Pharmacogenomics Intelligence Agent¶

live Domain: clinical Type: agent

RAG decision support + PGx drug-metabolism filtering.

A narrated, captioned explainer. Decision support for a qualified clinician.

Pharmacogenomics Intelligence Agent — what it takes in, what it computes, what it returns — Illustrative. Decision support for a qualified clinician — never autonomous diagnosis or prescribing.

In plain terms¶

The Pharmacogenomics Intelligence Agent answers one deceptively hard question: given this patient's genes, which drug and what dose is safe? It reads a patient's pharmacogenes, works out how fast they metabolize a drug, and grounds a dosing recommendation in the published CPIC guidelines — as decision support for the prescriber, never an autonomous prescription.

Why it matters¶

The same standard dose can be ineffective in one person and toxic in another, purely because of inherited differences in drug metabolism. Adverse drug reactions are a major cause of preventable harm. Getting the drug-gene match right before the first dose is one of the most concrete wins in precision medicine.

For a patient: the right drug at the right dose from the first prescription — matched to how their body actually processes it.

How it works¶

How the Pharmacogenomics agent reasons — genotype to star allele to phenotype to CPIC dose — Genotype → metabolizer phenotype → guideline dose. Decision support, never autonomous prescribing. Illustrative.

Call star alleles — the patient's drug-metabolism gene (e.g. CYP2D6, TPMT) is resolved into its named versions — star alleles, the standard shorthand (like *2 or *3) for the variants that change how fast that gene's enzyme works.
Assign phenotype — those alleles map to a metabolizer phenotype (poor → ultra-rapid).
Apply the guideline — the phenotype is matched to CPIC dosing guidance, with drug-metabolism filtering and a safety interlock.
Ground the answer — retrieval-augmented generation returns a cited recommendation, refusing to fabricate when the evidence isn't there.

What goes in, what comes out¶

In: a clinical query and the patient context (genotype).
Out: a grounded, cited dosing answer for the clinician.

Where it fits¶

Where the Pharmacogenomics agent sits — the safety interlock before any prescription — The right-drug-right-dose safety checkpoint the other engines hand off to. Illustrative.

It is the safety interlock: the Cardiology Engine and oncology hand off to it for the genetically safe drug, and it can flag any prescribing decision against the patient's metabolism — the prescriber still decides.

Honest limits¶

Decision support, never prescribing. It informs a qualified prescriber; it does not prescribe.
Grounded, and honest when it can't be. Like every intelligence agent it is a retrieval-augmented service: it needs a populated vector database and an LLM API key at runtime, and returns an honest degraded response (HTTP 503) rather than inventing clinical content when they're absent.
Guideline-cited. Recommendations trace to CPIC; where guidance is absent, it says so.

Interface¶

Endpoint: localhost:8507 · Invoke path: /
Serving: native · GPU: no · Cost class: —

Inputs

Name	Shape	Semantic	Notes
`query`	scalar	—
`patient_context`	map	patient_context

Outputs

Name	Shape	Semantic	Notes
`answer`	map	pgx_verdict

Tags: agent · pgx

Runtime dependency

This agent is a Retrieval-Augmented Generation service: at runtime it needs a populated vector database and an LLM API key. When those are absent it returns an honest degraded response (e.g. HTTP 503) and never fabricates clinical content.

↩ Back to the Intelligence Agents index · the Capability Maturity Matrix · the Capability Brief.

Note

Status and interface are generated from the capability registry (lib/hcls_common/capabilities.json) — the site cannot claim ahead of the code. All clinical output is decision support for a qualified clinician, never autonomous diagnosis.