Claim

A homomorphically encrypted, multi-registry pharmacogenomic surveillance framework can estimate clinically useful safety gradients for HLA-B*58:01-associated allopurinol hypersensitivity and TPMT/NUDT15-associated thiopurine myelotoxicity with discrimination close to plaintext pooled analysis, while keeping patient-level genotypes and labs encrypted.

Rationale

Pharmacogenomic safety signals are often strongest in pooled datasets, but cross-institutional sharing is blocked by privacy, governance, and jurisdictional barriers. For adverse-event prediction, many useful summary operations are additive or approximately linear and may be estimated over encrypted representations. If the encrypted pipeline preserves clinically relevant ranking and calibration, decentralized cohorts could validate rare-drug-toxicity thresholds without exposing raw genotypes, CBC time series, or identifiable medication histories.

Testable prediction

Compared with conventional pooled analysis, an FHE-based federated analysis of decentralized autoimmune registries will retain at least 90% of discrimination/calibration performance for:

• HLA-B*58:01 + CKD + dose models for allopurinol SCAR risk
• TPMT/NUDT15 + CBC + co-medication models for thiopurine myelotoxicity

Proposed study

• Data sources: separate registries with local pharmacogenomic and safety-event data
• Outcomes: SCAR after allopurinol; leukopenia/myelotoxicity after thiopurines
• Comparison arms: local-only models vs plaintext pooled model vs FHE federated model
• Primary metrics: AUROC, calibration slope, decision-curve net benefit, reclassification
• Falsification: if encrypted analysis materially degrades discrimination or calibration below clinically usable thresholds, the hypothesis fails

Why it matters

Rare but serious drug toxicities need large, diverse datasets. Privacy-preserving validation could make decentralized pharmacogenomics more ethical and more feasible.

References

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3. Moriyama T, Nishii R, Perez-Andreu V, et al. Nat Genet. 2016;48(4):367-373. DOI: 10.1038/ng.3508
4. Acar A, Aksu H, Uluagac AS, Conti M. BMC Med Inform Decis Mak. 2018;18(1):93. DOI: 10.1186/s12911-018-0716-9