecule and genetic perturbations epithelial permeability, cilia function, and more. We also use a mechanistic model combined with an active learning framework to significantly improve tissue-level phenotype prediction and sample efficiency (up to 30x). | We are looking for partners interested in our high-throughput, computer-aided phenotypic screening capabilities in epithelial tissues (lung, gut, and beyond). We have the ability to generate rich datasets linking molecular states to tissue-level function. Additionally, we are looking for partners interested in leveraging our predictive modeling framework. Our expertise is in combining AI with mechanistic approaches to make interpretable models in data-constrained settings. | TA2: Living systems tools for model development |
| James Fink | Quiver Bioscience | james.fink@quiverbioscience.com | Cambridge, MA | Quiver Bioscience uses cutting-edge, all-optical, high throughput measurements of human and tox species (mouse, rat, etc.) brain cell function to assess on-target efficacy and off-target toxicity of CNS-focused antisense oligonucleotides and other drug modalities, to bring the drugs with optimal profiles to patients in need. | Organizations with complementary experience, expertise and data such as in vivo toxicity and distribution data around RNA-based medicines and oligonucleotides, organ-on-a-chip capabilities, etc. | TA2: Living systems tools for model development |
| Thomas Caulfield | Mayo Clinic | caulfield.thomas@mayo.edu | Rochester, MN | We focus on pathophysiology, structural biology, computational chemistry, and drug design. We will leverage available public data, augmented by enterprise Mayo Clinic, via natural language processing and produce novel molecular dynamics metrics as features in a multimodal AI (including generative) for ADMET predictions. We intend to model the entire proteome, potential interactions between molecules and all proteins for off-target effects and employ dynamics to model time-dependent behaviors. | We seek teams with expertise in various -omics (e.g. metabolomics, microbiomics), molecular allergenicity/immunogenicity, in vitro pharmacokinetics (HLMs, IVIVC), and environmental/dietary impacts on drug response could greatly strengthen our current team. Mayo Clinic has a broad range of capabilities across the Mayo Clinic enterprise, but the above question addresses some of our key strengths, and we thinkwe can build a stronger more diverse team by finding partners with such experience. | TA1: Data discovery methods for predictive drug safety models |
| John Yin | University of Wisconsin-Madison | john.yin@wisc.edu | Madison, WI | To address future pandemics, our interdisciplinary team at the Wisconsin Institute for Discovery (yinlab.discovery.wisc.edu) envisions a transformative class of next-generation therapeutic interfering particles (TIPs) — bioengineered virus-like particles designed to overcome the limitations of current antivirals and mRNA vaccines. TIPs offer a breakthrough approach by co-evolving with viruses, thus preventing viral escape while eliciting robust innate and adaptive immune responses. | Our work integrates synthetic, systems, and computational strategies to accelerate TIP development. By leveraging advanced wet-lab virus cultures, single-cell X-omic measures, computational analyses, and simulations, we aim to rapidly optimize TIPs for safety, efficacy, and scalability. This platform will enable a flexible, adaptable response to viral threats, contributing to resilient pandemic preparedness. Contact John Yin for details (john.yin@wisc.edu). | Product Sponsor, Novel drug development activity |
| Serdar Uckun | Leap AI, Inc. | serdar.uckun@leap-ai.com | Cambridge, MA | in-silico high-throughput screening methods for pharmacodynamics using a proprietary generative AI tool chain | interested in partnering with clinical researchers on TA1 and TA2; looking for Product Sponsors to team with | TA3: In silico human physiology model |
| Lea Sanford | Providentia Technologies | lea@providentia.tech | New York, NY | We're focused on understanding how subtle, aggregate changes in cell membrane properties are correlated with and predictive of drug toxicity | we are looking for collaborative partners with expertise in computational systems physiology and or lipid physiology | TA2: Living systems tools for model development |
| Benjamin Kostiuk | Crohn's & Colitis Foundation | bkostiuk@crohnscolitisfoundation.org | New York City, NY | The Crohn’s & Colitis Foundation’s IBD Plexus program collects, cleans, and aggregates the most comprehensive IBD dataset and biorepository in the world. We follow thousands of clinically phenotyped patients longitudinally. We collect stool, intestinal tissues, and blood. From these samples we’ve generated transcriptomic and proteomic data, pathology images, genomics, and metagenomics. We leverage strategic partnerships to discover, validate, and develop drug targets and biomarkers. | TA3: In silico human physiology model We seek partners who share our goal of curing Crohn’s disease and ulcerative colitis. The ideal partner will have strong technical skills and experience leveraging large real-world datasets for the purpose of drug/biomarker discovery. The IBD Plexus team has strong IBD-specific expertise, so that is not necessary from a partner. | TA2: Living systems tools for model development |
| Venktesh Shirure | University of California Davis | vsshirure@ucdavis.edu | Davis, CA | We have been developing organ-on-chip (or complex in vitro models) technologies for >15 years with contributions in modeling the airways, the microcirculation, the heart, the bone marrow, and the cancer microenvironment. Our current focus area(s) include human bone marrow with an emphasis on granulopoiesis. Our model maintains hematopoiesis for up to three weeks, and we can collect function neutrophils that egress, thus providing a model that could simulate drug toxicity including neutropenia. | Our lab provides expertise in experimentally modeling human neutropenia and the microcirculation (TA2); thus, our expertise would partner with groups providing expertise in the TA1 and TA3. Our lab could generate experimental data that could be compared to existing clinical data and be used to validate in silico models focused on 1) simulating bone marrow toxicity and neutropenia; and/or 2) drug absorption in the microcirculation or drug-induced vascular injury (DIVI). | TA2: Living systems tools for model development |
| Arka Das | Embry-Riddle Aeronautical University | dasa@erau.edu | Daytona Beach, FL | Our team’s research focuses on in-silico and in-vitro investigations aimed at understanding and addressing congenital cardiovascular diseases and congestive heart conditions. We develop computational models and physical simulations to study blood flow dynamics, optimize treatment strategies, and explore new therapeutic interventions. By combining advanced modeling techniques with experimental validation, we aim to improve clinical outcomes for patients suffering from these conditions. | Our team is eager to collaborate with research groups focused on in-silico human physiology models and living system tools for model development. We aim to leverage advanced computational techniques to simulate complex biological processes, improving the understanding of human physiology. By partnering with teams in this field, we hope to advance model development and contribute to innovative solutions for studying and treating various medical conditions. | TA2: Living systems tools for model development |
| Tahmineh Mokhtari | University of California, Davis | mokhtari.tmn@gmail.com | Davis, CA | At Bruce's lab, our researchers are dedicated to developing and synthesizing new drugs while evaluating their efficacy through in vitro, in vivo, and clinical studies. We aim to combine our expertise in drug development with advanced computational analysis to enhance our research outcomes. By integrating innovative methodologies, we strive to improve drug metabolism and toxicity assessments, ultimately accelerating the development of safer therapeutics and addressing drug development issues. | At Bruce's lab, we seek partners to enhance drug development through innovative research and collaboration. We are interested in teaming with organizations like ARPA-H on initiatives such as CATALYST. Our ideal collaborators have expertise in computational modeling, data analytics, and methodologies that improve drug assessments. We value multidisciplinary approaches and aim to explore adaptive study designs to accelerate the development of safer therapeutics. | TA2: Living systems tools for model development |
| Daniel Gonzalez | Duke University | daniel.gonzalez@duke.edu | Durham, NC | The Duke Clinical Research Institute (DCRI) is an academic clinical research organization that focuses on conducting innovative clinical trials and clinical research to improve patient care. The DCRI Pharmacometrics Center conducts regulatory compliant population pharmacokinetic (PK)/pharmacodynamic (PD) and physiologically-based PK modeling analyses with particular expertise in special populations such as children and pregnant women. Our analyses are routinely submitted to the FDA. | We are seeking partners in living system tools to inform physiologically-based PK or quantitative systems pharmacology models in special populations such as children or pregnant women. In addition, we seek industry partners with expertise in developing and deploying AI/ML-enabled in silico tools who are interested in translating these tools into drug dosing recommendations in special populations. | TA3: In silico human physiology model |
| Luca Emili | InSilicoTrials | luca.emili@insilicotrials.com | Trieste, Italy | We are focused on the development of the cloud-based platform where models and data are integrated, creating web application using plug and play and with an orchestrator that give us the opportunity to combine different models to created complex simulations | models developers and data providers in tox experiments | TA1: Data discovery methods for predictive drug safety models |
| Pradipta Ghosh | UCSD | prghosh@ucsd.edu | San Diego, CA | I lead the world's largest and most expansive biobank [UC San Diego HUMANOID Center: https://networkmedicine.ucsd.edu/centers/humanoid/index.html] of adult stem-cell derived 3D models and primary cells that are used to build pre-clinical human models exclusively for use in HTP drug discovery. Our 1500 patient biobank includes cancers, pre-cancer, inflammatory, & other diseases. We build models that are benchmarked for capturing computationally determined invariant phenotypes of the disease. | In silico human physiology models. | TA2: Living systems tools for model development, TA3: In silico human physiology model |
| Vincenzo Carbone | InSilicoTrials Technologies SpA | vincenzo.carbone@insilicotrials.com | Trieste, Italy | InSilicoTrials offers a groundbreaking cloud-based technology platform that generates digital regulatory grade evidence using FDA-supported in silico methodologies. Simulation, predictive intelligence, and AI can be applied to the whole drug development lifecycle, from discovery, clinical trials to commercial strategies. Our platform supports diverse disease areas with cutting-edge models, synthetic patient simulations, and virtual patients while significantly cutting R&D time and costs. | We have established a Scientific and Technological Partners Network, counting more than 70 universities and research centers worldwide that collaborate with us to leverage their state-of-the-art in silico methodologies and transform them into innovative digital solutions that can help to design and assess new medical products. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Anil Srivastava | Open Health Systems Laboratory, Inc. | anil.srivastava@ohsl.us | 1400 Webster Street, Suite 307, Alameda, California 94501, CA | (1) In silico drug development to identify phytochemicals with anti-cancer properties; (2) physiological digital twin models; and (3) in silico clinical trials. | Collaborators to take the candidate molecules with in silico validation to development of integrative therapy. | TA3: In silico human physiology model |
| Cinzia Silvestri | Bi/ond | cinzia@biondteam.com | Delft, The Netherlands | Bi/ond is a Dutch biotech specializing in microelectronics and biology. * Biology: We focus on healthy and diseased skeletal and cardiac tissues, incorporating flow and electrophysiology. We offer a healthy skeletal model, a Duchenne muscular dystrophy model, and a healthy cardiac model, with more in development. Other applications: cancer-on-chip and vascularized kidney organoids. *Engineering: We integrate sensors and electrodes for real-time data monitoring and automation. | - We seek collaboration with companies focused on in silico models and data discovery methods to provide and enhance the data collected from our models. - We are interested in collaborating with companies specializing in lab automation to optimize our platform and protocols. - We aim to partner with providers of complementary organ-on-chip technologies to develop multi-organ systems. | TA2: Living systems tools for model development |
| Mariano Vazquez | ELEM Biotech | mariano@elem.bio | Barcelona, Spain | Current Research Focus Areas: ELEM focuses on the assessment of cardiac safety using supercomputer-based physiologically detailed, organ-scale human cardiac models that have proven to produce accurate estimations of concentration-QT interval prolongation using virtual humans. These models reproduce healthy and diseased phenotypes of male and females. Our cloud-based platform can be employed by any company to assess preclinically the QT-interval prolongation of their drugs. | What We Seek in Teaming Partners: We are looking for clinical, CROs or Pharma partners to share trial data for validation. We would also like to partner that produces PK/PD data to further enhance the in-silico platform accuracy. We are looking for In-vitro stem cell tissue models to work on translation to human function using our in-silico methods. | TA3: In silico human physiology model |
| Sofia Stathopoulos | InSilicoTrials | sofia.stathopoulos@insilicotrials.com | Trieste, Italy | InSilicoTrials is a Platform technology company dedicated to accelerating drug development through AI and advanced predictive technologies, operating under the framework of Good Simulation Practices (Springer Nature, 2024, Editors Viceconti and Emili). InSilicoTrials modeling and simulation AI solutions are developed in partnership with hundreds of leading research institutes worldwide and are powered by a unique network of over 50 global data providers. | Research Institutes, Data Partners, Drug Developers, Regulators and KOLs to streamline in silico solutions that de-risk and democratize drug development. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Rok Sosic | Stanford University | rok@cs.stanford.edu | Palo Alto, CA | We are developing AI models for virtual cells, where robust representations of cells and cellular systems under different conditions are directly learned from growing biological data across measurements and scales. We are also developing AI agents with a goal to speed up the pace of scientific discovery in biomedicine. | We are keen to work together with partners that can perform biological experiments. | TA3: In silico human physiology model |
| Nate Hughes | Icarus Therapeutics | nate@icarustx.ai | Bay Area, CA | ● Mission: Building the "match.com" of clinical trial enrollment ● Product: End-to-end technology platform matching principal investigators and patients directly ● Traction: On track for $150K revenue in 2024 ● Market Potential: The global clinical trials market was valued at $49.8 billion in 2022, with a projected CAGR of 5.8% from 2023 to 2030 ● Target Market: 1% capture of the $240 billion annual spend on patient recruitment would equal $2.4B | Looking for data scientists and epidemiologists | Product Sponsor: Novel drug development activity |
| John Clemmer | University of Mississippi Medical Center | jclemmer@umc.edu | Jackson, MS | Mathematical models of hypertension and cardiovascular renal diseases Validating virtual populations to replicate clinical trials and predict outcomes Advanced data analytics, data wrangling, and machine learning on large clinical datasets | Teams interested in modeling hypertension, kidney disease, or cardiovascular disease. | TA3: In silico human physiology model |
| Katie Hulse | Draper Labs | khulse@draper.com | Cambridge, MA | Draper Bioengineering seeks to leverage our 20+ years of expertise in custom MPS development to deliver extensive data sets derived from relevant human tissue models. Capabilities include the highest throughput platform available, in which we have demonstrated >12 different tissue types including liver, kidney, vascular, neural, lung, as well as multi-organ systems. Draper has employed these capabilities to execute solutions for multiple government, pharma and academic collaborators. | Draper is seeking partners with expertise related to TA1 and TA3 that complement our capabilities in developing high throughput MPS devices for data generation in TA2. Draper can help integrate TA1 and TA3 solutions based on extensive experience in software and algorithm development, data processing, systems integration, and large-program management. | TA2: Living systems tools for model development |
| Paul Stewart | Tranexamic Technologies | wpstewart7@gmail.com | Dallas, TX | We are developing a class of novel molecules as anticancer agents. | We would be interested in catalyst technologies that apply to our molecules based on our current understanding of their MOAs. | Product Sponsor, Novel drug development activity |
| Pooja Tiwari | ARNAV Biotech | pooja.tiwari@arnavbiotech.com | Atlanta, GA | ARNAV Biotech is developing next-gen mRNA vaccines and therapeutics against infectious diseases leveraging our platform technologies including CRISPR-Cas13, gene modulators and fusion inhibitors against viral infectious diseases. We are also expanding our portfolio to cancer and immune disorders. We have mRNA vaccines in pre-clinical development against influenza, Dengue, RSV and other viral infections and broad spectrum antivirals against RSV and influenza for infants and children. | Our expertise includes immune correlate development, assay development, vaccines and antiviral agents. We could also provide data (pre-clinical and in vivo mice studies) that could be used to train various in silico models from our current vaccine studies. We would like to collaborate with companies with expertise in in-silico ADME expertise. | Product Sponsor: Novel drug development activity |
| Thomas Hartung | Johns Hopkins Bloomberg School of Public Health | thartun1@jh.edu | Baltimore, MD | Over the last decade, the Johns Hopkins Center for Alternatives to Animal Testing has been embracing AI in toxicology, in parallel to other New Approach Methods (NAM). AI is a disruptive technology promising to solve some dilemmas in toxicology, such as throughput, costs and human relevance. Recently, we also combined AI with brain organoids to create Organoid Intelligence (OI), aka learning-in-a-dish. | For toxicology, AI promises better reporting, data retrieval, evidence integration, predictive toxicology of untested compounds & digital pathology. The prospects in better accuracy in human prediction, ethics & cost-effectiveness are enormous. Accelerated assessments with automated data analyses and real-time monitoring would give user-friendly prediction tools to democratize knowledge. AI empowers those involved in toxicology. We want to team up with like-minded groups to realize this vision. | TA1: Data discovery methods for predictive drug safety models, TA2: Living systems tools for model development, TA3: In silico human physiology model |
| Morgan Stanton | Opal Therapeutics | morgan@opaltherapeutics.com | San Francisco, CA | Therapeutic development for chronic gynecological disorders | Academic collaborator with a focus in female reproductive health | TA2: Living systems tools for model development |
| Sixue Zhang | Southern Research Institute | szhang@southernresearch.org | Birmingham, AL | Southern Research has an integrated platform to support the design-make-test-analyze iteration of drug discovery. Our platform leverages the latest artificial intelligence technology to aid the design of novel drug modalities. We also provide medicinal chemistry, structural biology, high throughput screening, bioanalysis, and various in vitro/in vivo assay support. We have a variety of projects covering oncology, infectious diseases, neurology, and other therapeutic areas. | We are looking for partners who would provide biology insights for our projects or collaborate with us on computational algorithm development. We also welcome any other potential collaborators who have drug discovery needs. | Product Sponsor: Novel drug development activity |
| Natalie Ma | Deep Origin | nma@deeporigin.com | South San Francisco, CA, CA | We build models and infrastructure to simulate living systems across scales, from atom-atom interactions to cell physiology, to test and filter drug candidates in silico. Some notable achievements: currently outperforming DiffDock, Schrodinger, and AlphaFold 3 on various problems in drug development. | High throughput experiment dataset generation and validation of predictions, particularly for enzymatic function, small molecule-to-protein or protein-to-protein interaction, cell survival, and/or gene or protein expression assays. Additional Product Development partners. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Kevin Luebke | SRI International | kevin.luebke@sri.com | Menlo Park, CA | AI/ML modeling of drug/biology interactions with sparse, multimodal training data; extensive experience with preclinical ADME-Tox animal studies and alternatives, including microphysiological systems | Product sponsor for novel drug development activity; additional alternatives to preclinical animal studies | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Rene Anand | Neurxstem Inc | rene.anand@gmail.com | Heath, OH | Neurxstem Inc. is a US-based, predictive and precision genomic medicine company dedicated to finding innovative solutions to the most challenging human brain diseases. Neurxstem has patented a novel, first-in-class Neural Organoid Platforms that closely mimics the human brain. Proprietary “big data” portfolios, grounded in marketable predictive biomarkers allows early diagnostic and precise therapeutics. | Teaming partners interested in drug discovery for brain diseases or AI/ML based drug discovery with licensable big data. | TA2: Living systems tools for model development |
| Vrad Levering | Triple Ring Technologies | vlevering@tripleringtech.com | Newark, CA | Triple Ring Technologies is a leading partner in developing science-driven products in medtech that incorporate AI and assay-based solutions. Our interdisciplinary team, including PhDs and industry experts, excels at collaborating with academic researchers to advance technologies up the TRL scale and to market. Through our deep understanding of microfluidics, optics, biology, systems, modeling, and assay development we can help develop your technology for commercial release. | We have a strong track record of engaging with ARPA-H, both as a subcontractor and as a prime. We offer product prototyping (ISO 13485 certified) and software development (including AI pipelines and ISO 62304 conforming) services. We are looking for an academic or startup partner that is developing technologies primarily in TA2 and TA3. | TA1: Data discovery methods for predictive drug safety models |
| Ronjon Nag | R42 Group | ronjon@r42group.con | Palo Alto, CA | We are working creating a vaccine for aging using computational techniques. | Clinical trial expertise | Product Sponsor, Novel drug development activity |
| Shuxing Zhang | University of Hawaii Cancer Center | shuxing@hawaii.edu | Honolulu, HI | We are University of Hawaii Cancer Center. We have strong programs of Cancer biology, AI-based drug discovery and development, clinical translational research, and population-based cancer science. | Although we have several of our own drug discovery and development for translation to the clinic, we are also open product sponsors to work with us and use/validate our ADME-Tox models for their animal-free IND-enabling studies for regulatory submission, especially for patient population of native Hawaiians, pacific islanders, Asian, and Japanese. | Product Sponsor, Novel drug development activity |
| David van Dijk | Yale University | david.vandijk@yale.edu | New Haven, CT | Our research builds a virtual in silico human by harnessing Cell2Sentence (C2S) to simulate cellular interactions and predict physiological responses. C2S transforms gene expression into interpretable text, facilitating insights into cell identity, interactions, and responses to perturbations. This approach creates human-like models reflecting real-time biological dynamics, offering a foundational tool for precise drug safety testing and understanding complex human biology without animal models. | We seek partners with expertise in living system models or drug development, especially those creating organoid or tissue systems to validate in silico predictions. Our goal is to integrate C2S with ex vivo models to simulate cellular responses to drugs, enhancing accuracy in drug safety and efficacy predictions. Such collaboration would advance our virtual human model, optimizing predictive power for human biology and supporting precision in drug testing. | TA3: In silico human physiology model |
| Young-Jae Cho | Seoul National University Bundang Hospital | lungdrcho@snu.ac.kr | Seongnam | We're doing new approach methodologies such as various microphysiological systems including human tissue derived organoids, esp. respiratory system. We're aiming to explore how to evaluate the efficacy of inhaled therapeutics or toxicity of aerosol toxin using our complex in vitro system. | There is little in silico model about mimicking respiratory system, so we try to find and meet collaborators to do research about in vitro-in vivo correlations. | TA2: Living systems tools for model development, TA3: In silico human physiology model, TA1: Data discovery methods for predictive drug safety models |
| Brennan Murphy | Certara | brennan.murphy@certara.com | Washington DC, DC | With our 2300 global customers, Certara is advancing precision medicine through in silico modeling, quantitative systems pharmacology, and AI-driven drug development platforms. Our research focuses on enhancing drug safety, predicting pharmacokinetics, and optimizing clinical trials using physiologically-based models. We aim to drive faster, safer, and more cost-effective drug discovery and regulatory submissions across a wide range of therapeutic areas. | We seek partners who bring expertise in high-throughput screening, data analytics, computational biology, and regulatory science. Our ideal collaborators share a commitment to innovation in drug development, advancing data-driven insights, and enhancing translational science to meet the unmet needs in precision therapeutics. Together, we can accelerate impactful solutions in healthcare. | TA3: In silico human physiology model, TA1: Data discovery methods for predictive drug safety models |
| Mohammed Moinul Islam | Somru BioScience Inc | moin@somrubioscience.com | Charlottetown, Prince Edward Island, Canada | Somru BioScience is an innovative biotechnology company specializing in drug development services for large-molecule biotherapeutic companies. We have developed a model-informed drug development platform that accelerates clients’ progress. Our research focuses on in silico predictive immunogenicity and the development of a digital Contract Research Organization (CRO) platform to enhance drug development efficiency. | We are seeking product sponsors and IT companies with expertise in artificial intelligence and machine learning. | TA2: Living systems tools for model development, TA3: In silico human physiology model |
| Ashish Agarwal | Solvuu | aa1@solvuu.com | New York City, NY | We have developed: 1) an operating system for managing and integrating chemical and biological data with assured quality and security, 2) a mathematical language for unified scientific knowledge representation across modeling frameworks such as linear algebra, calculus, statistics, ontologies, markup languages, and 3) a neuro-symbolic AI framework for learning predictive, explainable models in drug discovery, focusing on target identification and safety/efficacy profiles. | We are looking for partners with expertise in developing human-relevant living system models (ex vivo, in vitro, CIVMs) to generate data that can help validate our in silico drug safety models. They should have a need for partnering with a provider on data engineering solutions and bioinformatics/cheminformatics analytics. | TA1: Data discovery methods for predictive drug safety models |
| Tamer Mohamed | Baylor College of Medicine | tamer_1977@hotmail.com | Houston, TX | Our laboratory established a novel system for long-term culture of human and pig heart slices and efficiently demonstrated the efficacy of new cardiac regenerative therapies in such pre-clinical models (Ou et al., Circulation Research, 2019, Miller et al., Nature Communications Biology, 2022). This technology has opened a new avenue of research to explore pathophysiological mechanisms and toxicities in primary pig and human heart tissues. | As a partner in the HESI cardiac safety committee, we generated a dose-response curve for 13 different cardiotoxins on hiPS-CMs and human heart slices with over 15 parameters. We are looking to partner with experts in silico and AI prediction for cardiotoxicity to leverage our data and create an AI model for cardiotoxicity prediction. | TA2: Living systems tools for model development, Product Sponsor: Novel drug development activity |
| Md Nurunnabi | University of Mississippi | bsnabi@olemiss.edu | Oxford, MS | Drug formulation and advanced delivery strategies for therapeutics and diagnostics agents | We are looking to partner with individual expertise on cell engineering to enable production of specific therapeutic protein production upon administration. | TA2: Living systems tools for model development, Product Sponsor: Novel drug development activity |
| Wengong Jin | Northeastern University | w.jin@northeastern.edu | Boston, MA | My lab focuses on geometric and generative AI models for drug discovery. We build innovative AI tools to model toxicity by predicting human cell viability after treatment of a compound. Our models are trained on large-scale cell painting data from JUMP consortium that measures cell morphology and cell viability data from in-house human primary cell viability screens. Using these tools, we have successfully discovered new antibiotic candidates with low toxicity and high efficacy. | We are looking for product sponsors to pursue preclinical studies of AI-designed drug candidates | TA1: Data discovery methods for predictive drug safety models |
| James Glazier | Indiana University | jaglazier@gmail.com | Bloomington, IN | CompuCell3D (CC3D) open-source software provides advanced, flexible support for the construction and execution of multicellular agent-based computer simulations of tissue organization, homeostasis and failure and of organoids and cell cultures. CC3D has been used extensively in developmental toxicology, drug discovery, basic biology and tissue engineering. CC3D integrates easily with imaging, PBPK and subcellular network modeling tools and as part of drug discovery and development workflows. | We are looking for experimental, clinical, bioengineering, and drug and therapy-discovery partners interested in integrating multicellular agent-based modeling to accelerate their workflows and for partners interested in building multicellular models of specific organ systems, developmental processes, diseases or therapies. We have extensive experience working with large-scale interdisciplinary teams in simulation development and application. | TA3: In silico human physiology model |
| Jackson Brougher | Doloromics | jackson@doloromics.com | Menlo Park, CA | Doloromics has paired in silico cell-cell interaction modeling with ex vivo human DRG 3D cultures to better predict and screen therapeutic efficacy. | Ideally looking to pair our efficacy capabilities with organization capable of providing non-neuronal safety screens. We can measure cyto-and-neurotoxicity. | TA2: Living systems tools for model development, TA3: In silico human physiology model, TA1: Data discovery methods for predictive drug safety models, Product Sponsor: Novel drug development activity |
| Abhinav Bhushan | Illinois Institute of Technology | abhushan@iit.edu | CHICAGO, IL | We offer - novel microfluidic oxic-anoxic interface to support gut bacteria with colon - direct and indirect drug metabolism by gut bacteria - experimental coupling to liver/sinusoid - compartment modeling of PK - Experience working with DARPA E.g., we have leveraged the microfluidic platform with PK modeling to show that certain species of gut bacteria increase sulfasalazine absorption by several fold (lower efficacy), reflective of clinical observations. Publications https://t.ly/TUgIe | TA1 ad TA3 partners Multi-scale human data Scaling in vitro systems Project sponsors/partners | TA2: Living systems tools for model development, TA3: In silico human physiology model |
| James Morton | Gutz Analytics | jamie@gutzanalytics.com | Rockville, MD | Our research focuses on developing AI-powered digital twins to predict patient treatment responses, enabling diagnostics and therapeutic innovation. Key areas include longitudinal, multi-omics data integration (microbiome, metabolomics, proteomics), interpretable AI for causal biomarker discovery, and patient stratification to identify responsive populations. We specialize in working with small cohorts, enhancing precision in treatments for targeted patient groups. | We seek a product sponsor specializing in small molecule therapeutics with validated drug targets and lead molecules, ready for IND-enabling data generation using CATALYST Phase I technologies. Ideal partners have human/animal MPS, organoids, instrumented tissues, or ex vivo model capabilities for TA2. A focus on immunotherapy is a strong plus, aligning with our team’s expertise and case studies in immunotherapeutic applications. | TA3: In silico human physiology model, TA1: Data discovery methods for predictive drug safety models |
| Lei Xie | CUNY & Weill Cornell Medicine | lxie@iscb.org | New York City, NY | One of challenges in applying AI to CATALYST is out-of-distribution (OOD) problem where unseen testing data is significantly different from training data. We have developed several AI/ML methods to improve generalization, trustworthiness, and interpretability under an OOD scenario, and have successfully applied them to predicting genome-wide drug-target interactions, translating in vitro drug responses into patient clinical outcomes, and disentangling biological and technological cofounders. | We are looking for collaborations using high-throughput living systems tools (TA2) for model development. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Jessica Mustali | Misogi Labs | jessica.mustali@misogilabs.com | San Francisco, CA | At Misogi Labs we have developed a predictive, physics-infused AI platform for small molecules ADME/PK optimization. At the heart of it is Miso-5D, a groundbreaking large model pre-trained on multi-modal, physics-driven data, including 4D molecular conformations and QM properties across millions of molecules. By overcoming barriers in data scarcity, model training, and computational power, we've developed Miso-pk, our SOTA model for predicting small molecule pharmacokinetics. | We are interested in collaborating with data providers, labs with high-throughput data generation capabilities, or validation of AI predictions of ADME-Tox/PK. We are also interested in collaborating with TA3 teams in integrating predictions with PBPK models. (TA1+TA2+TA3) | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Raghu Rayannagari | Singularity IT Solutions LLC | raghu@singularityitsolutions.com | West Chester, PA | Singularity IT Solutions specializes in digital transformation, AI/ML applications, data engineering, and cloud migrations across multiple sectors, including healthcare, education, and federal government. Our focus is on scalable data management, real-time analytics, and operational automation. Our projects often involve building data pipelines, modernizing legacy systems, implementing machine learning models for predictive insights, and ensuring secure cloud infrastructure. | For ARPA-H’s CATALYST program, we seek partners with complementary technical expertise, particularly in bioinformatics, health data analytics, and advanced machine learning that supports innovative healthcare data applications in TA2, TA3 and Product Sponsors. | TA1: Data discovery methods for predictive drug safety models |
| Benjamin Ringler | TissueTinker | ben.ringler@tissuetinker.com | Montreal | TissueTinker is developing a 3D bioprinted tumor model library for preclinical cancer drug screening. Our platform provides a high-throughput and tunable system for co-culturing tumor spheroids/organoids to provide representative tumor microenvironments. Using our system we aim to accelerate preclinical drug development while also addressing data gaps associated with differences between patients of different ages, ethnicities, and comorbid conditions. | We are seeking partners TA3 partners with experience in the development of AI/ML PK/PD modeling technologies in need of TA2 living system models. | TA2: Living systems tools for model development |
| Maximilian Grill | Ebenbuild | grill@ebenbuild.com | Munich, Germany | We have developed a conceptually new in silico model for pulmonary drug delivery that, for the first time, allows to predict the locally delivered dose throughout the entire respiratory system, including the alveolar region and the full tree of conducting airways. The model is physics-based, patient- specific and disease-specific, and efficient enough to simulate large cohorts of these personalized digital twins. Preprint: https://arxiv.org/abs/2307.04757. Ebenbuild is a spin-off from TU Munich. | We are looking for partners covering TA2 and/or TA1 for orally inhaled drug products (OIDPs), as well as Product Sponsors in this field. As a team, we aim to achieve the goals of the CATALYST program with a unique solution tailored to the specific challenges of OIDPs. | TA3: In silico human physiology model |
| Greeshma Agasthya | Georgia Institute of Technology | greeshma@gatech.edu | Atlanta, GA | Current research focus areas are: (1) Developing multiscale digital twins for personalization of radiopharmaceutical therapy, and theranostics, (2) modeling and simulations to assess novel radiopharmaceuticals for cancer treatment, and (3) developing AI frameworks to model patient anatomy, physiology, computational fluid dynamics, and tumor response to treatment. | Clinical data partners, drug manufacturers, clinical scientists | TA3: In silico human physiology model |
| Ben Kogan | Arctop | bk+1@arctop.com | Los Angeles, CA | Arctop focuses on developing brain-computer interface (BCI) technology to monitor cognitive and emotional states in real time. Our expertise includes neurophysiology, signal processing, and AI for non-invasive brain decoding. We apply advanced neural sensing and computational models to healthcare, enabling insights into brain activity patterns that improve diagnostics, therapeutic interventions, and training in clinical and applied settings. | We seek partners with expertise in drug development, in silico modeling, pharmacokinetics (ADME), and human physiology simulation. Ideal collaborators have experience in building predictive safety and efficacy models or regulatory pathways for novel therapeutics. We value organizations focused on reducing drug failure rates, enhancing patient safety, and advancing computational methods in preclinical drug testing to align with the ARPA-H CATALYST program goals. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model |
| Andrew Larsen | Inductive Bio | andrew@inductive.bio | New York, NY | Inductive Bio’s ADMET Machine Learning (ML) platform helps scientists avoid unnecessary and costly in vitro and in vivo assays by providing high-performing in silico predictions. Our state-of-the-art ADMET models are trained on hundreds of thousands of data points from proprietary biopharma consortium programs, in-house data generation, and carefully curated public sources. Inductive is helping dozens of drug programs design high-quality compounds and reduce time to key milestones. | We are seeking product sponsors to utilize our predictive ADMET models in IND-enabling studies. Additionally, we are seeking TA2 collaborators who can provide relevant in vitro and in vivo toxicity data. | TA3: In silico human physiology model, TA1: Data discovery methods for predictive drug safety models |
| Pooja Tiwari | ARNAV Biotech | pooja.tiwari@arnavbiotech.com | Atlanta, GA | ARNAV Biotech has several lead candidates in the infectious disease area including small molecule/biologics, mRNA based vaccines, therapeutics, self-replicating RNA vaccines and therapeutics, and, trans-replicating RNA drug products including antibodies. Our research focus is on viral pathogens such as influenza, RSV, Dengue and Hepatitis. As a drug development company, we often face the challenges of high cost and time associated with the animal based pre-clinical testing. | We can support any lead organization in the TA2 in testing the performers teams' OoC or lungs on chips models with our products. We could provide testing, assay development and ex-vivo, in vitro support for various OoC models. We could also be the product sponsor for the performers and help in filling data gaps in safety and toxicity, and enhance pre-clinical testing outcome, provide multi-omics read outs of the ADME assays and endpoint analysis, and biomarker identification in ex-vivo models | TA2: Living systems tools for model development, Product Sponsor: Novel drug development activity |
| Srboljub Mijailovich | FilamenTech, Inc. | smijailo@gmail.com | Boston, MA | FilamenTech focuses on in-silico modeling of cardiac, skeletal, and lung muscle behavior using MUSICO platform that integrates genomics, proteomics, and biophysics across scales. MUSICO enables quantitative study of disease pathways, efficacy and safety testing of novel drugs, disease progression tracking, and reduces reliance on animal and human trials. By translating data across multiple scales and species, MUSICO provides critical insights into muscle function and personalized treatments. | We seek partners specializing in living systems tools, product sponsorship, and data discovery for predictive drug safety, especially cardiac toxicity. We are interested in collaborating with clinical researchers, CROs, and pharma partners to share trial and PK/PD data, enhancing the accuracy of our MUSICO platform. We also welcome AI and computational experts to co-develop advanced predictive models that support in silico testing and reduce preclinical and clinical trials. | TA3: In silico human physiology model |
| Heidi Haikala | Solid-IO @ University of Helsinki | heidi.haikala@helsinki.fi | Helsinki | Solid-IO is a pioneering health science deep tech company spinning out from the University of Helsinki at the end of 2024. We have developed an immunocompetent tumor-on-chip platform, designed to guide personalized cancer drug testing in the future. Our platform is designed to accelerate functional drug testing to identify the most effective treatments for each patient. Our team also brings in expertise in single cell technologies and spatial biology. | We are looking for teaming partners related to data analytics and AI, as well as as pharmaceutical companies to co-develop our platform with. | TA2: Living systems tools for model development |
| Casey McPherson | Chrysalis Genetics | casey@chrysalisgenetics.com | Austin, Tx | Houston, Tx | Boston, Ma, TX | We are a precision medicine commercial company scaling the development and commercialization of genetic medicines for ultra rare diseases. Founded by builders of Genzyme and Everlum Bio, We develop medicines with AI/ML tools to speed up the process of development, and use wearable technologies to reach clinical endpoints faster for each patient. We have a pipeline of antisense oligonucleotide therapeutics, with our lead candidate going into the clinic in 2025. | We are looking for partners skilled in computational biology, AI, organoid HTS, and wearable technologies. | Product Sponsor: Novel drug development activity, TA1: Data discovery methods for predictive drug safety models |
| Lawrence Vernetti | University of Pittsburgh - Pittsburgh, PA | Vernetti@pitt.edu | Pittsburgh, PA | We have developed a biomimetic liver MPS model to improve PBPK modeling, assess hepatotoxicity, and evaluate drug efficacy in MASLD. Our liver model has high concordance with clinical findings and has been functionally integrated with models of the pancreas, kidney, blood-brain barrier, and intestine through collaborations. We built a database to assemble and disseminate meta data, raw and processed data, experimental design and analysis for human organ models to predict safety and efficacy. | Our expertise in biomimetic liver models makes us an ideal partner for teams specializing in non-liver TA2 models and those with expertise in TA1 and TA3. Our lab can manage any organ data as well as generate experimental intrinsic clearance, metabolite identification, and hepatotoxicity data, which can be compared with existing clinical data to validate in silico models for predictive PBPK and toxicity. | TA2: Living systems tools for model development |
| Nira Barlow | GNQ Insilico | nira.barlow@gnqinsilico.com | Pleasanton, CA | Our multi-omics in silico platform transforms and de-risks drug development to optimize clinical trials and accelerate drug market entry. Using our data driven, multi-agentic AI approach, we model human biology as an interconnected dynamic system to reveal emergent properties in our Human Digital Twins. These digital representations of real patient’s health data inform our AI and quantum models to accurately simulate, predict, and optimize drug responses for personalized treatments. | Partners with high-throughput multi-omics screening capabilities for advanced organoid, human MPS, instrumented tissues, and ex vivo models. Our automated multi-omics (genomic, transcriptomic, proteomics, metabolomic, epigenetic) and clinical platform provides the necessary infrastructure for storing and analyzing complex biological data for TA2. Open to TA3 collaboration to advance physiological models through integration with our proprietary genomics and human physiology-driven AI models. | TA1: Data discovery methods for predictive drug safety models, TA3: In silico human physiology model, Product Sponsor: Novel drug development activity |