Genetic predisposition is one factor influencing interindividual drug response. Pharmacogenetic information can be used to guide the selection and dosing of certain drugs. However, the implementation of pharmacogenetics (PGx) in clinical practice remains challenging. Defining a formal structure, as well as concrete procedures and clearly defined responsibilities, may facilitate and increase the use of PGx in clinical practice. Over 140 patient cases from an observational study in Switzerland formed the basis for the design and refinement of a pharmacist-led pharmacogenetics testing and counselling service (PGx service) in an interprofessional setting. Herein, we defined a six-step approach, including: (1) patient referral; (2) pre-test-counselling; (3) PGx testing; (4) medication review; (5) counselling; (6) follow-up. The six-step approach supports the importance of an interprofessional collaboration and the role of pharmacists in PGx testing and counselling across healthcare settings.

Pharmacogenetics (PGx) is an emerging aspect of personalized medicine with the potential to increase efficacy and safety of pharmacotherapy. However, PGx testing is still not routinely integrated into clinical practice. We conducted an observational case series study where PGx information from a commercially available panel test covering 30 genes was integrated into medication reviews. The aim of the study was to identify the drugs that are most frequently object of drug-gene-interactions (DGI) in the study population. Patients and Methods:In out-patient and in-patient settings, we recruited 142 patients experiencing adverse drug reaction (ADR) and/or therapy failure (TF). Collected anonymized data from the individual patient was harmonized and transferred to a structured database. Results:The majority of the patients had a main diagnosis of a mental or behavioral disorder (ICD-10: F, 61%), of musculoskeletal system and connective tissue diseases (ICD-10: M, 21%), and of the circulatory system (ICD-10: I, 11%). The number of prescribed medicines reached a median of 7 per person, resulting in a majority of patients with polypharmacy (≥5 prescribed medicines, 65%). In total, 559 suspected DGI were identified in 142 patients. After genetic testing, an association with at least one genetic variation was confirmed for 324 suspected DGI (58%) caused by 64 different drugs and 21 different genes in 141 patients. After 6 months, PGxbased medication adjustments were recorded for 62% of the study population, whereby differences were identified in subgroups. Conclusion:The data analysis from this study provides valuable insights for the main focus of further research in the context of PGx. The results indicate that most of the selected patients in our sample represent suitable target groups for PGx panel testing in clinical practice, notably those taking drugs for mental or behavioral disorder, circulatory diseases, immunological diseases, pain-related diseases, and patients experiencing polypharmacy.