Evaluation of Various Static In Vitro–In Vivo Extrapolation Models for Risk Assessment of the CYP3A Inhibition Potential of an Investigational Drug

Vieira, L T; Kirby, Brian J.; Ragueneau‐Majlessi, Isabelle; Galetin, Aleksandra; Chien, Jenny Y.; Einolf, Heidi J.; Fahmi, Odette A.; Fischer, Volker; Fretland, Adrian J.; Grime, Ken; Hall, Stephen D.; Higgs, Richard E.; Plowchalk, David R.; Riley, Robert J.; Seibert, Eleanore; Skordos, Konstantine W.; Snoeys, Jan; Venkatakrishnan, Karthik; Waterhouse, T. H.; Obach, R. Scott; Berglund, Eva Gil; Zhang, L.; Zhao, Ping; Reynolds, Kellie S.; Huang, Shiew‐Mei

doi:10.1038/clpt.2013.187

Cited by 86 publications

(105 citation statements)

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“…Researchers are also encouraged to read comprehensive recent publications on victim DDIs resulting from modulation of transporters (Lai and Hsiao, 2014;Nakanishi and Tamai, 2015). Other topics not within the scope of this manuscript but comprehensively covered in recent publications include evaluation of NMEs as perpetrators of DDIs (Zhao et al, 2014;Varma et al, 2015) and assessment of performance of static and dynamic models commonly used for successful prediction of clinical DDIs (Vieira et al, 2014). This manuscript will summarize the commonly adopted industry practices, which include in vitro methods, in combination with in vivo preclinical and clinical studies, along with modeling and simulation, to best estimate the potential of a NME to be a victim of P450 and non-P450-mediated metabolic DDIs in the clinic.…”

Section: Introductionmentioning

confidence: 99%

“…This is commonly done via evaluation of: 1) in vitro f m in human-derived matrices to understand whether one or multiple P450 or non-P450 enzymes are involved in a NME's metabolism and 2) in vivo f CL information in preclinical species and whether in vitro-in vivo correlation (IVIVC) holds in preclinical species to gain qualitative understanding of whether metabolism or biliary or renal excretion is predominant. The combined information obtained is used as an early guide to evaluate victim DDI risk in the clinic using various predictive models (Vieira et al, 2014). Once the f CL,metabolism is available from human 14 C-ADME study and f m , enzyme is quantitatively available from a clinical DDI study (or PK study in genotyped population), the victim DDI predictions are further refined to predict additional and/or potentially complex DDIs before the NME being administered in larger clinical trials (Lu et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions--an Industry Perspective

Bohnert¹,

Patel²,

Templeton³

et al. 2016

Drug Metabolism and Disposition

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Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (f CL ), estimation of fractional contribution of metabolizing enzyme toward metabolism (f m ), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify f CL and f m , 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions--an Industry Perspective

Bohnert¹,

Patel²,

Templeton³

et al. 2016

Drug Metabolism and Disposition

View full text Add to dashboard Cite

show abstract

“…On the other hand, the clinical effects were clearly overestimated using [I]/K i values (2.41, 3.68 and 3.95 respectively). This indicates that factors such as protein binding which affects 'enzyme-available' inhibitor concentrations, as well as inhibition across multiple organs, could potentially complicate the predictive power of the in vitro models, and models that take the relevant confounding factors into account should provide better prediction for in vitro-in vivo scaling [19].…”

Section: In Vitro Approachesmentioning

confidence: 99%

In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

et al. 2017

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-In vitro and in silico models of drug metabolism are utilized regularly in the drug research and development as tools for assessing pharmacokinetic variability and drug-drug interaction risk. The use of in vitro and in silico predictive approaches offers advantages including guiding rational design of clinical drug-drug interaction studies, minimization of human risk in the clinical trials, as well as cost and time savings due to lesser attrition during compound development process. This article gives a review of some of the current in vitro and in silico methods used to characterize cytochrome P450(CYP)-mediated drug metabolism for estimating pharmacokinetic variability and the magnitude of drug-drug interactions. Examples demonstrating the predictive applicability of specific in vitro and in silico approaches are described. Commonly encountered confounding factors and sources of bias and error in these approaches are presented. With the advent of technological advancement in high throughput screening and computer power, the in vitro and in silico methods are becoming more efficient and reliable and will continue to contribute to the process of drug discovery, development and ultimately safer and more effective pharmacotherapy.

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“…[11][12][13] The ratio of intrinsic clear- ance value of the substrate for specific CYP reaction in the presence or absence of the gastrointestinal drug (R value) was calculated as follows:…”

Section: Prediction Of Drug Interactions In Vivomentioning

confidence: 99%

Inhibitory Effects of Gastrointestinal Drugs on CYP Activities in Human Liver Microsomes

Iwase

Nishimura

Kurata

et al. 2017

Biological & Pharmaceutical Bulletin

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OTC drugs have an important role in self-medication. However, the pharmacokinetic properties of some OTC drugs have not been fully investigated and reports concerning their drug interactions are insufficient. Several gastrointestinal drugs are available as OTC drugs. Because of their pharmacological properties, these drugs are often used concomitantly with other drugs. Therefore, it is important to predict the possible drug interactions among these drugs. In the current study, we investigated the inhibitory effects of five gastrointestinal drugs, namely loperamide, oxethazaine, papaverine, pirenzepine, and trimebutine, on CYP activities in human liver microsomes. Furthermore, we calculated the ratio of the intrinsic clearance of each CYP substrate in the presence or absence of the gastrointestinal drugs. The possibility of drug interactions in vivo was predicted by cut-off criteria. CYP3A4 activity was markedly inhibited by trimebutine, papaverine, and oxethazaine. Their inhibitory properties were competitive and the K i values were 6.56, 12.8, and 3.08 µM, respectively. Alternative R values of CYP3A4 exceeded the cut-off level. These results suggested that drug interactions mediated by CYP3A4 may occur during treatment with these gastrointestinal drugs, necessitating the confirmation of the clinical significance of these drug interactions to prevent unexpected adverse effects. Key words gastrointestinal drug; OTC drug; drug interaction; CYPIn recent years, people have become increasingly interested in their own health due to a rapidly aging society and/or the increase of lifestyle-related diseases. As a result, the concept of self-care, which includes self-medication, has attracted popular attention. Self-medication is defined as the selection and use of medicines by individuals to treat self-recognized illnesses or symptoms. 1) Self-medication includes the use of OTC drugs under the advice of healthcare professionals such as pharmacists.2) Therefore, OTC drugs play an important role in self-medication. OTC drugs are considered relatively safer than ethical drugs. However, many OTC drugs, especially those developed in the distant past, have not had their pharmacokinetic properties sufficiently studied. They may be safe to use alone; however, there is no evidence to suggest their safety when combined with other drugs.Many drug interactions affect specific metabolic processes, especially those mediated by CYP. CYP-mediated drug interactions are roughly classified into enzyme inhibition and enzyme induction. Most are based on enzyme inhibition, with many documented clinically significant cases. Therefore, it is important to examine whether OTC drugs have inhibitory effects on CYP activity.A recent study reported that diphenhydramine interacted with metoprolol via CYP2D6 inhibition.3) Diphenhydramine potently inhibited metoprolol α-hydroxylation in vitro. Moreover, a clinical study found that diphenhydramine decreased metoprolol metabolic clearance 2.5-fold in CYP2D6 extensive metabolizers.4) Diphenhydramine, a fir...

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Evaluation of Various Static In Vitro–In Vivo Extrapolation Models for Risk Assessment of the CYP3A Inhibition Potential of an Investigational Drug

Cited by 86 publications

References 28 publications

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions--an Industry Perspective

Evaluation of a New Molecular Entity as a Victim of Metabolic Drug-Drug Interactions--an Industry Perspective

In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

Inhibitory Effects of Gastrointestinal Drugs on CYP Activities in Human Liver Microsomes

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