Tag: drug interactions

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Analysis of in vitro- to-in vivo predictions of transporter-mediated inhibition drug interactions for drugs approved by the USA Food and Drug Administration between 2013 and 2016

Presented at Asia Pacific ISSX conference, May 2018, Hangzhou City, China
Jingjing Yu and Isabelle Ragueneau-Majlessi

2018 Asia Pacific ISSX Poster Presentation – Transporter-mediated DDIs

Abstract

The present work aimed to systematically review transporter-based in vitro and clinical inhibition evaluations of drugs approved by the U.S. Food and Drug Administration (FDA) from 2013 to 2016. In vitro inhibition parameters, pharmacokinetics, and clinical drug-drug interaction (DDI) studies available in the New Drug Application (NDA) reviews were analyzed using the University of Washington Drug Interaction Database. Following recommendations from the 2012 FDA DDI guidance, in vitro to in vivo prediction estimates were calculated for the transporters the most often studied.

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Risk of Clinically Relevant Pharmacokinetic-Based Drug-Drug Interactions with Drugs Approved by the U.S. Food and Drug Administration Between 2013 and 2016

Drug Metab Dispos. 2018 Jun; 46(6): 835-845.
Published online 2018 Mar 23

Abstract

A total of 103 drugs (including 14 combination drugs) were approved by the U.S. Food and Drug Administration from 2013 to 2016. Pharmacokinetic-based drug interaction profiles were analyzed using the University of Washington Drug Interaction Database, and the clinical relevance of these observations was characterized based on information from new drug application reviews. CYP3A was involved in approximately two-thirds of all drug-drug interactions (DDIs). Transporters (alone or with enzymes) participated in about half of all interactions, but most of these were weak-to-moderate interactions. When considered as victims, eight new molecular entities (NMEs; cobimetinib, ibrutinib, isavuconazole, ivabradine, naloxegol, paritaprevir, simeprevir, and venetoclax) were identified as sensitive substrates of CYP3A, two NMEs (pirfenidone and tasimelteon) were sensitive substrates of CYP1A2, one NME (dasabuvir) was a sensitive substrate of CYP2C8, one NME (eliglustat) was a sensitive substrate of CYP2D6, and one NME (grazoprevir) was a sensitive substrate of OATP1B1/3 (with changes in exposure greater than 5-fold when coadministered with a strong inhibitor). Approximately 75% of identified CYP3A substrates were also substrates of P-glycoprotein. As perpetrators, most clinical DDIs involved weak-to-moderate inhibition or induction. Only idelalisib showed strong inhibition of CYP3A, and lumacaftor behaved as a strong CYP3A inducer. Among drugs with large changes in exposure (≥5-fold), whether as victim or perpetrator, the most-represented therapeutic classes were antivirals and oncology drugs, suggesting a significant risk of clinical DDIs in these patient populations.

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Understanding the risk of clinically significant pharmacokinetic-based drug-drug interactions with drugs newly approved by the US FDA – a review of recent new drug applications (2013-2016)

Presented at ISSX conference, September 2017, Providence, RI, USA
Jingjing Yu and Isabelle Ragueneau-Majlessi

2017 ISSX Poster Presentation – 2013-2016 NDA Review

Abstract

The aim of the present work was to systematically review pharmacokinetic-based drug-drug interaction (DDI) data available in the most recent (2013-2016) New Drug Applications (NDAs) and highlight significant findings. The University of Washington Metabolism and Transport Drug Interaction Database was used to extract the results of metabolism, transport, and clinical DDI studies. All the DDI studies (new molecular entity (NME) as victim or perpetrator) with AUC changes ≥ 2-fold or < 2-fold but triggering dose recommendations were included in the analysis.

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Identification and evaluation of clinical substrates of organic anion transporting polypeptides 1B1 and 1B3

Presented at ISSX conference, September 2017, Providence, RI, USA
Savannah J. McFeely, Yu, Tasha K. Ritchie, Jingjing Yu, Eva Gil Berglund, Anna Nordmark, and Isabelle Ragueneau-Majlessi

2017 ISSX Poster Presentation – Evaluation of Clinical Substrates of OATP1B1/3

Abstract

The aim of this work was twofold: i) Provide a thorough analysis of the available in vitro and in vivo data regarding OATP1B1/1B3 substrates, ii)Propose the most sensitive and selective probe markers of OATP1B1/1B3 activity.

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Intestinal Drug Interactions Mediated by OATPs: A Systematic Review of Preclinical and Clinical Findings

J Pharm Sci. 2017 Sep; 106(9); 2312-2325
Published online 2017 Apr 13

Abstract

In recent years, an increasing number of clinical drug-drug interactions (DDIs) have been attributed to inhibition of intestinal organic anion-transporting polypeptides (OATPs); however, only a few of these DDI results were reflected in drug labels. This review aims to provide a thorough analysis of intestinal OATP-mediated pharmacokinetic-based DDIs, using both in vitro and clinical investigations, highlighting the main mechanistic findings and discussing their clinical relevance. On the basis of pharmacogenetic and clinical DDI results, a total of 12 drugs were identified as possible clinical substrates of OATP2B1 and OATP1A2. Among them, 3 drugs, namely atenolol, celiprolol, and fexofenadine, have emerged as the most sensitive substrates to evaluate clinical OATP-mediated intestinal DDIs when interactions with P-glycoprotein by the test compound can be ruled out. With regard to perpetrators, 8 dietary or natural products and 1 investigational drug, ronacaleret (now terminated), showed clinical intestinal inhibition attributable to OATPs, producing ≥20% decreases in area under the plasma concentration-time curve of the co-administered drug. Common juices, such as apple juice, grapefruit juice, and orange juice, are considered potent inhibitors of intestinal OATP2B1 and OATP1A2 (decreasing exposure of the co-administered substrate by ∼85%) and may be adequate prototype inhibitors to investigate intestinal DDIs mediated by OATPs.

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Detailed Evaluation of Pharmacokinetic-based Drug-drug Interaction Data Contained in New Drug and Biologic License Applications of Drugs Approved by the U.S. FDA in 2015

Presented at ASCPT conference, March 2017, Washington, DC, USA
Jingjing Yu, Zhu Zhou, Katie Owens, Tasha K. Ritchie, and Isabelle Ragueneau-Majlessi

2017 ASCPT Poster Presentation – 2015 NDA Review

Abstract

The aim of the present work was to perform a systematic analysis of metabolism, transport, and drug interaction data available in New Drug Applications (NDAs) and Biologic License Applications (BLAs) of drugs approved in 2015, and highlight significant findings.

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What Can Be Learned From Recent New Drug Applications? A Systematic Review of Drug Interaction Data for Drugs Approved by the US FDA in 2015

Drug Metab Dispos. 2017 Jan; 45(1); 86-108.
Published online 2016 Nov 7

Abstract

As a follow up to previous reviews, the aim of the present analysis was to systematically examine all drug metabolism, transport, pharmacokinetics (PK), and drug-drug interaction (DDI) data available in the 33 new drug applications (NDAs) approved by the Food and Drug Administration (FDA) in 2015, using the University of Washington Drug Interaction Database, and to highlight the significant findings. In vitro, a majority of the new molecular entities (NMEs) were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, 95 clinical DDI studies displayed positive PK interactions, with an area under the curve (AUC) ratio ≥ 1.25 for inhibition or ≤ 0.8 for induction. When NMEs were considered as victim drugs, 21 NMEs had at least one positive clinical DDI, with three NMEs shown to be sensitive substrates of CYP3A (AUC ratio ≥ 5 when coadministered with strong inhibitors): cobimetinib, isavuconazole (the active metabolite of prodrug isavuconazonium sulfate), and ivabradine. As perpetrators, nine NMEs showed positive inhibition and three NMEs showed positive induction, with some of these interactions involving both enzymes and transporters. The most significant changes for inhibition and induction were observed with rolapitant, a moderate inhibitor of CYP2D6 and lumacaftor, a strong inducer of CYP3A. Physiologically based pharmacokinetics simulations and pharmacogenetics studies were used for six and eight NMEs, respectively, to inform dosing recommendations. The effects of hepatic or renal impairment on the drugs’ PK were also evaluated to support drug administration in these specific populations.

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Investigating ABCB1-Mediated Drug-Drug Interactions: Considerations for In Vitro and In Vivo Assay Design

Curr Drug Metab. 2016; 17(5); 430-55.
Published online 2015 Sep 30

Abstract

Background

ABCB1 is a key ABC efflux transporter modulating the pharmacokinetics of a large percentage of drugs. ABCB1 is also a site of transporter mediated drug-drug interactions (tDDI). It is the transporter most frequently tested for tDDIs both in vitro and in the clinic.

Objective

Understanding the limitations of various in vitro and in vivo models, therefore, is crucial. In this review we cover regulatory aspects of ABCB1 mediated drug transport as well as inhibition and the available models and methods. We also discuss protein structure and mechanistic aspects of transport as ABCB1 displays complex kinetics that involves multiple binding sites, potentiation of transport and probe-dependent IC50 values.

Results

Permeability of drugs both passive and mediated by transporters is also a covariate that modulates apparent kinetic values. Levels of expression as well as lipid composition of the expression system used in in vitro studies have also been acknowledged as determinates of transporter activity. ABCB1-mediated clinical tDDIs are often complex as multiple transporters as well as metabolic enzymes may play a role. This complexity often masks the role of ABCB1 in tDDIs.

Conclusion

It is expected that utilization of in vitro data will further increase with the refinement of simulations. It is also anticipated that transporter humanized preclinical models have a significant impact and utility.

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Key Findings From Preclinical and Clinical Drug Interaction Studies Presented in New Drug and Biological License Applications Approved by the Food and Drug Administration in 2014

Drug Metab Dispos. 2016 Jan; 44(1); 83-101.
Published online 2015 Sep 30

Abstract

Regulatory approval documents contain valuable information, often not published, to assess the drug-drug interaction (DDI) profile of newly marketed drugs. This analysis aimed to systematically review all drug metabolism, transport, pharmacokinetics, and DDI data available in the new drug applications and biologic license applications approved by the U.S. Food and Drug Administration in 2014, using the University of Washington Drug Interaction Database, and to highlight the significant findings. Among the 30 new drug applications and 11 biologic license applications reviewed, 35 new molecular entities (NMEs) were well characterized with regard to drug metabolism, transport, and/or organ impairment and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, when NMEs were considered as victim drugs, 16 NMEs had at least one in vivo DDI study with a clinically significant change in exposure (area under the time-plasma concentration curve or Cmax ratio ≥2 or ≤0.5), with 6 NMEs shown to be sensitive substrates of cytochrome P450 enzymes (area under the time-plasma concentration curve ratio ≥5 when coadministered with potent inhibitors): paritaprevir and naloxegol (CYP3A), eliglustat (CYP2D6), dasabuvir (CYP2C8), and tasimelteon and pirfenidone (CYP1A2). As perpetrators, seven NMEs showed clinically significant inhibition involving both enzymes and transporters, although no clinically significant induction was observed. Physiologically based pharmacokinetic modeling and pharmacogenetics studies were used for six and four NMEs, respectively, to optimize dosing recommendations in special populations and/or multiple impairment situations. In addition, the pharmacokinetic evaluations in patients with hepatic or renal impairment provided useful quantitative information to support drug administration in these fragile populations.

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Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Drug Metab Dispos. 2015 Nov; 43(11); 1823-37.
Published online 2015 Aug 21

Abstract

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms “PBPK” and “physiologically based pharmacokinetic model” to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.