White-Label PGx Reporting: Add a Pharmacogenomics Line Without Replacing Your LIS

You do not need to rip out your LIS to start offering pharmacogenomic testing. A white-label PGx reporting line lets a CLIA lab keep its existing instruments and workflow, hand off raw genotype data to a dedicated interpretation engine, and get back a finished, branded report that your director signs out. It is the fastest credible path from "we run the assay" to "we deliver a clinical-grade PGx report."

What "white-label PGx reporting" actually means

White-label means the interpretation engine is invisible to the ordering clinician and the patient. The report looks like your laboratory produced it end to end — your logo, your letterhead, your CLIA number, your director's signature — because, in every way that matters clinically, you did. The vendor supplies the curated evidence, the diplotype-to-phenotype logic, and the report-generation infrastructure; your lab supplies the analytical result, the validation, and the sign-out.

Standalone means it is decoupled from any particular laboratory information system. You are not buying a new LIS and you are not committing to one. You are adding a reporting capability that consumes the genotype data you already produce and returns a clinical document. That distinction matters because the most common reason labs stall on PGx is the assumption that it requires a platform overhaul. It does not. Our PGx reporting product is built specifically to run as a line item on top of whatever you operate today.

How it fits a lab that already has an LIS

The integration surface is deliberately narrow. Your existing system stays the system of record for orders, demographics, and accessioning. What changes is only the interpretive step: instead of a tech manually cross-referencing CPIC tables and assembling a Word template, structured genotype data is sent to the reporting engine, and a finished, formatted report comes back.

Concretely, the flow looks like this:

• In: star-allele calls, diplotypes, or raw variant data from your genotyping or sequencing pipeline.
• Process: diplotype-to-phenotype translation in CPIC-standardized terminology, drug-gene matching across 700+ medications, and assembly of a structured, source-cited report.
• Out: a branded PDF plus discrete results, delivered back to your LIS or portal.

Because the boundary is just data in and a report out, you do not inherit a second EHR-style application your staff has to live in. The heavy lifting happens through our integration layer, which speaks the formats your stack already uses.

Delivery: API, HL7 v2, and FHIR — your choice

A reporting line is only useful if the result lands where your team and your clients already work. There is no single right transport, so the platform supports several:

• REST API for labs that want to submit genotypes and pull finished reports programmatically, including embedding a PGx order and result step inside an existing portal.
• HL7 v2 (ORM/ORU-style messaging) for the interface engines most clinical labs and hospital clients still run, so results flow into downstream systems as discrete fields, not just a PDF attachment.
• FHIR resources for modern EHR and patient-app integrations that expect Observation and DiagnosticReport semantics.
• Secure file exchange / upload for lower-volume or batch workflows where a full interface is overkill.

The point is that you do not bend your environment to the vendor. You pick the transport that matches your interface engine and your clients, and the same interpretive content is delivered through it. Mapping and connectivity are handled as part of Labrynix Connect.

Your brand, your CLIA sign-out

This is the line that separates a reporting partner from a send-out. With white-label reporting, the clinical document is yours. It carries your laboratory's identity, and — critically — it is released under your CLIA certificate by a qualified person at your lab. The AI layer drafts the interpretation; it never signs the report and never makes the clinical call. A director or designee at your lab reviews, edits if needed, approves, and signs out.

That human-in-the-loop step is not a formality. With the FDA LDT rule vacated in 2025, CLIA is once again the operative framework for laboratory-developed tests, which means the accountability for what goes out the door sits squarely with your lab and its director. A reporting engine that respects that — drafting structured content for a human to validate rather than auto-releasing — is the only model that fits the current regulatory reality. You can see how the finished document reads in a sample report.

Coverage and evidence: the part that actually differentiates

White-labeling itself is table stakes; most PGx vendors offer it. The real question a lab director should ask is what is inside the report. Two things matter most: breadth of coverage and the defensibility of the interpretation.

On breadth, the reporting covers 700+ medications, spanning FDA-labeled and over-the-counter drugs across cardiology, psychiatry, pain management, diabetes, and more. That range lets you serve primary-care and specialty PGx panels from one engine instead of stitching together partial sources.

On defensibility, the interpretation does not lean on any single authority — because no single source is sufficient. FDA labeling specifies an action for only some drug-gene pairs, and it does not always agree with CPIC. So the engine reconciles the major public evidence bases together: CPIC guidelines, FDA pharmacogenomic labeling, the Dutch DPWG recommendations, and PharmGKB annotations. The output is structured to the ACMG 2022 clinical pharmacogenomics standard across nomenclature, testing, interpretation, and reporting. The result is a report whose every recommendation can be traced to a cited source.

No black box: why transparency wins trust

The fastest way to lose a clinician's confidence in a PGx report is opacity. Independent analyses have shown commercial PGx tools diverging from CPIC on a meaningful share of drug-gene recommendations, and proprietary, unexplained logic is documented as eroding trust. Our approach is the opposite by design: source-cited, CPIC-concordant, and traceable, with the diplotype-to-phenotype call expressed in standardized phenotype terminology.

This also happens to be the answer to the broader skepticism about AI in the lab. Surveys consistently show that the top barriers to adoption are accuracy and over-reliance concerns, not lack of awareness. A reporting layer that shows its work — and that always ends with a human sign-out — addresses those concerns directly rather than asking clinicians to trust a model on faith. You can read more about how our lab-trained AI layer is built on leading models and kept transparent.

From genotype to a billable, branded report

Standing up a PGx line is not only about the science; it is about getting paid for it. Molecular and PGx claims increasingly require MolDX/DEX Z-codes from Medicare and major commercial payers, and claims submitted without the right Z-code, CPT, and documentation get denied. A reporting line that ends at the PDF leaves that problem unsolved.

Because Labrynix is a connected platform, the same data that produces the report can feed structured, payer-ready output — so the report you generate and the claim you submit are aligned from the start. If you want the full picture, the platform overview shows how reporting connects to billing and Z-code workflows, and you can model the economics of adding a PGx line with the ROI calculator.

Is a standalone PGx line right for your lab?

If you already run a genotyping or NGS workflow and want to add pharmacogenomics without a platform migration, white-label reporting is the lowest-friction path. You keep your LIS, you keep your sign-out authority, and you add a clinical product your clinicians are already asking for. If you are also evaluating a fuller platform, our LIS/LIMS can replace the underlying system later — but you do not have to start there, and many labs never need to.

The honest test is whether the report is defensible: branded as yours, signed by your director, traceable to cited evidence, and broad enough to be useful. When all four are true, a PGx reporting line stops being a project and becomes a product. To see it against your own data and panel, book a demo.

Frequently asked questions

Can I add white-label PGx reporting without replacing my existing LIS?

Yes. White-label PGx reporting is designed to sit alongside your current LIS, not replace it. Labrynix ingests genotype or variant data from your existing instruments and pipeline, returns a finished, branded interpretive report, and delivers it back over an API, HL7 v2, FHIR, or secure file exchange. Your sample accessioning, order entry, and core workflow stay exactly where they are today.

Whose name and CLIA number appear on a white-label PGx report?

Yours. The report carries your laboratory's branding, logo, and letterhead, and it is reviewed, approved, and signed out by your qualified staff under your CLIA certificate and laboratory director. The AI layer drafts a structured, source-cited interpretation, but a human at your lab validates and releases every report. The platform is the reporting engine behind the scenes; the clinical document is unmistakably yours.

How many medications does the PGx reporting cover, and what evidence is it based on?

Labrynix PGx reporting spans 700+ medications, including FDA-labeled and over-the-counter drugs across cardiology, psychiatry, pain, diabetes, and other therapeutic areas. Interpretations reconcile the major public evidence sources — CPIC guidelines, FDA pharmacogenomic labeling, DPWG recommendations, and PharmGKB annotations — and are structured to the ACMG 2022 clinical pharmacogenomics standard so every recommendation is traceable rather than a black box.