Discovery-to-trial decisions built on measured data and published rules. Every claim cites a real source — or the system abstains. No generative chemistry, no invented affinities, no black-box scores.
The same neuro-symbolic core behind Ardia’s reimbursement engine, pointed upstream at the discovery-to-trial decision layer — deterministic rules + real-database retrieval + guarded reasoning + human-in-the-loop. No new trust model required.
Every output runs through TARA’s Scholar tier — plan → retrieve from a named public source → reason → cite — with a source chip on each claim and a tamper-evident trace (query, source, version, timestamp, reviewer). The non-generative rule is enforced in the code path: no measured evidence means the system abstains rather than inventing an answer.
For a biomarker-defined program (EGFR, ALK, BRAF, MSI-H/TMB, HLA-B, DPYD) it maps the required test to FDA companion-Dx approvals, NCCN/CPIC guidance, and the concrete Medicare coverage path (MolDX Z-code, applicable LCD/NCD, CPT/PLA codes) — the direct bridge from discovery to the reimbursement business Ardia already owns.
Ranks candidate targets on real human genetic and genomic evidence from Open Targets (association scores, ClinVar/GWAS support, tissue specificity, tractability) — never intuition or generated hypotheses. Targets with weak or absent human evidence are flagged “insufficient evidence,” not scored optimistically.
Retrieves compounds with measured activity against a target from ChEMBL — real IC50/EC50/Ki, mechanism of action, and approved-drug status — rather than inventing molecules. If no measured bioactivity exists it abstains and says so; it never fabricates a structure or an affinity.
Surfaces measured ADMET and pharmacology (ChEMBL properties, CYP metabolism, PGx and drug–drug-interaction flags) plus published, rule-based structural alerts (PAINS, Brenk, Lipinski). Any predicted value is labelled predicted and visually separated from measured — never a black-box “toxic/safe” verdict.
Pulls the live competitive and feasibility picture from ClinicalTrials.gov — who is running trials for a target/indication, their endpoints, eligibility, enrollment and sponsors — each cited to an NCT id. Supports go/no-go and trial design; shows only real registered trials and makes no efficacy prediction.
Most “AI drug discovery” sells the parts that hallucinate. These are the capabilities we deliberately exclude — because a claim you can’t cite is a claim we won’t ship.
A single fully-grounded example on real public data — every value below was retrieved live from ChEMBL, ClinicalTrials.gov and PubMed and links back to its source. It illustrates the method, not a novel discovery or an efficacy claim.
| Target | EGFR — ChEMBL target CHEMBL203, UniProt P00533 (single protein, human) ChEMBL → |
| Drug | Osimertinib (Tagrisso / AZD9291) — ChEMBL CHEMBL3353410, max phase 4, first approval 2015 ChEMBL → |
| Mechanism | Irreversible, mutant-selective EGFR inhibitor (measured bioactivity curated in ChEMBL) PMID 24893891 → |
| Developability | MW 499.62 · ALogP 4.51 · HBD 2 · HBA 8 · PSA 87.55 Ų (ChEMBL calculated) → passes Lipinski Ro5 & Veber ChEMBL → |
| Active trials | NCT04181060 (osimertinib ± bevacizumab, Ph 3) · NCT07738172 (Ph 3) ClinicalTrials.gov → |
| ⚖ Abstained | Open Targets EGFR–NSCLC association score was unavailable at query time — the system returned “insufficient evidence” rather than inventing a score. |
Molecular descriptors are ChEMBL calculated properties (from structure), clearly separated from measured bioactivity. Illustrative of the governed method on real public data — not a treatment recommendation.
Rule set (each verified to its primary publication): Lipinski Ro5, Veber, Egan, Ghose, Congreve Ro3, ligand efficiency (LE/LLE), PAINS & Brenk structural alerts, the Bowes 2012 44-target secondary-pharmacology safety panel, and hERG / ICH S7B cardiac-repolarization assessment.
This is a design/roadmap capability for a pre-revenue company — built on the reasoning core, guardrails and cite-or-abstain that are real today. It feeds directly into precision medicine and the TARA governance the whole platform runs on.
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