Tag: drug interactions

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Understanding the role of CYP3A in the metabolism of kinase inhibitors marketed in the past decade to better manage the risk of clinical drug-drug interactions.

Presented at the 25th North American ISSX Meeting, September 2023
Jingjing Yu, Sophie Argon, Katie Owens, Ichiko Petrie, and Isabelle Ragueneau-Majlessi

2023 ISSX Poster Presentation – CYP3A-Kinase inhibitors

Abstract

Kinase inhibitors (KIs) are among the most represented therapeutic areas for novel drugs approved in recent years. In the present analysis, drug metabolism data for all KIs approved in the US since 2011 were reviewed. Mechanistic clinical drug interaction studies with CYP3A perpetrators were fully analyzed using Certara’s Drug Interaction Database (DIDB®). The mechanism(s) and clinical relevance of these interactions were characterized based on information available in the new drug application reviews.

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Risk of pharmacokinetic drug-drug interactions with novel drugs approved by the US FDA in 2022: a detailed review of DDI data from NDA documentation.

Presented at the 25th North American ISSX Meeting, September 2023
Jingjing Yu, Yan Wang, and Isabelle Ragueneau-Majlessi

2023 ISSX Poster Presentation – 2022 NDA Reviews

Abstract

Understanding the ADME processes involved in pharmacokinetic-based drug-drug interactions (DDIs) is critical to facilitate an optimal management of DDIs in the clinic. In the present work, drug metabolism and transport in vitro and in vivo data for small molecular drugs approved by the U.S. Food and Drug Administration in 2022 (N=22) were analyzed using the Certara Drug Interaction Database. The mechanism(s) and clinical relevance of these interactions were characterized based on information available in the new drug application (NDA) reviews.

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Seeing what is behind the smokescreen: A systematic review of methodological aspects of smoking interaction studies over the last three decades and implications for future clinical trials

Clin Transl Sci. 2023 May;16(5):742-758

Abstract

Smoking drug interaction studies represent a common approach for the clinical investigation of CYP1A2 induction. Despite this important role, they remain an “orphan topic” in the existing regulatory framework of drug interaction studies, and important methodological aspects remain unaddressed. The University of Washington Drug Interaction Database (DIDB) was used to systematically review the published literature on dedicated smoking pharmacokinetic interaction studies in healthy subjects (1990 to 2021, inclusive). Various methodological aspects of identified studies were reviewed. A total of 51 studies met all inclusion criteria and were included in the analysis. Our review revealed that methods applied in smoking interaction studies are heterogeneous and often fall short of established methodological standards of other interaction trials. Methodological deficiencies included incomplete description of study populations, poor definition and lack of objective confirmation of smoker and nonsmoker characteristics, under-representation of female subjects, small sample sizes, frequent lack of statistical sample size planning, frequent lack of use of existing markers of nicotine exposure and CYP1A2 activity measurements, and frequent lack of control of extrinsic CYP1A2 inducing or inhibiting factors. The frequent quality issues in the assessment and reporting of smoking interaction trials identified in this review call for a concerted effort in this area, if the results of these studies are meant to be followed by actionable decisions on dose optimization, when needed, for the effects of smoking on CYP1A2 victim drugs in smokers.

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Strong Pharmacokinetic Drug-Drug Interactions With Drugs Approved by the US Food and Drug Administration in 2021: Mechanisms and Clinical Implications

Clin Ther. 2022 Oct6;S0149-2918(22)00323-X

Abstract

This analysis aimed to identify all strong drug-drug interactions (DDIs) associated with drugs approved by the US Food and Drug Administration (FDA) in 2021.

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Enzyme- and Transporter-Mediated Clinical Drug Interactions with Drugs by the U.S. Food and Drug Administration in 2021: What Can be Learned from New Drug applications Reviews?

Presented at the ISSX/MDO Meeting, September 2022
Jingjing Yu, Yan Wang, and Isabelle Ragueneau-Majlessi

2022 ISSX Poster Presentation – 2021 NDA Reviews

Abstract

 The mechanistic evaluation of enzyme- and transporter-based drug-drug interactions (DDIs) during drug development is critical to support management strategies in the clinic.

The objectives of the study were to review pharmacokinetic-based clinical DDI data available in the new drug application (NDA) reviews for drugs approved by the FDA in 2021, and to understand the main mechanisms that mediate interactions resulting in label recommendations. 

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Exploring the Relationship of Drug BCS Classification, Food Effect, and Gastric pH-Dependent Drug Interactions

AAPS J. 2021 Dec 27;24(1):16

Abstract

Food effect (FE) and gastric pH-dependent drug-drug interactions (DDIs) are both absorption-related. Here, we evaluated if Biopharmaceutics Classification System (BCS) classes may be correlated with FE or pH-dependent DDIs. Trends in FE data were investigated for 170 drugs with clinical FE studies from the literature and new drugs approved from 2013 to 2019 by US Food and Drug Administration. A subset of 38 drugs was also evaluated to determine whether FE results can inform the need for a gastric pH-dependent DDI study. The results of FE studies were defined as no effect (AUC ratio 0.80-1.25), increased exposure (AUC ratio ≥1.25), or decreased exposure (AUC ratio ≤0.8). Drugs with significantly increased exposure FE (AUC ratio ≥2.0; N=14) were BCS Class 2 or 4, while drugs with significantly decreased exposure FE (AUC ratio ≤0.5; N=2) were BCS Class 1/3 or 3. The lack of FE was aligned with the lack of a pH-dependent DDI for all 7 BCS Class 1 or 3 drugs as expected. For the 13 BCS Class 2 or 4 weak base drugs with an increased exposure FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). Among the 16 BCS Class 2 or 4 weak base drugs with no FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). FE appears to have limited correlation with BCS classes except for BCS Class 1 drugs, confirming that multiple physiological mechanisms can impact FE. Lack of FE does not indicate absence of pH-dependent DDI for BCS Class 2 or 4 drugs.

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Evaluating the feasibility of performing pharmacogenetic guided-medication therapy management in a retirement community: A prospective, single arm study

J Am Coll Clin Pharm. 2021;1-11
  • doi: 10.1002/jac5.1570
  • Semantic Scholar

    • Abstract

    New drug application reviews contain critical drug interaction study results with newly approved drugs tested both as victims and as perpetrators of drug-drug interactions (DDIs). Pharmacokinetic-based DDI data for drugs approved by the US Food and Drug Administration in 2013–2017 (N = 137) were analyzed using the University of Washington Drug Interaction Database. For the largest metabolism- and transporter-based drug interactions, defined as a change in exposure ≥ 5-fold in victim drugs, the mechanisms and clinical relevance were characterized. Consistent with the major role of CYP3A in drug disposition, CYP3A inhibition and induction explained a majority of the observed interactions (new drugs as victims or as perpetrators). However, transporter-mediated interactions were also prevalent, with OATP1B1/1B3 playing a significant role. As victims, 17 and 4 new molecular entities (NMEs) were identified to be sensitive substrates of enzymes and transporters, respectively. When considered as perpetrators, three drugs showed strong inhibition of CYP3A, one was a strong CYP3A inducer, and two showed strong inhibition of transporters (OATP1B1/1B3 and/or BCRP). All DDIs with AUC changes ≥ 5-fold had labeling recommendations in their respective drug labels, contraindicating or limiting the coadministration with known substrates or perpetrators of the enzyme/transporter involved. The majority of sensitive substrates or strong inhibitors were oncology and antiviral treatments, suggesting a significant risk of DDIs in these patient populations for whom therapeutic management is already complex due to poly-therapy. Pharmacogenetic studies and physiologically based pharmacokinetic models were commonly used to assess the drug interaction potential in specific populations and clinical scenarios. Finally, absorption-based DDIs were evaluated in approximately 30% of drug applications, and 14 NMEs had label recommendations based on the results.

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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.

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

    Clin Ther. 2021 Nov;43(11):2032-2039

    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).

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    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.