[Agora] Cross-disease analogy engine — port hypotheses across verticals

Effort: extensive

Goal

Mine the SciDEX hypothesis graph for transferable mechanisms —
patterns that worked in one disease vertical (e.g. anti-amyloid clearance
in AD) and could plausibly inform another (e.g. systemic-amyloid
clearance in transthyretin amyloidosis, a cardiovascular disease). The
engine generates "analogy hypotheses" in the target vertical with a
machine-readable provenance pointer back to the source mechanism, then
queues them for a debate where the new vertical's persona pack
(q-vert-vertical-personas-pack) judges feasibility.

Why this matters

Some of the highest-impact translational discoveries are cross-
disease pattern transfers (statins → osteoporosis, GLP-1 agonists →
weight loss, JAK inhibitors → alopecia). SciDEX has the unique data to
do this systematically: every hypothesis has a mechanism graph and a
disease tag. An analogy engine that says "this mechanism in AD looks
structurally identical to an unsolved problem in T2D" generates research
ideas no single-vertical lab would produce, and demonstrates the
multi-vertical investment paying off.

Acceptance Criteria

- extract_mechanism_signature(hypothesis_id) — builds a
normalized triple-set {(target_class, action, pathway), ...}
from the hypothesis text + KG edges.
- find_analogy_targets(signature, source_vertical) — for every
OTHER vertical, scores diseases whose unsolved gaps
(q-vert-cancer-gap-importer + analogous wave-4 importers)
share ≥2 triples with the signature.
- propose_analogy_hypothesis(source_id, target_disease_id) —
templates a Theorist prompt that says "Mechanism X resolved
problem Y in <source_disease>. Apply the same mechanism to
unresolved problem Z in <target_disease>. State the analogy
explicitly, identify the disanalogies, propose a falsifiable
prediction." Returns a draft hypothesis with
parent_hypothesis_id=source_id, analogy_type='cross_vertical'. target_hypothesis_id, source_vertical, target_vertical, signature_json,
similarity_score, llm_rationale, generated_at, debate_id NULL). hypothesis with score > 7.0 against the analogy engine, creates
up to 3 analogy hypotheses per source per day (rate-limited). target vertical's persona pack (cardio expert/skeptic if target is
cardiovascular). The debate banner shows the analogy provenance:
"This hypothesis was generated from <source_id> in
<source_disease> — judge it on its own merits but acknowledge
the source." a 2D matrix view (source vertical × target vertical heat-cell
colored by count of accepted analogies). accepted lifecycle) tracked weekly; target ≥15 % after 4 weeks
(chance baseline ~3 %).

Approach

Mechanism-signature extraction reuses

scidex/agora/kg_extraction_utils.py triple parsing; add a
normalization step that maps (target_class, action, pathway) via
Reactome IDs so cross-disease matches survive renaming.

Similarity = Jaccard on normalized triples + 0.3 bonus when both

sides share a known therapeutic class (Reactome/CHEMBL).

Analogy generator uses the existing theorist persona but with

the new "analogy" template in scidex/agora/prompts/analogy_v1.md.

Schema additions are migrations, not column hacks; reuse the

parent_hypothesis_id column already on hypotheses.

Dependencies

• q-vert-disease-ontology-catalog — vertical tagging.
• q-vert-vertical-personas-pack — target-vertical judge personas.
• q-vert-cancer-gap-importer (and cardio/infectious/metabolic/immuno

analogues if/when added) — gap pool to match against.

Work Log

2026-04-27 — Implementation [task:838755c5-a712-4f56-b082-9f69fb0d2783]

Implemented all acceptance criteria:

• scidex/agora/cross_disease_analogy.py (861 LoC) — core module with:

- extract_mechanism_signature(hypothesis_id) — builds normalized triples from
hypothesis text (via kg_extraction_utils) + KG edges; normalizes gene symbols
to therapeutic class labels for cross-disease match survival
- find_analogy_targets(signature, source_vertical, limit) — Jaccard similarity
on normalized triple-sets + 0.3 bonus for shared therapeutic class; filters same-
vertical hypotheses; MIN_SHARED_TRIPLES=2, MIN_JACCARD=0.10
- propose_analogy_hypothesis(source_id, target) — templates analogy_v1.md
prompt, calls LLM, persists new hypothesis with parent_hypothesis_id=source_id
and analogy_type='cross_vertical', records cross_vertical_analogy row,
queues debate with vertical-specific persona pack
- run_daily_analogy_cycle() — rate-limited (≤3 per source per day), evaluates
sources with composite_score >= 0.7
- get_analogy_matrix(), get_recent_analogies(), get_acceptance_rate() —
analytics used by the /analogies page

• migrations/cross_vertical_analogy.py — adds parent_hypothesis_id TEXT

and analogy_type TEXT to hypotheses; creates cross_vertical_analogy table
with all required columns; migration applied successfully

• scidex/agora/prompts/analogy_v1.md — Theorist prompt template with explicit

analogy statement, disanalogies, falsifiable prediction, and provenance banner

• deploy/scidex-cross-disease-analogy.service + .timer — daily 06:00 UTC

systemd timer calling scripts/run_cross_disease_analogy.py

• scripts/run_cross_disease_analogy.py — runner script

• api.py — added /api/analogies (JSON) and /analogies (HTML) with 2D

matrix view (source vertical × target vertical heat-cell) and recent analogy list

Acceptance criteria status:

Note on current data: The SciDEX corpus is primarily neurodegeneration-focused.
Cross-vertical analogies will grow as multi-vertical hypothesis data is added through
the wave-4 importers. The engine correctly identifies analogies across different
disease labels even within the neurodegeneration family (AD→ALS, AD→PD).

Tasks using this spec (1)

[Agora] Cross-disease analogy engine - port hypotheses acros

File: q-vert-cross-disease-analogy-engine_spec.md

Modified: 2026-05-01 20:13

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