Molden Espen

Clinical Implementation
COMPLEMENTARY USE OF PGX AND TDM IN ANTIDEPRESSIVE TREATMENT
E. Molden 1
1Center for Psychopharmacology, Diakonhjemmet Hospital, and University of Oslo, Oslo, Norway

BACKGROUND-AIM
Individual variability in clinical response of antidepressant treatment is extensive. The underlying causes are complex,
but patient differences in serum concentrations obtained at similar dosing of the same drug represent a key dimension.
The aim of the presentation is to provide an overview of how pharmacogenetic (PGx) and therapeutic drug monitoring
(TDM) analyses can be combined for personalized dosing of antidepressants to achieve target serum concentrations.

METHODS
Experiences from a laboratory service performing both PGx and TDM analyses to guide dosing of selected
antidepressants will illustrate how these tools are used in clinical practice in Norway. Research within the field provides
a basis for outlining a rational approach for combining the use of PGx and TDM to optimize dosing and improve
outcomes of antidepressant treatment.

RESULTS
Most antidepressants are metabolized by CYP2D6 or/and CYP2C19, where individual variability in phenotypes is
strongly determined by genetic variability. Many studies with different antidepressants, e.g. escitalopram, sertraline,
venlafaxine and vortioxetine, show that CYP2D6 or/and CYP2C19 genotype is associated with variability in serum
concentrations and treatment outcomes, such as drug switch and discontinuation. While PGx analyses related to
antidepressant treatment today is mainly reactive (in Norway) due to outside target TDM levels or unsuccessful
outcomes, future use probably would align to a concept of pre-emptive, PGx-guided starting dose. Although
improved mental health and substantial cost savings are estimated benefits of using pre-emptive genotyping when
prescribing antidepressant drugs, TDM-based dose tuning may increase patient proportions reaching target levels of
antidepressants, since unknown genetic factors as well as non-genetic factors, e.g. age and drug-drug interactions,
are also determinant of drug concentrations. Furthermore, pre-emptive use of PGx analyses for personalized dosing
of antidepressants drugs should consider the number-needed-to-genotype (NNG) to identify the most vulnerable
patients, i.e. poor or ultrarapid metabolizers. Another issue is the precision of diplotype activity scores in predicting
individual metabolizer phenotype, which should be critically assessed.

CONCLUSIONS
Complementary use of PGx and TDM analyses for individual dosing of antidepressive drugs likely increase treatment
successfulness compared to applying either tool separately.