Literature DB >> 31939004

Population-based meta-analysis of bortezomib exposure-response relationships in multiple myeloma patients.

Li Zhang1, Donald E Mager2.   

Abstract

Bortezomib (Velcade®) is a reversible proteasome inhibitor that shows potent antineoplastic activity, by inhibiting the constitutively increased proteasome activity in myeloma cells, and is approved as a first-line therapy for multiple myeloma (MM). Although clinically successful, bortezomib exhibits a relatively narrow therapeutic index and can induce dose-limiting toxicities such as thrombocytopenia. This study aims to develop a quantitative and predictive pharmacodynamic model to investigate bortezomib dosing-regimens in a rational and efficient manner. Mean temporal profiles of bortezomib pharmacokinetics, proteasome activity, M-protein concentrations, and platelet counts following bortezomib monotherapy were extracted from published clinical studies. A population-based meta-analysis of bortezomib anti-myeloma activity and thrombocytopenia was conducted sequentially with a Stochastic Approximation Expectation Maximization algorithm in Monolix. The final pharmacodynamic model integrates drug-target interactions and cell signaling dynamics with temporal biomarkers of clinical efficacy and toxicity. Bortezomib pharmacokinetics, disease progression, and platelet dynamic profiles were well characterized in MM patients, and a local sensitivity analysis of the final model suggests that increased proteasome concentration could ultimately attenuate bortezomib antineoplastic activity in MM patients. In addition, model simulations confirm that a once-weekly dosing schedule represents an optimal therapeutic regimen with comparable antineoplastic activity but significantly reduced risk of thrombocytopenia. In conclusion, a pharmacodynamic model was successfully developed, which provides a quantitative, mechanism-based platform for probing bortezomib dosing-regimens. Further research is needed to determine whether this model could be used to individualize bortezomib regimens to maximize antineoplastic efficacy and minimize thrombocytopenia during MM treatment.

Entities:  

Keywords:  Bortezomib; Multiple myeloma; Pharmacodynamics; Pharmacokinetics; Thrombocytopenia; Tumor burden

Mesh:

Substances:

Year:  2020        PMID: 31939004     DOI: 10.1007/s10928-019-09670-3

Source DB:  PubMed          Journal:  J Pharmacokinet Pharmacodyn        ISSN: 1567-567X            Impact factor:   2.745


  47 in total

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Authors:  Prashant Kapoor; Vijay Ramakrishnan; S Vincent Rajkumar
Journal:  Semin Hematol       Date:  2012-07       Impact factor: 3.851

2.  Many facets of bortezomib resistance/susceptibility.

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Journal:  Blood       Date:  2008-09-15       Impact factor: 22.113

3.  Safety of prolonged therapy with bortezomib in relapsed or refractory multiple myeloma.

Authors:  James R Berenson; Sundar Jagannath; Bart Barlogie; David T Siegel; Raymond Alexanian; Paul G Richardson; David Irwin; Melissa Alsina; S Vincent Rajkumar; Gordon Srkalovic; Seema Singhal; Steven Limentani; Ruben Niesvizky; Dixie L Esseltine; Elizabeth Trehu; David P Schenkein; Kenneth Anderson
Journal:  Cancer       Date:  2005-11-15       Impact factor: 6.860

4.  Model of chemotherapy-induced myelosuppression with parameter consistency across drugs.

Authors:  Lena E Friberg; Anja Henningsson; Hugo Maas; Laurent Nguyen; Mats O Karlsson
Journal:  J Clin Oncol       Date:  2002-12-15       Impact factor: 44.544

5.  Prediction-corrected visual predictive checks for diagnosing nonlinear mixed-effects models.

Authors:  Martin Bergstrand; Andrew C Hooker; Johan E Wallin; Mats O Karlsson
Journal:  AAPS J       Date:  2011-02-08       Impact factor: 4.009

6.  Systems Modeling of Bortezomib and Dexamethasone Combinatorial Effects on Bone Homeostasis in Multiple Myeloma Patients.

Authors:  Li Zhang; Donald E Mager
Journal:  J Pharm Sci       Date:  2018-11-22       Impact factor: 3.534

7.  Pharmacogenomics of bortezomib test-dosing identifies hyperexpression of proteasome genes, especially PSMD4, as novel high-risk feature in myeloma treated with Total Therapy 3.

Authors:  John D Shaughnessy; Pingping Qu; Saad Usmani; Christoph J Heuck; Qing Zhang; Yiming Zhou; Erming Tian; Ichiro Hanamura; Frits van Rhee; Elias Anaissie; Joshua Epstein; Bijay Nair; Owen Stephens; Ryan Williams; Sarah Waheed; Yazan Alsayed; John Crowley; Bart Barlogie
Journal:  Blood       Date:  2011-05-31       Impact factor: 22.113

8.  Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.

Authors:  Vaishali L Chudasama; Meric A Ovacik; Darrell R Abernethy; Donald E Mager
Journal:  J Pharmacol Exp Ther       Date:  2015-07-10       Impact factor: 4.030

Review 9.  Bortezomib-induced peripheral neuropathy in multiple myeloma: a comprehensive review of the literature.

Authors:  Andreas A Argyriou; Gregoris Iconomou; Haralabos P Kalofonos
Journal:  Blood       Date:  2008-06-23       Impact factor: 22.113

10.  Computational modeling of ERBB2-amplified breast cancer identifies combined ErbB2/3 blockade as superior to the combination of MEK and AKT inhibitors.

Authors:  Daniel C Kirouac; Jin Y Du; Johanna Lahdenranta; Ryan Overland; Defne Yarar; Violette Paragas; Emily Pace; Charlotte F McDonagh; Ulrik B Nielsen; Matthew D Onsum
Journal:  Sci Signal       Date:  2013-08-13       Impact factor: 8.192

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Review 1.  Proteasome Inhibitors and Their Pharmacokinetics, Pharmacodynamics, and Metabolism.

Authors:  Jinhai Wang; Ying Fang; R Andrea Fan; Christopher J Kirk
Journal:  Int J Mol Sci       Date:  2021-10-27       Impact factor: 5.923

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