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Beyond Genotype: Integrating Phenoconversion into Pharmacogenetic Decision-Making in Psychiatry

AI Summary
  • Phenoconversion causes mismatch between genotype-predicted and observed metabolic phenotype, affecting drug response and safety.
  • Factors such as drug interactions, smoking, inflammation, physiology and disease modify enzyme activity and systemic drug exposure.
  • Integrate pharmacogenetics with concomitant medications, clinical status, lifestyle, therapeutic drug monitoring and longitudinal data for dynamic personalised prescribing.
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Pharmaceuticals (Basel). 2026 Oct 2;19(10):1570. doi: 10.3390/ph19101570.

ABSTRACT

Interindividual variability in psychotropic drug response contributes to treatment failure, adverse drug reactions, and repeated medication adjustments. Pharmacogenetics supports precision prescribing by identifying genetic variants associated with drug metabolism, efficacy, and tolerability, and evidence-based recommendations are available for several psychotropic medications. However, genotype predicts metabolic capacity rather than the enzyme activity actually expressed in vivo or the systemic drug exposure achieved at a given time. This narrative review examines phenoconversion, the mismatch between genotype-predicted and observed metabolic phenotype, and its implications for psychiatric pharmacotherapy. Drug-drug interactions, smoking, inflammation, physiological changes, and disease-related factors can modify drug-metabolizing enzyme activity or otherwise alter systemic drug exposure despite an unchanged genotype. We discuss how these influences can limit the applicability of genotype-based dosing recommendations and propose a dynamic framework integrating pharmacogenetic results with concomitant medications, clinical conditions, lifestyle factors, therapeutic drug monitoring, and longitudinal changes in patient status. This framework may also refine the assessment of treatment adequacy, because prescribed dose, duration, and adherence do not necessarily ensure adequate drug exposure. Future clinical decision-support systems should combine pharmacogenetic and longitudinal clinical data to enable more individualized and dynamically informed psychopharmacological treatment.

PMID:42943267 | DOI:10.3390/ph19101570

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