Prototype BETA 1.0

PGx Engine BETA-1.0

First packaged build of an interpretable pharmacogenomics engine: it maps a
reported star-allele diplotype to a metabolizer phenotype, then matches that
phenotype to published CPIC gene–drug recommendations and shows the guideline
text behind each one.

Built for BMI 530: Software Development in Biomedical Informatics.

Educational prototype. Not clinical decision support, and not validated
for patient care. Nothing here should inform a prescribing decision.

What's in it

• Python engine — resolution, phenotype assignment and recommendation
  matching, served over HTTP by FastAPI, frozen with PyInstaller
• JavaFX client — gene and diplotype picker, gene cards, and drug rows that
  open to show the full CPIC recommendation, its implications, the genes that
  decided it and a link to the guideline
• Knowledge base — CYP2C19, CYP2D6 and CYP2B6: 18,678 diplotypes and 2,159
  recommendations, built from CPIC v1.61.0 (retrieved 2026-11-11)

Report schema 1.1. Every report carries its own provenance block: CPIC release,
PharmVar version, retrieval timestamp and engine version.

What it deliberately does not do

It does not combine genes into a composite score, and it does not rank drugs
best-to-worst. That layer is what separates a commercial combinatorial test
from the guidelines underneath it, and it is also the layer the evidence does
not support. Where a guideline declines to advise, the report says so and marks
it — an abstention is a result, not a blank.

Validation

• GeT-RM reference diplotypes resolved 652 / 663 (98.3%), or 99.4%
  excluding the seven where GeT-RM itself reports no consensus
• CYP2D6 activity-score banding checked against CPIC across all 16,836
  diplotypes
• A rebuild five weeks later against CPIC v1.61.0 changed no phenotype and no
  recommendation for the six drugs in scope
• 99 tests, run offline against a generated fixture database

Attribution

Gene–drug recommendations, diplotype–phenotype tables and allele function
assignments come from CPIC / ClinPGx via their public
REST API, and guideline text is reproduced verbatim with attribution.
Reference diplotypes from CDC GeT-RM.