Literature DB >> 25186956

Mechanistic pharmacokinetic/pharmacodynamic modeling of in vivo tumor uptake, catabolism, and tumor response of trastuzumab maytansinoid conjugates.

Russ Wada1, Hans K Erickson, Gail D Lewis Phillips, Carmela A Provenzano, Douglas D Leipold, Elaine Mai, Holly Johnson, Jay Tibbitts.   

Abstract

PURPOSE: Trastuzumab emtansine (T-DM1), an antibody-drug conjugate (ADC) comprised of trastuzumab linked to the antimitotic agent DM1, has shown promising results in patients with human epidermal growth factor receptor 2-positive metastatic breast cancer. Investigations of the mechanisms of the action of ADCs, including T-DM1, have been primarily descriptive or semiquantitative. However, quantitative pharmacokinetic/pharmacodynamic (PK/PD) analysis may provide insights into their complex behavior. The analyses described herein applied PK/PD modeling to nonclinical studies of maytansinoid conjugates.
METHODS: The maytansinoid conjugates T-DM1 and T-SPP-DM1, with thioether and disulfide linkers, respectively, were tested in mouse efficacy, PK, and tumor uptake studies. (3)[H]DM1-bearing ADCs were used to facilitate the quantitation of the ADCs in plasma, as well as ADC and ADC catabolites in tumors. Three mechanistic PK/PD models were used to characterize plasma ADC, tumor ADC, and tumor catabolite concentrations. Tumor catabolite concentrations were used to fit tumor response. Model parameters were estimated using R software and nonlinear least squares regression.
RESULTS: Plasma ADC-associated DM1 concentrations of T-DM1 decreased more slowly than those of T-SPP-DM1, likely due to slower DM1 release. A comparison of the mechanistic models found that the best model allowed catabolism and catabolite exit rates to differ between ADCs, that T-DM1 exhibited both faster tumor catabolism and catabolite exit rate from tumors than T-SPP-DM1; findings inconsistent with expected behavior based on the physicochemical nature of the respective catabolites. Tumor catabolite concentrations adequately described tumor response with both ADCs showing similar potency.
CONCLUSION: Mechanistic PK/PD studies described herein provided results that confirmed and challenged current hypotheses, and suggested new areas of investigation.

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Year:  2014        PMID: 25186956     DOI: 10.1007/s00280-014-2561-2

Source DB:  PubMed          Journal:  Cancer Chemother Pharmacol        ISSN: 0344-5704            Impact factor:   3.333


  9 in total

1.  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

2.  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

Review 3.  Integrated PK-PD and agent-based modeling in oncology.

Authors:  Zhihui Wang; Joseph D Butner; Vittorio Cristini; Thomas S Deisboeck
Journal:  J Pharmacokinet Pharmacodyn       Date:  2015-01-15       Impact factor: 2.745

Review 4.  Antibody-Drug Conjugates: Pharmacokinetic/Pharmacodynamic Modeling, Preclinical Characterization, Clinical Studies, and Lessons Learned.

Authors:  William D Hedrich; Tamer E Fandy; Hossam M Ashour; Hongbing Wang; Hazem E Hassan
Journal:  Clin Pharmacokinet       Date:  2018-06       Impact factor: 6.447

Review 5.  Antibody-Drug Conjugates in Non-Small Cell Lung Cancer: Emergence of a Novel Therapeutic Class.

Authors:  Jennifer A Marks; Molly Wilgucki; Stephen V Liu; Joshua E Reuss
Journal:  Curr Oncol Rep       Date:  2022-10-05       Impact factor: 5.945

Review 6.  Computational oncology--mathematical modelling of drug regimens for precision medicine.

Authors:  Dominique Barbolosi; Joseph Ciccolini; Bruno Lacarelle; Fabrice Barlési; Nicolas André
Journal:  Nat Rev Clin Oncol       Date:  2015-11-24       Impact factor: 66.675

7.  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

8.  A Novel Integrated Pharmacokinetic-Pharmacodynamic Model to Evaluate Combination Therapy and Determine In Vivo Synergism.

Authors:  Young Hee Choi; Chao Zhang; Zhenzhen Liu; Mei-Juan Tu; Ai-Xi Yu; Ai-Ming Yu
Journal:  J Pharmacol Exp Ther       Date:  2021-03-12       Impact factor: 4.030

9.  Pharmacokinetic-Pharmacodynamic Modeling of Tumor Targeted Drug Delivery Using Nano-Engineered Mesenchymal Stem Cells.

Authors:  Shen Cheng; Susheel Kumar Nethi; Mahmoud Al-Kofahi; Swayam Prabha
Journal:  Pharmaceutics       Date:  2021-01-12       Impact factor: 6.321

  9 in total

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