Literature DB >> 20923246

A quantitative framework and strategies for management and evaluation of metabolic drug-drug interactions in oncology drug development: new molecular entities as object drugs.

Karthik Venkatakrishnan1, Michael D Pickard, Lisa L von Moltke.   

Abstract

This article outlines general strategies for the management and evaluation of pharmacokinetic drug-drug interactions (DDIs) resulting from perturbation of clearance of investigational anticancer drug candidates by concomitantly administered agents in a drug development setting, with a focus on drug candidates that cannot be evaluated in first-in-human studies in healthy subjects. A risk level classification is proposed, based on quantitative integration of knowledge derived from preclinical drug-metabolism studies evaluating the projected percentage contribution [f(i)(%)] of individual molecular determinants (e.g. cytochrome P450 isoenzymes) to the overall human clearance of the investigational agent. The following classification is proposed with respect to susceptibility to DDIs with metabolic inhibitors: a projected maximum DDI expected to result in a ≤1.33-fold increase in exposure, representing a low level of risk; a projected maximum DDI expected to result in a >1.33-fold but <2-fold increase in exposure, representing a moderate level of risk; and a projected maximum DDI expected to result in a ≥2-fold increase in exposure, representing a potentially high level of risk. For DDIs with metabolic inducers, the following operational classification is proposed, based on the sum of the percentage contributions of enzymes that are inducible via a common mechanism to the overall clearance of the investigational drug: <<25%, representing a low level of risk; <50%, representing a moderate level of risk; and ≥50%, representing a potentially high level of risk. To ensure patient safety and to minimize bias in determination of the recommended phase II dose (RP2D), it is recommended that strong and moderate inhibitors and inducers of the major contributing enzyme are excluded in phase I dose-escalation studies of high-risk compounds, whereas exclusion of strong inhibitors and inducers of the contributing enzyme(s) is recommended as being sufficient for moderate-risk compounds. For drugs that will be investigated in diseases such as glioblastoma, where there may be relatively frequent use of enzyme-inducing antiepileptic agents (EIAEDs), a separate dose-escalation study in this subpopulation is recommended to define the RP2D. For compounds in the high-risk category, if genetic deficiencies in the activity of the major drug-metabolizing enzyme are known, it is recommended that poor metabolizers be studied separately to define the RP2D for this subpopulation. Whereas concomitant medication exclusion criteria that are utilized in the phase I dose-escalation studies will probably also need to be maintained for high-risk compounds in phase II studies unless the results of a clinical DDI study indicate the absence of a clinically relevant interaction, these exclusion criteria can potentially be relaxed beyond phase I for moderate-risk compounds, if supported by the nature of clinical toxicities and the understanding of the therapeutic index in phase I. Adequately designed clinical DDI studies will not only inform potential relaxation of concomitant medication exclusion criteria in later-phase studies but, importantly, will also inform the development of pharmacokinetically derived dose-modification guidelines for use in clinical practice when coupled with adequate safety monitoring, as illustrated in the prescribing guidance for many recently approved oncology therapeutics.

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Year:  2010        PMID: 20923246     DOI: 10.2165/11536740-000000000-00000

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  80 in total

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Journal:  Drug Metab Dispos       Date:  2006-04-19       Impact factor: 3.922

2.  Impact of ignoring extraction ratio when predicting drug-drug interactions, fraction metabolized, and intestinal first-pass contribution.

Authors:  Brian J Kirby; Jashvant D Unadkat
Journal:  Drug Metab Dispos       Date:  2010-08-19       Impact factor: 3.922

Review 3.  Membrane transporters in drug development.

Authors:  Kathleen M Giacomini; Shiew-Mei Huang; Donald J Tweedie; Leslie Z Benet; Kim L R Brouwer; Xiaoyan Chu; Amber Dahlin; Raymond Evers; Volker Fischer; Kathleen M Hillgren; Keith A Hoffmaster; Toshihisa Ishikawa; Dietrich Keppler; Richard B Kim; Caroline A Lee; Mikko Niemi; Joseph W Polli; Yuichi Sugiyama; Peter W Swaan; Joseph A Ware; Stephen H Wright; Sook Wah Yee; Maciej J Zamek-Gliszczynski; Lei Zhang
Journal:  Nat Rev Drug Discov       Date:  2010-03       Impact factor: 84.694

4.  Use of sandwich-cultured human hepatocytes to predict biliary clearance of angiotensin II receptor blockers and HMG-CoA reductase inhibitors.

Authors:  Koji Abe; Arlene S Bridges; Kim L R Brouwer
Journal:  Drug Metab Dispos       Date:  2008-12-15       Impact factor: 3.922

Review 5.  Predicting drug disposition via application of a Biopharmaceutics Drug Disposition Classification System.

Authors:  Leslie Z Benet
Journal:  Basic Clin Pharmacol Toxicol       Date:  2009-12-07       Impact factor: 4.080

Review 6.  Genetic variability in CYP3A5 and its possible consequences.

Authors:  Hong-Guang Xie; Alastair J J Wood; Richard B Kim; C Michael Stein; Grant R Wilkinson
Journal:  Pharmacogenomics       Date:  2004-04       Impact factor: 2.533

Review 7.  Tamoxifen pharmacogenomics: the role of CYP2D6 as a predictor of drug response.

Authors:  M P Goetz; A Kamal; M M Ames
Journal:  Clin Pharmacol Ther       Date:  2007-09-19       Impact factor: 6.875

8.  Apparent high CYP3A5 expression is required for significant metabolism of vincristine by human cryopreserved hepatocytes.

Authors:  Jennifer B Dennison; Michael A Mohutsky; Robert J Barbuch; Steven A Wrighton; Stephen D Hall
Journal:  J Pharmacol Exp Ther       Date:  2008-07-23       Impact factor: 4.030

9.  A proposal for a pharmacokinetic interaction significance classification system (PISCS) based on predicted drug exposure changes and its potential application to alert classifications in product labelling.

Authors:  Akihiro Hisaka; Makiko Kusama; Yoshiyuki Ohno; Yuichi Sugiyama; Hiroshi Suzuki
Journal:  Clin Pharmacokinet       Date:  2009       Impact factor: 6.447

10.  The effect of ketoconazole on the pharmacokinetics and pharmacodynamics of ixabepilone: a first in class epothilone B analogue in late-phase clinical development.

Authors:  Sanjay Goel; Marvin Cohen; S Nilgün Cömezoglu; Lionel Perrin; François André; David Jayabalan; Lisa Iacono; Adriana Comprelli; Van T Ly; Donglu Zhang; Carrie Xu; W Griffith Humphreys; Hayley McDaid; Gary Goldberg; Susan B Horwitz; Sridhar Mani
Journal:  Clin Cancer Res       Date:  2008-05-01       Impact factor: 13.801

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  5 in total

1.  Drug-drug interaction potential of marketed oncology drugs: in vitro assessment of time-dependent cytochrome P450 inhibition, reactive metabolite formation and drug-drug interaction prediction.

Authors:  Jane R Kenny; Sophie Mukadam; Chenghong Zhang; Suzanne Tay; Carol Collins; Aleksandra Galetin; S Cyrus Khojasteh
Journal:  Pharm Res       Date:  2012-03-14       Impact factor: 4.200

2.  Designing phase I oncology dose escalation using dose-exposure-toxicity models as a complementary approach to model-based dose-toxicity models.

Authors:  Kristyn Pantoja; Shankar Lanke; Alain Munafo; Anja Victor; Christina Habermehl; Armin Schueler; Karthik Venkatakrishnan; Pascal Girard; Kosalaram Goteti
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-08-05

3.  Effects of Strong CYP3A Inhibition and Induction on the Pharmacokinetics of Ixazomib, an Oral Proteasome Inhibitor: Results of Drug-Drug Interaction Studies in Patients With Advanced Solid Tumors or Lymphoma and a Physiologically Based Pharmacokinetic Analysis.

Authors:  Neeraj Gupta; Michael J Hanley; Karthik Venkatakrishnan; Alberto Bessudo; Drew W Rasco; Sunil Sharma; Bert H O'Neil; Bingxia Wang; Guohui Liu; Alice Ke; Chirag Patel; Karen Rowland Yeo; Cindy Xia; Xiaoquan Zhang; Dixie-Lee Esseltine; John Nemunaitis
Journal:  J Clin Pharmacol       Date:  2017-08-11       Impact factor: 3.126

Review 4.  Toward Optimum Benefit-Risk and Reduced Access Lag For Cancer Drugs in Asia: A Global Development Framework Guided by Clinical Pharmacology Principles.

Authors:  K Venkatakrishnan; C Burgess; N Gupta; A Suri; T Takubo; X Zhou; D DeMuria; M Lehnert; K Takeyama; S Singhvi; A Milton
Journal:  Clin Transl Sci       Date:  2016-02-05       Impact factor: 4.689

5.  Effects of rifampin, itraconazole and esomeprazole on the pharmacokinetics of alisertib, an investigational aurora a kinase inhibitor in patients with advanced malignancies.

Authors:  Xiaofei Zhou; Shubham Pant; John Nemunaitis; A Craig Lockhart; Gerald Falchook; Todd M Bauer; Manish Patel; John Sarantopoulos; Michael Bargfrede; Andreas Muehler; Lakshmi Rangachari; Bin Zhang; Karthik Venkatakrishnan
Journal:  Invest New Drugs       Date:  2017-08-30       Impact factor: 3.850

  5 in total

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