# Known Limitations

The honest list of what would break this MVP at scale or in a different disease. Useful for the
next pharma conversation: "yes, we know these are limitations, here's how v2 addresses them."
Source: PLAN.md §9.

1. **Cell-composition confound in sickle cell expression data.** Whole-blood differential
   expression partly reflects different blood cell ratios, not disease biology. v1 acknowledges
   this; v2 should deconvolve cell types.

2. **LINCS L1000 cell-line limitations.** The 978 landmark genes were measured mostly in cancer
   cell lines (MCF7, A375, PC3, …). Signatures for non-oncology diseases may be noisy. A
   field-wide limitation, not unique to Reverso.

3. **L-glutamine LINCS coverage — RESOLVED, opposite of expected.** L-glutamine DOES have a
   Phase I signature (hydroxyurea is Phase-II-only) — both ground-truth drugs are scorable. But
   L-glutamine's connectivity is **ambiguous (WTCS=0)**: its up- and down-set enrichments share
   a sign, so it shows no reversal. It ranks 100/300. So the ground-truth test effectively rests
   on hydroxyurea, which itself only reaches top 13% (raw) — see the recovery test report.

4. **Connectivity scoring surfaces broad-effect drugs as false positives.** HDAC inhibitors and
   broad kinase inhibitors often top connectivity rankings simply because they perturb many
   genes. The mechanistic prior (Week 3) helps filter, but does not eliminate this.

5. **Hydroxyurea will probably pass the recovery test by construction.** Sickle cell +
   hydroxyurea is a well-studied pair. Passing is necessary but not sufficient to claim the
   platform generalizes. The next disease is the real test — do not sell sickle cell results as
   proving the platform.

6. **No mechanistic validation layer.** Pure ML matching is not sufficient for extrapolation
   (flagged by multiple experts). The MVP knowingly omits the mechanistic layer; it is a phase-2
   addition. Position the MVP as "discovery hypothesis generation," not "validated prediction."

7. **Top-ranked novel candidates are not wet-lab validated.** They are computational hypotheses
   to test, not discoveries. Use careful language in any write-up.

8. **Gene-space bottleneck (v1 → fixed in v1.1).** v1 scored on only the 978 landmark genes (12%
   signature overlap) — the main driver of the v1 failure. v1.1 uses the full 12,328-gene space
   (85% overlap) and recovers hydroxyurea. HBG1/HBG2 remain absent from LINCS entirely.

9. **No reference-signature library for tau.** Textbook CMap tau saturated at ±100 (a coherent
   query always out-connects random gene sets). v1.1 substitutes a per-drug specificity z-score.
   Proper tau needs a library of real reference signatures — a v2 / curated-data item.

10. **Negative-control criterion may be invalid for connectivity scoring.** Unrelated drugs
    (norethindrone, ciprofloxacin) rank as top specific reversers — connectivity measures
    expression reversal, not therapeutic relatedness.

## Recovery test outcome

Pre-registered test (**v1, confirmatory**): **FAILED** all three criteria (hydroxyurea rank
40/top 13%; L-glutamine rank 100; 1/5 negative controls bottom-half). Post-hoc (**v1.1,
exploratory**): hydroxyurea recovers to rank 18 (top 6%, passes), but L-glutamine (rank 213, does
not reverse) and negative controls (2/5) still fail → overall still FAIL. See
`recovery_test_report.md`.

| Drug | Issue | v1.1 status |
|---|---|---|
| hydroxyurea | needed the full gene space | rank 18 (top 6%) — recovered post-hoc |
| L-glutamine | metabolite, no reversal signal (positive connectivity) | rank 213 — genuine negative |
| neg controls | reverse the generic inflammation signature | 2/5 bottom-half — criterion questionable |