Master Orchestrator
Wake the foundry for a daily scan, force a long-horizon self-correction cycle, convene multi-agent debates and cancel running tasks.
Daily scan
Scans the newest 7 days of PubMed and trial updates, sets its own goal and runs the full pipeline.
Self-correction
Reviews failures, scores and bias, writes adaptations to memory, retires stale lessons and proposes goals.
Resolve a debate
Proponent vs skeptic over live PubMed evidence, arbitrated by the orchestrator.
The foundry exhibits a critical pattern of generating mechanistically innovative but clinically premature hypotheses. All recent outputs achieved 'revise' verdicts with moderate novelty (58-71) but alarmingly low confidence (33-41) and rigor (36-42), alongside persistent bias flags (10-13 per hypothesis). This reveals three systemic failures: (1) Insufficient evidence triangulation - agents propose complex multi-target interventions from single-paper mechanistic insights without validation convergence; (2) Safety-blind optimization - drug_screener prioritizes novelty over geriatric pharmacovigilance, proposing hepatotoxic/cardiotoxic agents for fragile populations; (3) Incomplete genetic contextualization - hypotheses ignore epistatic interactions between TREM2, ApoE, and BIN1 variants that may reverse intervention effects. The foundry is operating in 'speculative research mode' rather than 'translational validation mode'. Current strategy lessons address symptoms but don't enforce structural constraints on hypothesis generation pipelines.
Underperforming - consistently passing hypotheses with <45 rigor and confidence scores. Validation criteria are too permissive for mechanistic complexity. Needs upgraded statistical thresholds: require ≥3 independent corroborating studies for novel mechanisms, minimum confidence 60 for translational claims, and mandatory preregistered replication search.
Misaligned priorities - selecting repurposing candidates based on target engagement without geriatric safety profiling. Missing critical filters: polypharmacy interaction databases, age-stratified adverse event analysis, and organ reserve requirements. Needs integration with FDA adverse event reporting system (FAERS) for elderly-specific toxicity patterns.
Identifying but not blocking biased hypotheses - flagging 10-13 issues per output without enforcement. Bias detection should gate hypothesis advancement: >8 flags should trigger mandatory revision cycles before orchestrator review. Needs escalation authority.
Surface-level evidence synthesis - connecting published findings without probing for failed replications, retracted papers, or clinical trial graveyards. Requires access to ClinicalTrials.gov results database, PubPeer comments, and preprint contradiction alerts to identify mechanistic controversies.
Adequate performance but lacks validation roadmap integration. Biomarker proposals should include assay availability, normative data requirements, and regulatory precedent (FDA/EMA qualified biomarkers). Needs commercial viability assessment.
Generating complex multi-node models without sensitivity analysis. Should quantify which pathway connections are well-established (>10 papers) vs. speculative (<3 papers) and propagate uncertainty through models. Needs Bayesian confidence weighting.
Designing protocols without feasibility constraints. Missing enrollment rate projections, site capacity analysis, and competing trial landscape assessment. Should integrate CenterWatch data on typical AD trial accrual rates and failure modes.
Functioning adequately - no failures reported. Could enhance value by proactively identifying data gaps that limit hypothesis testing before full research cycles complete.
Completed task but impact unclear. Should provide conflict-of-interest screening, institutional review board template compatibility, and data-sharing agreement precedents to accelerate partnerships.
Successfully coordinating workflow but not enforcing quality gates. Should implement stage-gate process: preliminary hypotheses must pass confidence >50 threshold before resource-intensive drug screening and trial design. Needs decisional authority to halt low-confidence tracks.
- Implement mandatory evidence strength scoring: literature_bridger must classify each mechanistic claim as 'established' (≥5 independent labs, ≥3 species), 'emerging' (2-4 studies, ≥1 human data), or 'speculative' (<2 studies, in vitro only). Hypothesis_validator rejects translational proposals built on >40% speculative mechanisms. This forces foundry toward incremental validation rather than speculative leaps.
- Activate elderly-specific safety veto: drug_screener must query age-stratified adverse events (≥65 years) from FAERS and label candidates as 'geriatric-suitable', 'geriatric-caution', or 'geriatric-prohibitive' based on hepatotoxicity, orthostatic hypotension, falls risk, and polypharmacy interactions. Trial_optimizer auto-excludes 'prohibitive' agents and mandates intensive monitoring + DSMB for 'caution' tier.
- Enforce genetic power analysis: trial_optimizer must calculate sample size for genotype-stratified endpoints (TREM2 R47H, ApoE ε4 homozygotes, BIN1 risk variants) with minimum 80% power to detect 30% effect modification. Protocols without adequate genetic representation are flagged 'underpowered' and returned for redesign or biomarker enrichment.
- Create replication verification checkpoint: Before hypothesis_validator approves novel mechanisms, literature_bridger must search ClinicalTrials.gov for terminated trials testing similar approaches, PubPeer for post-publication critiques, and preprint servers for contradictory findings. Document 'mechanism controversy score' (0-100) based on replication failures and expert disagreement.
- Establish bias escalation protocol: bias_detection agent outputs now gate progression - hypotheses with >8 flags enter mandatory revision loop with specific remediation requirements (add female-predominant cohorts, include diversity statement, adjust for comorbidity confounds). Only after bias count <8 does hypothesis advance to trial_optimizer.
- Retire lesson c03739e6-debc-4551-9f89-5939793430e0 into structural requirement: genetic stratification is no longer a 'lesson learned' but a hard constraint enforced by trial_optimizer validation rules. Convert from advisory to algorithmic enforcement.
- Validate blood-based p-tau217/p-tau181 ratio as a TREM2 functional status biomarker that predicts anti-inflammatory treatment response in prodromal AD
- Systematically replicate the top 10 most-cited but unvalidated Alzheimer's disease mechanisms from 2020-2023 using harmonized human iPSC models from ApoE3/3, ApoE4/4, and TREM2 R47H genetic backgrounds
- Identify which FDA-approved Alzheimer's or neurology drugs show genotype-dependent efficacy signals in completed trial data through meta-analysis of ApoE-stratified and TREM2-stratified subgroups
- Design and validate composite digital-cognitive biomarkers combining wearable sensor data (gait, sleep) with smartphone-based cognitive testing to detect TREM2-associated neuroinflammatory decline 2-3 years before clinical symptoms