PHARMIP: An insilico method to predict genetics that underpin adverse drug reactions

Abstract

Pharmacovigilance is the pharmacological science that focuses on the safe and appropriate use of drugs.Variability in response to drug therapy in both terms of safety and efficacy is highly related to patient's personal genomics. Hence, pharmacovigilance considers pharmacogenomics methodologies in the evaluation of medicinal products. The aim of this work is to introduce the pharmacovigilance/pharmacogenomics insilico pipeline (PHARMIP) that uses the drug (or drug candidate) digital structure and the advances in bioinformatics tools and databases to figure-out the genetic factors underlying the drug reported adverse reactions (ADRs).PHARMIP uses user-friendly freely available bioinformatics resources to help pharmacovigilance and pharmacogenomics scientists with minimal bioinformatics experience to retrieve helpful information for their daily basis activities. Also, PHARMIP could help the advances in precision medicine in a drug-centric approach as it can be used to reveal genetic risk factors for certain drug ADRs. Domperidone was used as an example to the application of PHARMIP as the pipeline was initially developed during the insilico exploration of domperidone cardiotoxic ADRs.Method is composed of 3 main steps: • Preparing the drug off-label targets (OLT) list. • Retrieving the related diseases/ adverse reactions (DA) list. • Analysis of DA list to get answers.

Keywords

• Pharmacovigilance
• Pharmacogenomics
• Precision medicine
• Similarity ensemble approach
• Pharmacophore mapping
• Molecular docking