Introduction Pharmacogenetics (PGx) is a well-researched tool to improve pharmacotherapy. So far, it has not been implemented into daily practice in Germany. In psychopharmacology, substantial benefit can be expected by using PGx due to the excessive CYP metabolism of the psychotropic drugs as well as already discovered target polymorphisms (e. g., serotonin receptor). Methods An evaluation of a naturalistic pharmacist-led pilot implementation of PGx testing in a psychiatric hospital in patients undergoing inpatient treatment for major depressive disorder was conducted. Length of stay, number of antidepressant switches, and rehospitalization rates were analyzed. A PGx-tested intervention cohort of n=49 was retrospectively compared to a control cohort of n=94 patients. Results The intervention cohort showed significantly shorter stays than the control, after correction of the length of hospital stay and the time to genotyping results (mean intervention: 36.3 d (SD: ±19.3 d); control: 46.6 d (±19.1 d); p=0.003). Antidepressant- naïve patients had the largest benefit from the PGx testing (intervention: 24.7 d (±13.5 d); control: 50.2 d (±22.5 d); p < 0.001. The number of antidepressant switches during the entire stay did not differ between the groups: 0.41 (0.64) vs. 0.21 (0.46); p=0.063 [95% CI −0.01–0.40]). Discussion Depressed patients, especially treatment-naïve, seem to benefit from PGx testing prior to treatment. Although the results of this retrospective evaluation are promising, more systematic prospective studies are needed to assess the effect of PGx testing on the treatment of major depressive disorder.

No abstract

Drug interactions are a well-known cause of adverse drug events, and drug interaction databases can help the clinician to recognize and avoid such interactions and their adverse events. However, not every interaction leads to an adverse drug event. This is because the clinical relevance of drug–drug interactions also depends on the genetic profile of the patient. If inhibitors or inducers of drug metabolising enzymes (e.g., CYP and UGT) are added to the drug therapy, phenoconcversion can occur. This leads to a genetic phenotype that mismatches the observable phenotype. Drug–drug–gene and drug–gene–gene interactions influence the toxicity and/or ineffectivness of the drug therapy. To date, there have been limited published studies on the impact of genetic variations on drug–drug interactions. This review discusses the current evidence of drug–drug–gene interactions, as well as drug–gene–gene interactions. Phenoconversion is explained, the and methods to calculate the phenotypes are described. Clinical recommendations are given regarding the integratation of the PGx results in the assessment of the relevance of drug interactions in the future.

Background: The use of therapeutic drug monitoring (TDM) to guide treatment with long-acting injectable (LAI) antipsychotics, which are increasingly prescribed, remains a matter of debate. The aim of this review was to provide a practical framework for the integration of TDM when switching from an oral formulation to the LAI counterpart, and in maintenance treatment. Methods: The authors critically reviewed 3 types of data: (1) positron emission tomography data evaluating dopamine (D2/D3) receptor occupancy related to antipsychotic concentrations in serum or plasma; D2/D3 receptors are embraced as target sites in the brain for antipsychotic efficacy and tolerability, (2) pharmacokinetic studies evaluating the switch from oral to LAI antipsychotics, and (3) pharmacokinetic data for LAI formulations. Based on these data, indications for TDM and therapeutic reference ranges were considered for LAI antipsychotics. Results: Antipsychotic concentrations in blood exhibited interindividual variability not only under oral but also under LAI formulations because these concentrations are affected by demographic characteristics such as age and sex, genetic peculiarities, and clinical variables, including comedications and comorbidities. Reported data combined with positron emission tomography evidence indicated a trend toward lower concentrations under LAI administration than under oral medications. However, the available evidence is insufficient to recommend LAI-specific therapeutic reference ranges. Conclusions: Although TDM evidence for newer LAI formulations is limited, this review suggests the use of TDM when switching an antipsychotic from oral to its LAI formulation. The application of TDM practice is more accurate for dose selection than the use of dose equivalents as it accounts more precisely for individual characteristics.

No abstract