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Mody H, Sutaria DS, Miles D. Clinical Pharmacology Considerations for the "Off-the-Shelf" Allogeneic Cell Therapies. Clin Pharmacol Ther 2024; 115:1233-1250. [PMID: 38501153 DOI: 10.1002/cpt.3241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/25/2024] [Indexed: 03/20/2024]
Abstract
Autologous chimeric antigen receptor T-cell (CAR-T) therapies have garnered unprecedented clinical success with multiple regulatory approvals for the treatment of various hematological malignancies. However, there are still several clinical challenges that limit their broad utilization for aggressive disease conditions. To address some of these challenges, allogeneic cell therapies are evaluated as an alternative approach. As compared with autologous products, they offer several advantages, such as a more standardized "off the shelf" product, reduced manufacturing complexity, and no requirement of bridging therapy. As with autologous CAR-T therapies, allogeneic cell therapies also present clinical pharmacology challenges due to their in vivo living nature, unique pharmacokinetics or cellular kinetics (CKs), and complex dose-exposure-response relationships that are impacted by various patient- and product-related factors. On top of that, allogeneic cell therapies present additional unique challenges, including attenuated in vivo persistence and graft-vs.-host disease risk as compared with autologous counterparts. This review draws comparison between autologous and allogeneic cell therapies, summarizing key engineering aspects unique to allogeneic cell therapy. Clinical pharmacology learnings from emerging clinical data of allogeneic cell therapy programs are also highlighted, with particular emphasis on CK, dose-exposure-response relationship, lymphodepletion regimen, repeat dosing, and patient- and product-related factors that can impact CK and patient outcomes. There are specific unique challenges and opportunities arising from the development of allogeneic cell therapies, especially in optimizing lymphodepletion and establishing a regimen for repeat dosing. This review highlights how clinical pharmacologists are well positioned to help address these challenges by leveraging novel clinical pharmacology and modeling and simulation approaches.
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Affiliation(s)
- Hardik Mody
- Clinical Pharmacology, Genentech, South San Francisco, California, USA
| | | | - Dale Miles
- Clinical Pharmacology, Genentech, South San Francisco, California, USA
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2
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Kirouac DC, Zmurchok C, Morris D. Making drugs from T cells: The quantitative pharmacology of engineered T cell therapeutics. NPJ Syst Biol Appl 2024; 10:31. [PMID: 38499572 PMCID: PMC10948391 DOI: 10.1038/s41540-024-00355-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 02/26/2024] [Indexed: 03/20/2024] Open
Abstract
Engineered T cells have emerged as highly effective treatments for hematological cancers. Hundreds of clinical programs are underway in efforts to expand the efficacy, safety, and applications of this immuno-therapeutic modality. A primary challenge in developing these "living drugs" is the complexity of their pharmacology, as the drug product proliferates, differentiates, traffics between tissues, and evolves through interactions with patient immune systems. Using publicly available clinical data from Chimeric Antigen Receptor (CAR) T cells, we demonstrate how mathematical models can be used to quantify the relationships between product characteristics, patient physiology, pharmacokinetics and clinical outcomes. As scientists work to develop next-generation cell therapy products, mathematical models will be integral for contextualizing data and facilitating the translation of product designs to clinical strategy.
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Affiliation(s)
- Daniel C Kirouac
- Notch Therapeutics, Vancouver, BC, Canada.
- The University of British Columbia, School of Biomedical Engineering, Vancouver, BC, Canada.
- Metrum Research Group, Tariffville, CT, USA.
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3
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Arabameri A, Arab S. Understanding the Interplay of CAR-NK Cells and Triple-Negative Breast Cancer: Insights from Computational Modeling. Bull Math Biol 2024; 86:20. [PMID: 38240892 DOI: 10.1007/s11538-023-01247-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
Chimeric antigen receptor (CAR)-engineered natural killer (NK) cells have recently emerged as a promising and safe alternative to CAR-T cells for targeting solid tumors. In the case of triple-negative breast cancer (TNBC), traditional cancer treatments and common immunotherapies have shown limited effectiveness. However, CAR-NK cells have been successfully employed to target epidermal growth factor receptor (EGFR) on TNBC cells, thereby enhancing the efficacy of immunotherapy. The effectiveness of CAR-NK-based immunotherapy is influenced by various factors, including the vaccination dose, vaccination pattern, and tumor immunosuppressive factors in the microenvironment. To gain insights into the dynamics and effects of CAR-NK-based immunotherapy, we propose a computational model based on experimental data and immunological theories. This model integrates an individual-based model that describes the interplay between the tumor and the immune system, along with an ordinary differential equation model that captures the variation of inflammatory cytokines. Computational results obtained from the proposed model shed light on the conditions necessary for initiating an effective anti-tumor response. Furthermore, global sensitivity analysis highlights the issue of low persistence of CAR-NK cells in vivo, which poses a significant challenge for the successful clinical application of these cells. Leveraging the model, we identify the optimal vaccination time, vaccination dose, and time interval between injections for maximizing therapeutic outcomes.
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Affiliation(s)
- Abazar Arabameri
- Department of Electrical Engineering, University of Zanjan, Zanjan, Iran.
| | - Samaneh Arab
- Department of Tissue Engineering and Applied Cell Sciences, School of Medicine, Semnan University of Medical Sciences, Semnan, Iran
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4
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Mitra A, Ahmed MA, Krishna R, Sun K, Gibbons FD, Campagne O, Rayad N, Roman YM, Albusaysi S, Burian M, Younis IR. Model-Informed Approaches and Innovative Clinical Trial Design for Adeno-Associated Viral Vector-Based Gene Therapy Product Development: A White Paper. Clin Pharmacol Ther 2023; 114:515-529. [PMID: 37313953 DOI: 10.1002/cpt.2972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/02/2023] [Indexed: 06/15/2023]
Abstract
The promise of viral vector-based gene therapy (GT) as a transformative paradigm for treating severely debilitating and life-threatening diseases is slowly coming to fruition with the recent approval of several drug products. However, they have a unique mechanism of action often necessitating a tortuous clinical development plan. Expertise in such complex therapeutic modality is still fairly limited in this emerging class of adeno-associated virus (AAV) vector-based gene therapies. Because of the irreversible mode of action and incomplete understanding of genotype-phenotype relationship and disease progression in rare diseases careful considerations should be given to GT product's benefit-risk profile. In particular, special attention needs to be paid to safe dose selection, reliable dose exposure response (including clinically relevant endpoints), or creative approaches in study design targeting small patient populations during clinical development. We believe that quantitative tools encompassed within model-informed drug development (MIDD) framework fits quite well in the development of such novel therapies, as they enable us to benefit from the totality of data approach in order to support dose selection as well as optimize clinical trial designs, end point selection, and patient enrichment. In this thought leadership paper, we provide our collective experiences, identify challenges, and suggest areas of improvement in applications of modeling and innovative trial design in development of AAV-based GT products and reflect on the challenges and opportunities for incorporating MIDD tools and more in rational development of these products.
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Affiliation(s)
- Amitava Mitra
- Clinical Pharmacology, Kura Oncology, Boston, Massachusetts, USA
| | - Mariam A Ahmed
- Quantitative Clinical Pharmacology, Takeda Development Center Americas, Inc., Cambridge, Massachusetts, USA
| | - Rajesh Krishna
- Integrated Drug Development, Certara USA, Inc., Princeton, New Jersey, USA
| | - Kefeng Sun
- Quantitative Clinical Pharmacology, Takeda Development Center Americas, Inc., Cambridge, Massachusetts, USA
| | - Francis D Gibbons
- Quantitative Solutions, Preclinical and Translational Sciences, Takeda Development Center Americas, Inc., Cambridge, Massachusetts, USA
| | - Olivia Campagne
- Quantitative Clinical Pharmacology, Takeda Development Center Americas, Inc., Cambridge, Massachusetts, USA
| | - Noha Rayad
- Clinical Pharmacology, Modeling and Simulation, Parexel International (MA) Corporation, Mississauga, Ontario, Canada
| | - Youssef M Roman
- Department of Pharmacotherapy and Outcomes Science, Virginia Commonwealth University School of Pharmacy, Richmond, Virginia, USA
| | - Salwa Albusaysi
- Department of Pharmaceutics, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Maria Burian
- Translational Medicine Neuroscience and Gene Therapy, UCB Biopharma SRL, Braine-l'Alleud, Belgium
| | - Islam R Younis
- Clinical Pharmacology Sciences, Gilead Science, Inc, Foster City, California, USA
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5
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Mody H, Ogasawara K, Zhu X, Miles D, Shastri PN, Gokemeijer J, Liao MZ, Kasichayanula S, Yang TY, Chemuturi N, Gupta S, Jawa V, Upreti VV. Best Practices and Considerations for Clinical Pharmacology and Pharmacometric Aspects for Optimal Development of CAR-T and TCR-T Cell Therapies: An Industry Perspective. Clin Pharmacol Ther 2023; 114:530-557. [PMID: 37393588 DOI: 10.1002/cpt.2986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 06/26/2023] [Indexed: 07/04/2023]
Abstract
With the promise of a potentially "single dose curative" paradigm, CAR-T cell therapies have brought a paradigm shift in the treatment and management of hematological malignancies. Both CAR-T and TCR-T cell therapies have also made great progress toward the successful treatment of solid tumor indications. The field is rapidly evolving with recent advancements including the clinical development of "off-the-shelf" allogeneic CAR-T therapies that can overcome the long and difficult "vein-to-vein" wait time seen with autologous CAR-T therapies. There are unique clinical pharmacology, pharmacometric, bioanalytical, and immunogenicity considerations and challenges in the development of these CAR-T and TCR-T cell therapies. Hence, to help accelerate the development of these life-saving therapies for the patients with cancer, experts in this field came together under the umbrella of International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) to form a joint working group between the Clinical Pharmacology Leadership Group (CPLG) and the Translational and ADME Sciences Leadership Group (TALG). In this white paper, we present the IQ consortium perspective on the best practices and considerations for clinical pharmacology and pharmacometric aspects toward the optimal development of CAR-T and TCR-T cell therapies.
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Affiliation(s)
- Hardik Mody
- Clinical Pharmacology, Genentech, South San Francisco, California, USA
| | - Ken Ogasawara
- Clinical Pharmacology, Pharmacometrics, Disposition and Bioanalysis, Bristol Myers Squibb, Lawrence Township, New Jersey, USA
| | - Xu Zhu
- Quantitative Clinical Pharmacology, AstraZeneca, Boston, Massachusetts, USA
| | - Dale Miles
- Clinical Pharmacology, Genentech, South San Francisco, California, USA
| | | | - Jochem Gokemeijer
- Discovery Biotherapeutics, Bristol Myers Squibb, Cambridge, Massachusetts, USA
| | - Michael Z Liao
- Clinical Pharmacology, Genentech, South San Francisco, California, USA
| | | | - Tong-Yuan Yang
- Bioanalytical Discovery and Development Sciences, Janssen R&D, LLC, Spring House, Pennsylvania, USA
| | - Nagendra Chemuturi
- Clinical Pharmacology, DMPK, Pharmacometrics, Moderna, Inc., Cambridge, Massachusetts, USA
| | - Swati Gupta
- Development Biological Sciences, Immunology, AbbVie, Irvine, California, USA
| | - Vibha Jawa
- Clinical Pharmacology, Pharmacometrics, Disposition and Bioanalysis, Bristol Myers Squibb, Lawrence Township, New Jersey, USA
| | - Vijay V Upreti
- Clinical Pharmacology, Modeling & Simulation, Amgen, South San Francisco, California, USA
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6
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Han L, Rodriguez Messan M, Yogurtcu ON, Nukala U, Yang H. Analysis of tumor-immune functional responses in a mathematical model of neoantigen cancer vaccines. Math Biosci 2023; 356:108966. [PMID: 36642160 DOI: 10.1016/j.mbs.2023.108966] [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: 09/13/2022] [Revised: 01/03/2023] [Accepted: 01/03/2023] [Indexed: 01/15/2023]
Abstract
Cancer neoantigen vaccines have emerged as a promising approach to stimulating the immune system to fight cancer. We propose a simple model including key elements of cancer-immune interactions and conduct a phase plane analysis to understand the immunological mechanisms of cancer neoantigen vaccines. Analytical results are obtained for two widely used functional forms that represent the killing rate of tumor cells by immune cells: the law of mass action (LMA) and the dePillis-Radunskaya Law (LPR). Using the LMA, our results reveal that a slowly growing tumor can escape the immune surveillance and that there is a unique periodic solution. The LPR offers richer dynamics, in which tumor elimination and uncontrolled tumor growth are both present. We show that tumor elimination requires sufficient number of initial activated T cells in relationship to the malignant cells, which lends support to using the neoantigen cancer vaccine as an adjuvant therapy after the primary tumor is surgically removed or treated using radiotherapy. We also derive a sufficient condition for uncontrolled tumor growth under the assumption of the LPR. The juxtaposition of analyses with these two different choices for the killing rate function highlights their importance on model behavior and biological implications, by which we hope to spur further theoretical and experimental work to understand mechanisms underlying different functional forms for the killing rate.
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Affiliation(s)
- Lifeng Han
- Office of Biostatistics and Pharmacovigilance, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, United States of America
| | - Marisabel Rodriguez Messan
- Office of Biostatistics and Pharmacovigilance, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, United States of America
| | - Osman N Yogurtcu
- Office of Biostatistics and Pharmacovigilance, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, United States of America
| | - Ujwani Nukala
- Office of Biostatistics and Pharmacovigilance, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, United States of America
| | - Hong Yang
- Office of Biostatistics and Pharmacovigilance, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, United States of America.
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7
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Paixão EA, Barros LRC, Fassoni AC, Almeida RC. Modeling Patient-Specific CAR-T Cell Dynamics: Multiphasic Kinetics via Phenotypic Differentiation. Cancers (Basel) 2022; 14:cancers14225576. [PMID: 36428671 PMCID: PMC9688514 DOI: 10.3390/cancers14225576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/03/2022] [Accepted: 11/07/2022] [Indexed: 11/16/2022] Open
Abstract
Chimeric Antigen Receptor (CAR)-T cell immunotherapy revolutionized cancer treatment and consists of the genetic modification of T lymphocytes with a CAR gene, aiming to increase their ability to recognize and kill antigen-specific tumor cells. The dynamics of CAR-T cell responses in patients present multiphasic kinetics with distribution, expansion, contraction, and persistence phases. The characteristics and duration of each phase depend on the tumor type, the infused product, and patient-specific characteristics. We present a mathematical model that describes the multiphasic CAR-T cell dynamics resulting from the interplay between CAR-T and tumor cells, considering patient and product heterogeneities. The CAR-T cell population is divided into functional (distributed and effector), memory, and exhausted CAR-T cell phenotypes. The model is able to describe the diversity of CAR-T cell dynamical behaviors in different patients and hematological cancers as well as their therapy outcomes. Our results indicate that the joint assessment of the area under the concentration-time curve in the first 28 days and the corresponding fraction of non-exhausted CAR-T cells may be considered a potential marker to classify therapy responses. Overall, the analysis of different CAR-T cell phenotypes can be a key aspect for a better understanding of the whole CAR-T cell dynamics.
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Affiliation(s)
- Emanuelle A. Paixão
- Graduate Program, Laboratório Nacional de Computação Científica, Petrópolis 25651-075, Brazil
- Correspondence:
| | - Luciana R. C. Barros
- Center for Translational Research in Oncology, Instituto do Câncer do Estado de São Paulo, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo 01246-000, Brazil
| | - Artur C. Fassoni
- Institute for Mathematics and Computer Science, Universidade Federal de Itajubá, Itajubá 37500-903, Brazil
| | - Regina C. Almeida
- Computational Modeling Department, Laboratório Nacional de Computação Científica, Petrópolis 25651-075, Brazil
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8
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Huang W, Li J, Liao MZ, Liu SN, Yu J, Jing J, Kotani N, Kamen L, Guelman S, Miles DR. Clinical Pharmacology Perspectives for Adoptive Cell Therapies in Oncology. Clin Pharmacol Ther 2022; 112:968-981. [PMID: 34888856 PMCID: PMC9786613 DOI: 10.1002/cpt.2509] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Accepted: 11/24/2021] [Indexed: 12/30/2022]
Abstract
Adoptive cell therapies (ACTs) have shown transformative efficacy in oncology with five US Food and Drug Administration (FDA) approvals for chimeric antigen receptor (CAR) T-cell therapies in hematological malignancies, and promising activity for T cell receptor T-cell therapies in both liquid and solid tumors. Clinical pharmacology can play a pivotal role in optimizing ACTs, aided by modeling and simulation toolboxes and deep understanding of the underlying biological and immunological processes. Close collaboration and multilevel data integration across functions, including chemistry, manufacturing, and control, biomarkers, bioanalytical, and clinical science and safety teams will be critical to ACT development. As ACT is comprised of alive, polyfunctional, and heterogeneous immune cells, its overall physicochemical and pharmacological property is vastly different from other platforms/modalities, such as small molecule and protein therapeutics. In this review, we first describe the unique kinetics of T cells and the appropriate bioanalytical strategies to characterize cellular kinetics. We then assess the distinct aspects of clinical pharmacology for ACTs in comparison to traditional small molecule and protein therapeutics. Additionally, we provide a review for the five FDA-approved CAR T-cell therapies and summarize their properties, cellular kinetic characteristics, dose-exposure-response relationship, and potential baseline factors/variables in product, patient, and regimen that may affect the safety and efficacy. Finally, we probe into existing empirical and mechanistic quantitative techniques to understand how various modeling and simulation approaches can support clinical pharmacology strategy and propose key considerations to be incorporated and explored in future models.
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Affiliation(s)
- Weize Huang
- Genentech Inc.South San FranciscoCaliforniaUSA
| | - Junyi Li
- Genentech Inc.South San FranciscoCaliforniaUSA
| | | | | | - Jiajie Yu
- Genentech Inc.South San FranciscoCaliforniaUSA
| | - Jing Jing
- Genentech Inc.South San FranciscoCaliforniaUSA
| | - Naoki Kotani
- Genentech Inc.South San FranciscoCaliforniaUSA,Chugai Pharmaceutical Co., Ltd.TokyoJapan
| | - Lynn Kamen
- Genentech Inc.South San FranciscoCaliforniaUSA
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9
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He JZ, Wang H, Lim K, Ren S, Rollins F, Vallaster M, Wong R, Stebbings R, Standifer N, Keefe R, Phipps A, Gibbs M. A Consideration of Fixed Dosing Versus Body Size-Based Dosing Strategies for Chimeric Antigen Receptor T-Cell Therapies. Clin Pharmacol Drug Dev 2022; 11:1130-1135. [PMID: 36094760 PMCID: PMC9826131 DOI: 10.1002/cpdd.1171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 08/19/2022] [Indexed: 01/27/2023]
Affiliation(s)
- Jimmy Zhijian He
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaGaithersburgMarylandUSA
| | - Hechuan Wang
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaGaithersburgMarylandUSA
| | - KyoungSoo Lim
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaGaithersburgMarylandUSA
| | - Song Ren
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaGaithersburgMarylandUSA
| | - Fred Rollins
- Competitive Intelligence and AnalysisOncology R&D, AstraZenecaGaithersburgMarylandUSA
| | - Markus Vallaster
- Clinical DevelopmentCell Therapies and Immuno‐Oncology, AstraZenecaWalthamMassachusettsUSA
| | - Ryan Wong
- Clinical Pharmacology and Safety SciencesBiopharmaceuticals R&D, AstraZenecaCambridgeUK
| | - Richard Stebbings
- Clinical Pharmacology and Safety SciencesBiopharmaceuticals R&D, AstraZenecaCambridgeUK
| | - Nathan Standifer
- Integrated BioanalysisClinical Pharmacology and Safety SciencesBiopharmaceuticals R&D, AstraZenecaSouth San FranciscoCaliforniaUSA
| | - Robert Keefe
- CMC DevelopmentCell Therapy, Oncology R&D, AstraZenecaGaithersburgMarylandUSA
| | - Alex Phipps
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaCambridgeUK
| | - Megan Gibbs
- Clinical Pharmacology and Quantitative PharmacologyBiopharmaceuticals R&D, AstraZenecaGaithersburgMarylandUSA
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10
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Kast J, Nozohouri S, Zhou D, Yago MR, Chen PW, Ahamadi M, Dutta S, Upreti VV. Recent advances and clinical pharmacology aspects of Chimeric Antigen Receptor (CAR) T-cellular therapy development. Clin Transl Sci 2022; 15:2057-2074. [PMID: 35677992 PMCID: PMC9468561 DOI: 10.1111/cts.13349] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 05/19/2022] [Accepted: 05/24/2022] [Indexed: 01/25/2023] Open
Abstract
Advances in immuno-oncology have provided a variety of novel therapeutics that harness the innate immune system to identify and destroy neoplastic cells. It is noteworthy that acceptable safety profiles accompany the development of these targeted therapies, which result in efficacious cancer treatment with higher survival rates and lower toxicities. Adoptive cellular therapy (ACT) has shown promising results in inducing sustainable remissions in patients suffering from refractory diseases. Two main types of ACT include engineered Chimeric Antigen Receptor (CAR) T cells and T cell receptor (TCR) T cells. The application of these immuno-therapies in the last few years has been successful and has demonstrated a safe and rapid treatment regimen for solid and non-solid tumors. The current review presents an insight into the clinical pharmacology aspects of immuno-therapies, especially CAR-T cells. Here, we summarize the current knowledge of TCR and CAR-T cell immunotherapy with particular focus on the structure of CAR-T cells, the effects and toxicities associated with these therapies in clinical trials, risk mitigation strategies, dose selection approaches, and cellular kinetics. Finally, the quantitative approaches and modeling techniques used in the development of CAR-T cell therapies are described.
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Affiliation(s)
- Johannes Kast
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., South San Francisco, California, USA
| | - Saeideh Nozohouri
- Department of Pharmaceutical Sciences, School of Pharmacy, Texas Tech University Health Sciences Center, Amarillo, Texas, USA
| | - Di Zhou
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., South San Francisco, California, USA
| | - Marc R Yago
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., South San Francisco, California, USA
| | - Po-Wei Chen
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., Thousand Oaks, California, USA
| | - Malidi Ahamadi
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., Thousand Oaks, California, USA
| | - Sandeep Dutta
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., Thousand Oaks, California, USA
| | - Vijay V Upreti
- Clinical Pharmacology, Modeling & Simulation, Amgen Inc., South San Francisco, California, USA
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11
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Parol W, Anderson GSF, Chapman MA. CAR-T cell therapies for cancer: what novel technologies are being developed for toxicity data? Expert Opin Drug Metab Toxicol 2022; 18:241-244. [PMID: 35686653 DOI: 10.1080/17425255.2022.2085551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 05/31/2022] [Indexed: 11/04/2022]
Affiliation(s)
- Wiktoria Parol
- University of Cambridge, MRC Toxicology Unit, Cambridge, UK
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12
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Mahasa KJ, Ouifki R, Eladdadi A, Pillis LD. A combination therapy of oncolytic viruses and chimeric antigen receptor T cells: a mathematical model proof-of-concept. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:4429-4457. [PMID: 35430822 DOI: 10.3934/mbe.2022205] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Combining chimeric antigen receptor T (CAR-T) cells with oncolytic viruses (OVs) has recently emerged as a promising treatment approach in preclinical studies that aim to alleviate some of the barriers faced by CAR-T cell therapy. In this study, we address by means of mathematical modeling the main question of whether a single dose or multiple sequential doses of CAR-T cells during the OVs therapy can have a synergetic effect on tumor reduction. To that end, we propose an ordinary differential equations-based model with virus-induced synergism to investigate potential effects of different regimes that could result in efficacious combination therapy against tumor cell populations. Model simulations show that, while the treatment with a single dose of CAR-T cells is inadequate to eliminate all tumor cells, combining the same dose with a single dose of OVs can successfully eliminate the tumor in the absence of virus-induced synergism. However, in the presence of virus-induced synergism, the same combination therapy fails to eliminate the tumor. Furthermore, it is shown that if the intensity of virus-induced synergy and/or virus oncolytic potency is high, then the induced CAR-T cell response can inhibit virus oncolysis. Additionally, the simulations show a more robust synergistic effect on tumor cell reduction when OVs and CAR-T cells are administered simultaneously compared to the combination treatment where CAR-T cells are administered first or after OV injection. Our findings suggest that the combination therapy of CAR-T cells and OVs seems unlikely to be effective if the virus-induced synergistic effects are included when genetically engineering oncolytic viral vectors.
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Affiliation(s)
- Khaphetsi Joseph Mahasa
- Department of Mathematics and Computer Science, National University of Lesotho, Roma 180, Maseru, Lesotho
| | - Rachid Ouifki
- Department of Mathematics and Applied Mathematics, North-West University, Mafikeng campus, Private Bag X2046, Mmabatho 2735, South Africa
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13
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Sussman M, Crivera C, Benner J, Adair N. Applying State-of-the-Art Survival Extrapolation Techniques to the Evaluation of CAR-T Therapies: Evidence from a Systematic Literature Review. Adv Ther 2021; 38:4178-4194. [PMID: 34251651 PMCID: PMC8342396 DOI: 10.1007/s12325-021-01841-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/22/2021] [Indexed: 12/28/2022]
Abstract
INTRODUCTION Traditional statistical techniques for extrapolating short-term survival data for anticancer therapies assume the same mortality rate for noncured and "cured" patients, which is appropriate for projecting survival of non-curative therapies but may lead to an underestimation of the treatment effectiveness for potentially curative therapies. Our objective was to ascertain research trends in survival extrapolation techniques used to project the survival benefits of chimeric antigen receptor T cell (CAR-T) therapies. METHODS A global systematic literature search produced a review of survival analyses of CAR-T therapies, published between January 1, 2015 and December 14, 2020, based on publications sourced from MEDLINE, scientific conferences, and health technology assessment agencies. Trends in survival extrapolation techniques used, and the rationale for selecting advanced techniques, are discussed. RESULTS Twenty publications were included, the majority of which (65%, N = 13) accounted for curative intent of CAR-T therapies through the use of advanced extrapolation techniques, i.e., mixture cure models [MCMs] (N = 10) or spline-based models (N = 3). The authors' rationale for using the MCM approach included (a) better statistical fits to the observed Kaplan-Meier curves (KMs) and (b) visual inspection of the KMs indicated that a proportion of patients experienced long-term remission and survival which is not inherently captured in standard parametric distributions. DISCUSSION Our findings suggest that an advanced extrapolation technique should be considered in base case survival analyses of CAR-T therapies when extrapolating short-term survival data to long-term horizons extending beyond the clinical trial duration. CONCLUSION Advanced extrapolation techniques allow researchers to account for the proportion of patients with an observed plateau in survival from clinical trial data; by only using standard-partitioned modeling, researchers may risk underestimating the survival benefits for the subset of patients with long-term remission. Sensitivity analysis with an alternative advanced extrapolation technique should be implemented and re-assessment using clinical trial extension data and/or real-world data should be conducted as longer-term data become available.
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Affiliation(s)
- Matthew Sussman
- Panalgo LLC, 265 Franklin Street, Suite 1101, Boston, MA, 02110, USA.
| | | | - Jennifer Benner
- Panalgo LLC, 265 Franklin Street, Suite 1101, Boston, MA, 02110, USA
| | - Nicholas Adair
- Panalgo LLC, 265 Franklin Street, Suite 1101, Boston, MA, 02110, USA
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Tosca EM, Bartolucci R, Magni P, Poggesi I. Modeling approaches for reducing safety-related attrition in drug discovery and development: a review on myelotoxicity, immunotoxicity, cardiovascular toxicity, and liver toxicity. Expert Opin Drug Discov 2021; 16:1365-1390. [PMID: 34181496 DOI: 10.1080/17460441.2021.1931114] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Introduction:Safety and tolerability is a critical area where improvements are needed to decrease the attrition rates during development of new drug candidates. Modeling approaches, when smartly implemented, can contribute to this aim.Areas covered:The focus of this review was on modeling approaches applied to four kinds of drug-induced toxicities: hematological, immunological, cardiovascular (CV) and liver toxicity. Papers, mainly published in the last 10 years, reporting models in three main methodological categories - computational models (e.g., quantitative structure-property relationships, machine learning approaches, neural networks, etc.), pharmacokinetic-pharmacodynamic (PK-PD) models, and quantitative system pharmacology (QSP) models - have been considered.Expert opinion:The picture observed in the four examined toxicity areas appears heterogeneous. Computational models are typically used in all areas as screening tools in the early stages of development for hematological, cardiovascular and liver toxicity, with accuracies in the range of 70-90%. A limited number of computational models, based on the analysis of drug protein sequence, was instead proposed for immunotoxicity. In the later stages of development, toxicities are quantitatively predicted with reasonably good accuracy using either semi-mechanistic PK-PD models (hematological and cardiovascular toxicity), or fully exploited QSP models (immuno-toxicity and liver toxicity).
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Affiliation(s)
- Elena M Tosca
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Roberta Bartolucci
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Paolo Magni
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Italo Poggesi
- Clinical Pharmacology & Pharmacometrics, Janssen Research & Development, Beerse, Belgium
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