Based Research Foundation studies how human-relevant in-vitro systems can help evaluate AI-discovered drug candidates before scarce clinical trial capacity is committed.
Story reel
How candidate ranking changes when evidence quality is treated as a decision gate instead of a decorative metric.
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A practical framework for moving from AI-generated hypotheses to a shortlist that can support translational planning.
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Why methods, assumptions, and benchmark rationale must be visible before candidates enter expensive downstream work.
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The nonclinical layer should reduce uncertainty, not create new ambiguity in candidate progression decisions.
Read noteHow candidate ranking changes when evidence quality is treated as a decision gate instead of a decorative metric.
Read researchA practical framework for moving from AI-generated hypotheses to a shortlist that can support translational planning.
See programsWhy methods, assumptions, and benchmark rationale must be visible before candidates enter expensive downstream work.
About the nonprofitThe nonclinical layer should reduce uncertainty, not create new ambiguity in candidate progression decisions.
Read noteAI systems can nominate far more candidates than clinical programs can responsibly test. The hard problem is choosing which candidates deserve costly biological and patient-facing studies.
Read the research approachOrganoids and microphysiological systems can help expose weak biological claims early and make candidate prioritization more legible.
ProgramsAI discovery expands the candidate list. Clinical translation narrows it. The work in between needs better public methods, not another slogan.
About the nonprofitA note on the difference between useful preclinical signal and decorative biological complexity.
Research update · Apr 15Read newsThe field needs better filters between model output and the clinical pipeline.
Program note · Apr 10Read blogNonprofit status, legal details, and contact information are in the About section.
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