Building a Scalable PGx Program: 5 Workflow Pitfalls to Avoid
Pharmacogenomics (PGx) holds enormous promise, but implementing it at scale is anything but straightforward.
We’ve seen many PGx programs start strong and then stall. Not because of clinical resistance, but because of operational friction. From inconsistent reporting to unclear ownership, the obstacles often aren’t scientific in nature, they’re workflow-based.
If you’re building a PGx service that’s designed to grow, here are five common pitfalls to avoid.
5 Workflow Pitfalls to Avoid
1. No Plan for Dry-Lab Bottlenecks
You can process samples fast. But can you generate reports fast?
Many PGx programs hit a wall because interpretation and reporting steps are manual, inconsistent, or poorly documented. Without automation and templated output, turnaround time slows and quality varies.
2. Inconsistent Genotype-to-Phenotype Mapping
You can process samples fast. But can you generate reports fast?
Many PGx programs hit a wall because interpretation and reporting steps are manual, inconsistent, or poorly documented. Without automation and templated output, turnaround time slows and quality varies.
3. Reports That Don’t Fit the Prescribing Workflow
It’s not enough to be accurate. You also have to be usable.
If your reports don’t integrate into the clinical workflow (i.e. EHR med lists, prescribing systems, pharmacist dashboards, etc.) they’re unlikely to be referenced at the point of care. A scalable PGx program builds for delivery, not just discovery.
4. Lack of QA and Audit Infrastructure
Every change to a gene-drug recommendation needs to be traceable. Programs that rely on ad hoc review or undocumented logic can’t support regulatory or payer audits, especially across multiple facilities or test types. Auditability must be a design feature.
5. Too Much Custom Code, Not Enough Repeatability
Custom scripts may work at pilot scale, but they’re hard to maintain across teams and sites. Scalable programs minimize fragile code and maximize configuration so you can grow without rewriting pipelines every quarter.
PraediGene is Built for PGx at Scale
PraediGene supports clinical-grade PGx workflows with built-in:
- Star allele translation and phenotype mapping
- Drug-gene summary tables and stratification
- Customizable report templates for prescribers
- EHR/LIS output formats (PDF, JSON, HL7)
- Audit trails for every logic version and report output
Used across multiple facilities, PraediGene is designed to scale without sacrificing control, clarity, or compliance.
Launching a PGx program is about building the right infrastructure to grow.
Avoiding these five workflow pitfalls sets the stage for a service that clinicians trust.