Dr. Maria A. Miteva:”AI Approach to Predict Inhibitors of Drug Metabolizing Enzymes and Transporters for the Design of Safer Drugs”

Abstract

Drug-drug interactions (DDI) are key for safety treatments. Drug metabolizing enzymes (DME) and drug transporters strongly influence the drug disposition and can be involved in DDI of a large number of drugs and drug candidates. We employ an AI-based approach integrating structural bioinformatics and machine learning/deep learning methodologies to predict interactions of drugs with DME and drug transporters. We focus on the DME cytochrome P450 and the ABC transporters P-glycoprotein and BCRP. Such AI approaches can improve the prediction of DDI in clinical practice and drug development pipelines.

Curriculum Vitae

Maria Miteva is a Research Director at INSERM. She has been working in Bulgaria (Bulgarian Academy of Sciences), Sweden (Karolinska Institutet), and France (CNRS, INSERM). She joined INSERM in 2002 and is currently co-directing the INSERM Unit ERL U1268 “Medicinal Chemistry and Translational Research”, at the Faculty of Pharmacy, University Paris Cite. She has experience in bioinformatics, chemoinformatics and AI for drug discovery, medicinal chemistry, biophysics, drug-drug interactions, and toxicity prediction. She has 4 patents and more than 100 peer-reviewed publications (ID ORCID:N-2419-2018). She edited the book “In silico lead discovery“ (Bentham Sci 2011). Currently she is the Editor-in-Chief of Advances and Applications in Bioinformatics and Chemistry (Dove Medical Press Ltd).