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Prescription Advice Based on Data of Drug-Drug-Gene Interaction of Patients with Polypharmacy

PURPOSE: Pharmacogenetic counselling is a complex task and requires the efforts of an interdisciplinary team, which cannot be implemented in most cases. Therefore, simple rules could help to minimize the risk of medications incompatible with each other or with frequent genetic variants. PATIENTS AND...

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Detalles Bibliográficos
Autores principales: Salamone, Sandro, Spirito, Sara, Simmaco, Maurizio, Unger, Marius, Preissner, Saskia, Gohlke, Björn-Oliver, Eckert, Andreas, Preissner, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9394521/
https://www.ncbi.nlm.nih.gov/pubmed/36004008
http://dx.doi.org/10.2147/PGPM.S368606
Descripción
Sumario:PURPOSE: Pharmacogenetic counselling is a complex task and requires the efforts of an interdisciplinary team, which cannot be implemented in most cases. Therefore, simple rules could help to minimize the risk of medications incompatible with each other or with frequent genetic variants. PATIENTS AND METHODS: One hundred and eighty-four multi-morbid Caucasian patients suffering from side effects or inefficient therapy were enrolled and genotyped. Their medication was analyzed by a team of specialists using Drug-PIN(®) (medication support system) and individual recommendations for 34 drug classes were generated. RESULTS: In each of the critical drug classes, 50% of the drugs cannot be recommended to be prescribed in typical drug cocktails. PPIs and SSRI/SNRIs represent the most critical drug classes without showing a single favorable drug. Among the well-tolerated drugs (not recommended for less than 5% of the patients) are metamizole, celecoxib, olmesartan and famotidine. For each drug class, a ranking of active ingredients according to their suitability is presented. CONCLUSION: Genotyping and its profound analysis are not available in many settings today. The consideration of frequent alterations of metabolic elimination routes and drug–drug–gene interactions by using simple rankings can help to avoid many incompatibilities, side effects and inefficient therapies.