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AyoOluwa O. Olubamiwa

AyoOluwa O. Olubamiwa received a Bachelor of Pharmacy (B.Pharm.) degree from the  University of Ibadan, Nigeria in 2012, and obtained a PhD degree in Pharmaceutical Sciences  (Emphasis: Medicinal Chemistry) from the University of Mississippi, USA in 2021. She is  currently an ORISE postdoctoral fellow at the National Center for Toxicological Research (NCTR) of the FDA. Her research interests include investigating risk factors that predispose to drug-induced liver injury using statistical modeling and applying computer-aided drug design tools to develop novel and optimize small molecules as drugs and probes for protein disease targets.

OpenTox Virtual Conference 2023 

The association of drug interactions for cytochrome P450 (CYP) enzymes and  non-CYP enzymes with drug-induced liver injury in humans 

Drug-induced liver injury (DILI) is a common cause of attrition in the drug development process for new drug candidates, as well as a common reason for the withdrawal of approved drug molecules from the market. Despite the diverse and complex mechanisms associated with DILI,  several attempts have been made develop predictive models that correlate various physicochemical  properties and pharmacological parameters of drugs with their reported DILI risk. Using a dataset of 325 molecules from Elsevier’s PharmaPendium database, we applied logistic regression and random Forest to identify correlations between the reported DILI risk of the drugs and their interactions with cytochrome P450 (CYP) and non-CYP enzymes. Our analysis reveals that drugs that are inhibitors of non-CYP enzymes are more likely to be correlated with DILI risk (OR: 3.34,  p < 0.05) than drugs that are not inhibitors of non-CYP enzymes. Among the different families of  non-CYP enzyme examined, drugs that interact (as substrates, inhibitors, and/or inducers) with the  UGT enzyme family are more likely associated with severe DILI risk. The UGT enzymes also appear to be as important as CYP enzymes, in predicting DILI risk. These findings could help identify new drug candidates with DILI liability at the early stages of drug development.