Identifying CYP2C19 and CYP2D6 poor metabolizers from TDM data

Pharmacogenetic (PGx) analysis and therapeutic drug monitoring (TDM) are tools used for personalized dosing. While PGx enables pre-emptive dose predictions to hit target concentrations of specific drugs based on genetic information, TDM captures all sources of pharmacokinetic variability, but often needs steady-state conditions to provide reliable dose adjustments.Most laboratories perform either TDM or PGx. We used TDM data to predict critical drug-metabolizing phenotype, where poor metabolizers (PMs) of CYP2C19 or CYP2D6 probably represent the most important category.

Leveraged by large-scale data collected in a laboratory performing both TDM of psychotropic medications and PGx analyses, biomarker estimates, such as metabolic ratios (MR) derived from TDM analyses were used to identify CYP2C19 or CYP2D6 PMs. The same approach was applied for other, non-drug agents, using an UPLC-MS analysis that can identify CYP2C19 or CYP2D6 PMs.

Escitalopram, sertraline, risperidone and venlafaxine are drugs where MR from TDM analyses were efficiently used to identify CYP2C19 or CYP2D6 metabolism. Among these, escitalopram (CYP2C19) and venlafaxine (CYP2D6) were probably the most promising and reliable ones in detecting PMs. In addition, UPLC-MS analyses could detect solanidine, a CYP2D6 biomarker found in potatoes, which may provide an important, extra value in performing TDM.

MRs of several psychotropic drugs measured by TDM can be used with quite high sensitivity and specificity for the identification of CYP2D6 or CYP2C19 PMs. So far, the dietary biomarker solanidine seems to be the most promising biomarker and might be considered for inclusion in TDM assays to identify CYP2D6 or CYP2C19 PMs.

Publication History

Article published online:
12 March 2024