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Kulesza A, Couty C, Lemarre P, Thalhauser CJ, Cao Y. Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice. J Pharmacokinet Pharmacodyn 2024:10.1007/s10928-024-09930-x. [PMID: 38904912 DOI: 10.1007/s10928-024-09930-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 06/07/2024] [Indexed: 06/22/2024]
Abstract
Quantitative predictive modeling of cancer growth, progression, and individual response to therapy is a rapidly growing field. Researchers from mathematical modeling, systems biology, pharmaceutical industry, and regulatory bodies, are collaboratively working on predictive models that could be applied for drug development and, ultimately, the clinical management of cancer patients. A plethora of modeling paradigms and approaches have emerged, making it challenging to compile a comprehensive review across all subdisciplines. It is therefore critical to gauge fundamental design aspects against requirements, and weigh opportunities and limitations of the different model types. In this review, we discuss three fundamental types of cancer models: space-structured models, ecological models, and immune system focused models. For each type, it is our goal to illustrate which mechanisms contribute to variability and heterogeneity in cancer growth and response, so that the appropriate architecture and complexity of a new model becomes clearer. We present the main features addressed by each of the three exemplary modeling types through a subjective collection of literature and illustrative exercises to facilitate inspiration and exchange, with a focus on providing a didactic rather than exhaustive overview. We close by imagining a future multi-scale model design to impact critical decisions in oncology drug development.
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Affiliation(s)
| | - Claire Couty
- Novadiscovery, 1 Place Giovanni Verrazzano, 69009, Lyon, France
| | - Paul Lemarre
- Novadiscovery, 1 Place Giovanni Verrazzano, 69009, Lyon, France
| | - Craig J Thalhauser
- Genmab US, Inc., 777 Scudders Mill Rd Bldg 2 4th Floor, Plainsboro, NJ, 08536, USA
| | - Yanguang Cao
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
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De Sutter PJ, Gasthuys E, Vermeulen A. Comparison of monoclonal antibody disposition predictions using different physiologically based pharmacokinetic modelling platforms. J Pharmacokinet Pharmacodyn 2023:10.1007/s10928-023-09894-4. [PMID: 37952005 DOI: 10.1007/s10928-023-09894-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 10/17/2023] [Indexed: 11/14/2023]
Abstract
Physiologically based pharmacokinetic (PBPK) models can be used to leverage physiological and in vitro data to predict monoclonal antibody (mAb) concentrations in serum and tissues. However, it is currently not known how consistent predictions of mAb disposition are across PBPK modelling platforms. In this work PBPK simulations of IgG, adalimumab and infliximab were compared between three platforms (Simcyp, PK-Sim, and GastroPlus). Accuracy of predicted serum and tissue concentrations was assessed using observed data collected from the literature. Physiological and mAb related input parameters were also compared and sensitivity analyses were carried out to evaluate model behavior when input values were altered. Differences in serum kinetics of IgG between platforms were minimal for a dose of 1 mg/kg, but became more noticeable at higher dosages (> 100 mg/kg) and when reference (healthy) physiological input values were altered. Predicted serum concentrations of both adalimumab and infliximab were comparable across platforms, but were noticeably higher than observed values. Tissue concentrations differed remarkably between the platforms, both for total- and interstitial fluid (ISF) concentrations. The accuracy of total tissue concentrations was within a three-fold of observed values for all tissues, except for brain tissue concentrations, which were overpredicted. Predictions of tissue ISF concentrations were less accurate and were best captured by GastroPlus. Overall, these simulations show that the different PBPK platforms generally predict similar mAb serum concentrations, but variable tissue concentrations. Caution is therefore warranted when PBPK models are used to simulate effect site tissue concentrations of mAbs without data to verify the predictions.
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Affiliation(s)
- Pieter-Jan De Sutter
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
| | - Elke Gasthuys
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium
| | - An Vermeulen
- Laboratory of Medical Biochemistry and Clinical Analysis, Department of Bioanalysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium
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Chen C, Fan X, Zhang L, Xu P, Zou H, Zhao X, Gupta M, Feng YS, Xu XS, Yan X. Clearance as an Early Indicator of Efficacy for Therapeutic Monoclonal Antibodies: Circumventing Dose Selection Challenges in Oncology. Clin Pharmacokinet 2023; 62:705-713. [PMID: 36930421 DOI: 10.1007/s40262-023-01231-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND AND OBJECTIVE The designs of first-in-human (FIH) studies in oncology (e.g., 3 + 3 dose escalation design) usually do not provide a sufficient sample size to determine the dose-response relationship for efficacy. This study aimed to assess the feasibility of using monoclonal antibody (mAb) clearance as a biomarker for efficacy to facilitate the identification of potentially efficacious doses across cancer types and drug targets. METHODS We performed electronic searches of the Drugs@FDA website, the European Medicines Agency website, and PubMed to identify reports of FIH trials of approved mAbs in oncology. The clearance, half-life, and overall response rate (ORR) data for the mAbs at different dose levels were extracted. RESULTS Twenty-five approved mAbs were included in this study. As expected, due to the small sample sizes in FIH studies, there was no clear dose-response for ORR. However, we found a clear negative association between mAb clearance and ORR across tumors/drug targets, and a clear negative dose-clearance relationship, with clearance decreasing and saturated at high dose levels. The approved mAb doses (1-25 mg/kg) are approximately 2-fold the saturation doses (1-10 mg/kg). The associated clearance values at the approved doses vary across different cancers and drug targets (0.17-1.56 L/day), while tend to be similar within a disease/drug target. Anti-CD20 mAbs for B-cell lymphomas show a higher clearance (~ 1 L/day) than other cancers and targets (e.g., ~ 0.3 L/day for anti-PD-1). CONCLUSIONS Clearance of mAbs can be a tumor/drug target-agnostic biomarker for potential anti-tumor activity as clearance decreases with increasing ORR. Our findings shed important insights into target clearance values that may lead to desired efficacy for different cancers and drug targets, which can be used to guide dose selection for the future development of mAbs during FIH oncology studies.
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Affiliation(s)
- Chengcong Chen
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Xiaoqing Fan
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Lin Zhang
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Peng Xu
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Huixi Zou
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Xing Zhao
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR
| | - Manish Gupta
- Clinical Pharmacology and Quantitative Science, Genmab Inc., Princeton, NJ, USA
| | - Yan Summer Feng
- Clinical Pharmacology and Quantitative Science, Genmab Inc., Princeton, NJ, USA
| | - Xu Steven Xu
- Clinical Pharmacology and Quantitative Science, Genmab Inc., Princeton, NJ, USA.
| | - Xiaoyu Yan
- School of Pharmacy, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR.
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Pasquiers B, Benamara S, Felices M, Nguyen L, Declèves X. Review of the Existing Translational Pharmacokinetics Modeling Approaches Specific to Monoclonal Antibodies (mAbs) to Support the First-In-Human (FIH) Dose Selection. Int J Mol Sci 2022; 23:12754. [PMID: 36361546 PMCID: PMC9657028 DOI: 10.3390/ijms232112754] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 10/18/2022] [Accepted: 10/19/2022] [Indexed: 08/27/2023] Open
Abstract
The interest in therapeutic monoclonal antibodies (mAbs) has continuously growing in several diseases. However, their pharmacokinetics (PK) is complex due to their target-mediated drug disposition (TMDD) profiles which can induce a non-linear PK. This point is particularly challenging during the pre-clinical and translational development of a new mAb. This article reviews and describes the existing PK modeling approaches used to translate the mAbs PK from animal to human for intravenous (IV) and subcutaneous (SC) administration routes. Several approaches are presented, from the most empirical models to full physiologically based pharmacokinetic (PBPK) models, with a focus on the population PK methods (compartmental and minimal PBPK models). They include the translational approaches for the linear part of the PK and the TMDD mechanism of mAbs. The objective of this article is to provide an up-to-date overview and future perspectives of the translational PK approaches for mAbs during a model-informed drug development (MIDD), since the field of PK modeling has gained recently significant interest for guiding mAbs drug development.
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Affiliation(s)
- Blaise Pasquiers
- PhinC Development, 91300 Massy, France
- Université Paris Cité, Inserm UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
| | | | | | | | - Xavier Declèves
- Université Paris Cité, Inserm UMRS-1144, Optimisation Thérapeutique en Neuropsychopharmacologie, 75006 Paris, France
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