How reliable are pharmacogenomic panels in ADHD?Â
With the rise of personalised medicine, ADHD pharmacogenomic panels have become more widely available, often marketed as tools to guide medication choices through genetic screening. Their reliability is nuanced; these tests show promise, but their clinical utility in ADHD is still limited and continues to evolve.
What these panels typically include
Pharmacogenomic panels used in ADHD often test for variants in genes like:
- CYP2D6 affects the metabolism of atomoxetine and some stimulants
- CES1 impacts breakdown of methylphenidate
- COMT, DAT1, DRD4 involved in dopamine regulation and drug response
Some panels may also include genes linked to side effect risks (e.g., cardiovascular sensitivity) or mental health comorbidities. The idea is to match medications to your genetic makeup to improve response and reduce adverse effects.
How valid and useful are they?
Test validity
Many of the tested variants are scientifically valid meaning they have known roles in drug metabolism. For instance, CYP2D6 testing has clear pharmacokinetic relevance for atomoxetine. These markers are backed by data and included in FDA drug labelling.
Clinical utility
Despite their biological plausibility, most panels do not yet have strong enough evidence to predict which ADHD drug will work best for you. Most current studies show small effect sizes, and results can be inconsistent across populations.
Interpretation complexity
A genetic result is just one piece of the puzzle. Factors like age, environment, coexisting conditions, and lifestyle also play major roles in treatment success. So even a “high-risk” gene marker may not translate into clinical symptoms.
Should you use one?
Pharmacogenomic panels may be most helpful for individuals who have poor responses or side effects with multiple medications. While not a silver bullet, they can provide useful context, especially when interpreted by a qualified clinician.
Visit providers like ADHD Certify for personal consultations that include expert interpretation of pharmacogenomic data.
For a deeper dive into the science, diagnosis, and full treatment landscape, read our complete guide to Genetic studies and biomarkers.

