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medRxiv

OpenScientist: evaluating an open agentic AI co-scientist to accelerate biomedical discovery

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  • March 18, 2026
  • Justin Reese, et al., Lawrence Berkeley National Laboratory
Topic/Product:
CNS Disease Panel 120, Immunology, Inflammation Panel 250
Disease Area:
Aging
Sample Type:
Plasma

Abstract

Background Advances in medicine depend on analyzing large and complex data sources, but discovery is partly constrained by the limited time and domain expertise of human researchers. Agentic artificial intelligence (agentic AI) can accelerate discovery by automating components of the scientific workflow, including information retrieval, data analysis, and knowledge synthesis.

Aim OpenScientist, an open-source agentic AI co-scientist, aims to accelerate biomedical discovery by semi-autonomously investigating scientist-defined queries and generating clinically relevant, verifiable scientific insights.

Methods Domain experts evaluated OpenScientist for novel discoveries in four clinical case studies: (1) a prespecified analysis in a community-based Alzheimer’s disease biomarker cohort, (2) unsupervised modeling for plasma proteomic survival prediction, (3) hypothesis investigation in single-cell transcriptomic data from neurons with neurofibrillary tangles, and (4) hypothesis generation with validation in a multiple myeloma dataset with a randomized negative control.

Results OpenScientist completed analyses in minutes that otherwise would take weeks to months of human time and expertise. It identified %ptau217 as the best predictor of amyloid PET status, generated a plasma proteomic survival model with performance comparable to published models, proposed a mechanism linking tau pathology to altered lysosomal acidification, and generated multiple myeloma hypotheses that were validated in an external cohort while distinguishing true signal from randomized controls.

Conclusion OpenScientist demonstrates that open, auditable, agentic AI can support real-world clinical research by generating hypotheses, executing analyses, and discovering insights from complex datasets.

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Authors & Affiliations

Kaleigh F. Roberts* ¹²¹⁶, Zachary B. Abrams* ³¹⁶, Luca Cappelletti⁴, Mahdi Moqri⁵, Nicholas Heugel²⁶¹⁶, J. Harry Caufield⁷, Mathieu Bourdenx⁸¹⁶, Yan Li⁶, Jineta Banerjee⁹, Luca Foschini⁹, Diego Galeano¹⁰, Nomi L. Harris⁷, Melody Li²⁶, Kejun Ying¹¹¹², Justin A. Melendez²⁶¹⁶, Nicolas R. Barthélemy²⁶, James G. Bollinger²⁶, Yingxin He²⁶, Vitaliy Ovod²⁶, Tammie L. S. Benzinger¹³, Shaney Flores¹³, Brian A. Gordon¹³, Adegoke A. Ojewole¹⁶, Mukta Phatak¹⁴¹⁶, Donald L. Elbert¹⁵¹⁶, Sarah Biber³⁶¹⁶, Eric C. Landsness⁶¹⁶, Christopher J. Mungall⁷, Randall J. Bateman# ²⁶¹⁶, and Justin T. Reese# ⁷¹⁶

¹ Department of Pathology & Immunology, Washington University in St. Louis, St. Louis, MO, USA
² Tracy Family SILQ Center, Washington University in St. Louis, MO, USA
³ Institute for Informatics, Data Science, and Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
⁴ Department of Biology, University of Fribourg, Fribourg, Switzerland
⁵ Department of Medicine, Harvard Medical School, Boston, MA, USA
⁶ Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
⁷ Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
⁸ UK Dementia Research Institute at University College London, London, UK
⁹ Sage Bionetworks, Seattle, WA, USA
¹⁰ Electronics and Mechatronics Department, Facultad de Ingenieria, Universidad Nacional de Asuncion, Paraguay
¹¹ Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
¹² Institute for Protein Design, University of Washington, Seattle, WA, USA
¹³ Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
¹⁴ The 10,000 Brains Project, Oakland, CA, USA
¹⁵ Department of Neurology, University of Washington, Seattle, WA, USA
¹⁶ Consortium for Biomedical Research & AI in Neurodegeneration (C-BRAIN)

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Steve Williams, MD, PhD

CSO

Dr. Willams serves as the company’s Chief Scientific Officer. He was previously Chief Medical Officer at Standard Biotools and at SomaLogic where he pioneered the discipline for discovery and validation of predictive, diagnostic and prognostic models using machine-learning applied to large-plex proteomics. 20 such tests were used for drug characterization, safety and efficacy when incorporated in clinical drug trials at Pharma/Biotech and 17 different multivariate tests were validated and translated into regulated healthcare uses. Prior to SomaLogic, Dr. Williams was at Pfizer in the UK and the USA as a clinical triallist in Translational Medicine, and subsequently as VP, Global Clinical Technology. He sat on the National Advisory Council for the National Institute of Biomedical Imaging and Bioengineering, the Executive Committee for the FNIH Biomarkers Consortium, and worked with FDA and PhRMA on developing evidentiary standards for biomarker qualification. Dr. William’s medical training was in London, at Charing Cross and Westminster Medical School, followed by a PhD in medicine/physiology at the same institution and training in Radiology at the University of Newcastle Upon Tyne. Steve is co-inventor on 26 proteomics patents and author/coauthor on multiple foundational proteomics manuscripts.

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Justin McAnear

CFO

Mr. McAnear serves as the company’s Chief Financial Officer. He brings over 25 years of operational and financial leadership experience across various sectors and was instrumental in taking 10x Genomics public in 2019, serving as its CFO for over five years. Mr. McAnear served for over 3 years as Tesla’s VP of Worldwide Finance and Operations, supporting landmark initiatives such as the Model X and Model 3 launches and Solar City acquisition.  He also held various roles at Apple and J&J earlier in his career and served as a naval officer and aviator for over 9 years.