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Pharmacokinetic Drug-Drug Interactions With Drugs Approved by the U.S. Food and Drug Administration in 2020: Mechanistic Understanding and Clinical Recommendations

Drug Metab Dispos. 2021 Oct7; 47(2); 135-144

Abstract

Pharmacokinetic-based drug-drug interaction (DDI) data for drugs approved by the U.S. Food and Drug Administration in 2017 (N = 34) were analyzed using the University of Washington Drug Interaction Database. The mechaniDrug-drug interaction (DDI) data for small molecular drugs approved by the U.S. Food and Drug Administration in 2020 (N = 40) were analyzed using the University of Washington Drug Interaction Database. The mechanism(s) and clinical relevance of these interactions were characterized based on information available in the new drug application reviews. About 180 positive clinical studies, defined as mean area under the curve ratios (AUCRs) {greater than or equal to} 1.25 for inhibition DDIs or pharmacogenetic studies and {less than or equal to} 0.8 for induction DDIs, were then fully analyzed. Oncology was the most represented therapeutic area, including 30% of 2020 approvals. As victim drugs, inhibition and induction of CYP3A explained most of all observed clinical interactions. Three sensitive substrates were identified: avapritinib (CYP3A), lonafarnib (CYP3A), and relugolix (P-gp), with AUCRs of 7.00, 5.07, and 6.25 when co-administered with itraconazole, ketoconazole, and erythromycin, respectively. As precipitants, three drugs were considered strong inhibitors of enzymes (AUCR {greater than or equal to} 5): cedazuridine for cytidine deaminase, and lonafarnib and tucatinib for CYP3A. No drug showed strong inhibition of transporters. No strong inducer of enzymes or transporters was identified. As expected, all DDIs with AUCRs {greater than or equal to} 5 or {less than or equal to} 0.2 and almost all those with AUCRs of 2-5 and 0.2-0.5 triggered dosing recommendations in the drug label. Overall, all 2020 drugs found to be either sensitive substrates or strong inhibitors of enzymes or transporters were oncology treatments, underscoring the need for effective DDI management strategies in cancer patients often receiving poly-therapy. Significance Statement This minireview provides a thorough and specific overview of the most significant pharmacokinetic-based DDI data observed (or expected) with small molecular drugs approved by the U.S. Food and Drug Administration in 2020. It will help to better understand mitigation strategies to manage the DDI risks in the clinic.

Analysis of Drug-Drug Interaction Labeling Language and Clinical Recommendations for Newly approved Drugs Evaluated With Digoxin, Midazolam, and S-Warfarin

Abstract

To best promote drug tolerability and efficacy in the clinic, data from drug-drug interaction (DDI) evaluations and subsequent translation of the results to DDI prevention and/or management strategies must be incorporated into the US Food and Drug Administration (FDA) product labeling in a consistent manner because differences in language might result in varied interpretations. This analysis aimed to assess the consistency in DDI labeling language in New Drug Applications (NDAs).

Systematic Review of Drug Disposition Characteristics of Drugs Most Affected by Hepatic Impairment

Presented virtually at 24th North American ISSX Meeting, September 2021
Jessica Sontheimer, Zoé Borgel, Jingjing Yu, William Copalu, Catherine K. Yeung, Eva Berglund, and Isabelle Ragueneau-Majlessi

2021 ISSX Poster Presentation – Drug Disposition Characteristics and Hepatic Impairment

Abstract

The aim of the study was to systematically review the disposition parameters of drugs most affected by hepatic impairment(HI) and investigate whether there are elimination characteristics (such as enzyme or transporter involvement in drug elimination) that predisposed for a large effect of HI on drug exposure.

Anti-Infective Knowledgebase: Development of a Comprehensive Tool for Understanding the Disposition and the Interaction Potential of Anti-Infective Drugs Used in Low-Income Countries

Presented virtually at 24th North American ISSX Meeting, September 2021
Jingjing Yu,Yan Wang, Cheryl Wu, and Isabelle Ragueneau-Majlessi

2021 ISSX Poster Presentation – Anti-Infective Knowledgbase

Abstract

Patients with infectious diseases in low-income countries (LICs) are often at risk of pharmacokinetic (PK) drug-drug interactions (DDIs). To assist in silico mechanistic modeling and simulations to predict DDI liability and guide optimal management of DDIs, a knowledgebase of anti-infective drugs, specifically treatments for malaria and tuberculosis, has been established.

Mechanisms and clinical significance of pharmacokinetic-based drug-drug interactions with drugs approved by the U.S. Food and Drug Administration in 2020

Presented virtually at the 24th North American ISSX Meeting, September 2021
Jingjing Yu, Yan Wang, and Isabelle Ragueneau-Majlessi

2021 ISSX Poster Presentation – 2020 NDA Clinical DDI Review

Abstract

The aim of the present work was to review pharmacokinetic drug-drug interaction (DDI) data available in New Drug Applications (NDAs) for drugs approved by the US Food and Drug Administration in 2020 and analyze the mechanisms mediating interactions in order to facilitate an optimal management of DDIs in the clinic.

Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients

CPT Pharmacometrics Syst Pharmacol. 2021 Aug;10(8):953-961

Abstract

Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic of current research. Not only can excipients alter the disposition of coformulated drugs, but it is likely that these effects on co-administered drugs can reach to clinical significance leading to potential adverse effects or loss of efficacy. These risks can be evaluated through use of in silico methods of mechanistic modeling, including approaches, such as population pharmacokinetic (PK) and physiologically-based PK modeling, which require a comprehensive understanding of the compounds to ensure accurate predictions. We established a knowledgebase of the available compound (or substance) and interaction-specific parameters with the goal of providing a single source of physiochemical, in vitro, and clinical PK and interaction data of commonly used excipients. To illustrate the utility of this knowledgebase, a model for cremophor EL was developed and used to hypothesize the potential for CYP3A- and P-gp-based interactions as a proof of concept.

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