Literature DB >> 25666843

Application of Pharmacokinetic-Pharmacodynamic Modeling and Simulation for Antibody-Drug Conjugate Development.

Aman P Singh1, Young G Shin2, Dhaval K Shah3.   

Abstract

Characterization and prediction of the pharmacokinetics (PK) and pharmacodynamics (PD) of Antibody-Drug Conjugates (ADCs) is challenging, since it requires simultaneous quantitative understanding about the PK-PD properties of three different molecular species i.e., the monoclonal antibody, the drug, and the conjugate. Mathematical modeling and simulation provides an excellent tool to overcome these challenges, as it can simultaneously integrate the PK-PD of ADCs and their components in a quantitative manner. Additionally, the computational PK-PD models can also serve as a cornerstone for the model-based drug development and preclinical-to-clinical translation of ADCs. To provide an overview of this subject matter, this manuscript reviews the PK-PD models applicable to ADCs. Additionally, the usage of these models during different drug development stages (i.e., discovery, preclinical development, and clinical development) is also emphasized. The importance of PK-PD modeling and simulation in making rationale go/no-go decisions throughout the drug development process is also highlighted. There is an array of PK-PD models available, ranging from the systems models specifically developed for ADCs to the empirical models applicable to all chemotherapeutic agents, which one can employ for ADCs. The decision about which model to choose depends on the questions to be answered, time at hand, and resources available.

Keywords:  PK-PD; antibody-drug conjugate (ADC); model based drug development; modeling and simulation; pharmacodynamics; pharmacokinetics; preclinical-to-clinical translation

Mesh:

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Year:  2015        PMID: 25666843     DOI: 10.1007/s11095-015-1626-1

Source DB:  PubMed          Journal:  Pharm Res        ISSN: 0724-8741            Impact factor:   4.200


  39 in total

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Authors:  D E Mager; W J Jusko
Journal:  J Pharmacokinet Pharmacodyn       Date:  2001-12       Impact factor: 2.745

2.  Towards a platform PBPK model to characterize the plasma and tissue disposition of monoclonal antibodies in preclinical species and human.

Authors:  Dhaval K Shah; Alison M Betts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-12-06       Impact factor: 2.745

3.  Bioanalysis of antibody-drug conjugates: American Association of Pharmaceutical Scientists Antibody-Drug Conjugate Working Group position paper.

Authors:  Boris Gorovits; Stephen C Alley; Sanela Bilic; Brian Booth; Surinder Kaur; Phillip Oldfield; Shobha Purushothama; Chetana Rao; Stacy Shord; Patricia Siguenza
Journal:  Bioanalysis       Date:  2013-05       Impact factor: 2.681

4.  Maturing antibody-drug conjugate pipeline hits 30.

Authors:  Asher Mullard
Journal:  Nat Rev Drug Discov       Date:  2013-05       Impact factor: 84.694

5.  Modeling the efficacy of trastuzumab-DM1, an antibody drug conjugate, in mice.

Authors:  Nelson L Jumbe; Yan Xin; Douglas D Leipold; Lisa Crocker; Debra Dugger; Elaine Mai; Mark X Sliwkowski; Paul J Fielder; Jay Tibbitts
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-04-28       Impact factor: 2.745

6.  Physiologically based pharmacokinetic model for topotecan in mice.

Authors:  Dhaval K Shah; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-11-20       Impact factor: 2.745

7.  A population pharmacokinetic/pharmacodynamic model of thrombocytopenia characterizing the effect of trastuzumab emtansine (T-DM1) on platelet counts in patients with HER2-positive metastatic breast cancer.

Authors:  Brendan C Bender; Franziska Schaedeli-Stark; Reinhold Koch; Amita Joshi; Yu-Waye Chu; Hope Rugo; Ian E Krop; Sandhya Girish; Lena E Friberg; Manish Gupta
Journal:  Cancer Chemother Pharmacol       Date:  2012-08-12       Impact factor: 3.333

8.  Antibody biodistribution coefficients: inferring tissue concentrations of monoclonal antibodies based on the plasma concentrations in several preclinical species and human.

Authors:  Dhaval K Shah; Alison M Betts
Journal:  MAbs       Date:  2013-02-13       Impact factor: 5.857

9.  Theoretic criteria for antibody penetration into solid tumors and micrometastases.

Authors:  Greg M Thurber; Stefan C Zajic; K Dane Wittrup
Journal:  J Nucl Med       Date:  2007-05-15       Impact factor: 10.057

10.  Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice.

Authors:  Amit Garg; Joseph P Balthasar
Journal:  J Pharmacokinet Pharmacodyn       Date:  2007-07-18       Impact factor: 2.745

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  21 in total

Review 1.  Pharmacokinetic and pharmacodynamic considerations for the next generation protein therapeutics.

Authors:  Dhaval K Shah
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-09-15       Impact factor: 2.745

2.  Determination of Cellular Processing Rates for a Trastuzumab-Maytansinoid Antibody-Drug Conjugate (ADC) Highlights Key Parameters for ADC Design.

Authors:  Katie F Maass; Chethana Kulkarni; Alison M Betts; K Dane Wittrup
Journal:  AAPS J       Date:  2016-02-24       Impact factor: 4.009

3.  Development of a Translational Physiologically Based Pharmacokinetic Model for Antibody-Drug Conjugates: a Case Study with T-DM1.

Authors:  Antari Khot; Jay Tibbitts; Dan Rock; Dhaval K Shah
Journal:  AAPS J       Date:  2017-08-14       Impact factor: 4.009

4.  Evolution of the Systems Pharmacokinetics-Pharmacodynamics Model for Antibody-Drug Conjugates to Characterize Tumor Heterogeneity and In Vivo Bystander Effect.

Authors:  Aman P Singh; Gail M Seigel; Leiming Guo; Ashwni Verma; Gloria Gao-Li Wong; Hsuan-Ping Cheng; Dhaval K Shah
Journal:  J Pharmacol Exp Ther       Date:  2020-04-09       Impact factor: 4.030

5.  Measurement and Mathematical Characterization of Cell-Level Pharmacokinetics of Antibody-Drug Conjugates: A Case Study with Trastuzumab-vc-MMAE.

Authors:  Aman P Singh; Dhaval K Shah
Journal:  Drug Metab Dispos       Date:  2017-08-18       Impact factor: 3.922

6.  Antibody Coadministration as a Strategy to Overcome Binding-Site Barrier for ADCs: a Quantitative Investigation.

Authors:  Aman P Singh; Leiming Guo; Ashwni Verma; Gloria Gao-Li Wong; Greg M Thurber; Dhaval K Shah
Journal:  AAPS J       Date:  2020-01-14       Impact factor: 4.009

7.  A "Dual" Cell-Level Systems PK-PD Model to Characterize the Bystander Effect of ADC.

Authors:  Aman P Singh; Dhaval K Shah
Journal:  J Pharm Sci       Date:  2019-02-18       Impact factor: 3.534

8.  Application of a PK-PD Modeling and Simulation-Based Strategy for Clinical Translation of Antibody-Drug Conjugates: a Case Study with Trastuzumab Emtansine (T-DM1).

Authors:  Aman P Singh; Dhaval K Shah
Journal:  AAPS J       Date:  2017-04-03       Impact factor: 4.009

9.  Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1).

Authors:  Aman P Singh; Katie F Maass; Alison M Betts; K Dane Wittrup; Chethana Kulkarni; Lindsay E King; Antari Khot; Dhaval K Shah
Journal:  AAPS J       Date:  2016-03-30       Impact factor: 4.009

10.  Multiscale Modeling of Antibody-Drug Conjugates: Connecting Tissue and Cellular Distribution to Whole Animal Pharmacokinetics and Potential Implications for Efficacy.

Authors:  Cornelius Cilliers; Hans Guo; Jianshan Liao; Nikolas Christodolu; Greg M Thurber
Journal:  AAPS J       Date:  2016-06-10       Impact factor: 4.009

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