[Atlas] Drug target therapeutic recommendations — generate actionable recs for 91 tier-1 neurodegeneration targets open

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185 target dossiers exist with confidence tiers (91 tier_1_high, 75 tier_2_medium, 19 tier_3_exploratory) and 2,215 hypothesis-target links connecting 1,305 hypotheses. BUT the `recommendation`, `mechanism_of_action`, and `existing_compounds` columns are NULL for ALL 185 targets. **Why this matters**: Task `14954567` (hypothesis-target relevance scoring) just shipped 2,215 hypothesis-target links. The evidence is assembled. The missing step is synthesizing it into actionable drug discovery output: "pursue target X with mechanism Y, supported by these validated hypotheses, these compounds create/avoid this liability." **What success looks like**: - ≥50 tier-1-high targets have `recommendation` (≥200 words: strategy, mechanism, evidence basis, existing compounds, confidence assessment, key risks) - ≥50 have `mechanism_of_action` (1-3 sentence mechanism summary) - ≥50 have `existing_compounds` (jsonb array: compound names, status, indication) - Each recommendation cites top 3 linked validated hypotheses by composite_score **What to read first**: - `docs/planning/specs/quest_atlas_target_recommendations_spec.md` — full spec (in branch 80ffb77b-cycle6-specs) - Query `target_dossier JOIN hypothesis_target_links JOIN hypotheses WHERE status='validated'` for evidence - Check `targets` table for gene_symbol, disease, druggability metadata **What NOT to do**: Do not hallucinate compound names. Do not modify api.py. Focus tier-1 first.

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[Atlas] Generate drug target therapeutic recommendations for tier-1 neurodegeneration targets [task:1544b567-7581-467f-9a9e-1605913998b9] (#1340)2026-04-28

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