Stevenson et al: Navigating PGx Testing in Practice

See a new open-access paper from the Pharmacogenomics Global Research Network (PGRN), Stevenson et al. in Clin Pharmacol Therapeutics.

See also, Patel et al, 2025, Medical policy determinations for PGx among US health plans.  Am J M Care.

Here's the authors' abstract for Stevenson et al:

There is increasing attention on the clinical utility and value of pharmacogenetic (PGx) testing to individualize medication management. Most clinical practice guidelines from medical professional societies do not recommend routine PGx testing, with a few key exceptions. Inconsistent recommendations across clinical practice guidelines, FDA product labeling, and payer reimbursement policies have hampered widespread adoption of testing. 

Multiple resources exist to aid in the adoption and use of actionable PGx test results in clinical practice; however, most of these resources do not provide guidance on who should receive PGx testing and when-a critical question the clinical community continues to struggle with. There are multiple considerations when answering this question beyond the clinical validity of the drug-gene interaction itself, such as the actionable result frequency, severity of the adverse clinical outcome, predictive power of the PGx test, suitability of alternative treatments, cost, and turnaround time of test results. This perspective discusses these considerations and models for testing including preemptive screening, pretreatment testing, and reactive testing, highlighting advantages and disadvantages of each approach. The authors provide their perspectives on identifying candidates for PGx testing in the current real-world environment and how that differs from a clinically ideal scenario.

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Here's a Chat GPT Summary of the same paper:

In their comprehensive 2025 mini-review in Clinical Pharmacology & Therapeutics, Stevenson and colleagues address one of the thorniest issues in pharmacogenomics (PGx): identifying who should be tested and when. While the clinical validity of drug–gene interactions is increasingly well-supported, real-world implementation remains limited by inconsistent guidance from CPIC, FDA labeling, and clinical practice guidelines—not to mention payer resistance. 

The authors distinguish among three key PGx testing models: preemptive screening, pretreatment testing, and reactive testing..

Preemptive testing offers maximal long-term value and enables instant decision support, but is rarely reimbursed and difficult to operationalize outside of well-funded academic programs.

• Pretreatment testing—triggered by a diagnosis or high-risk drug—is more feasible and often covered, especially for medications with FDA boxed warnings or CPIC Level A/B recommendations. 
• Reactive testing, though more common, is least efficient, coming only after adverse events occur. The authors argue that shared decision-making, education of prescribers (especially via PGx-trained pharmacists), and robust EHR-based clinical decision support are critical for broader adoption. 

The authors propose a tiered strategy, starting with PGx for drugs linked to severe toxicities or regulatory requirements, and evolving toward more expansive panel-based testing as infrastructure and payer alignment mature. For clinicians and health systems alike, the paper provides a pragmatic roadmap for integrating PGx into practice while recognizing current structural, scientific, and reimbursement limitations.