1
|
Pasquiers B, Benamara S, Felices M, Ternant D, Declèves X, Puszkiel A. Translation of Monoclonal Antibodies Pharmacokinetics from Animal to Human Using Physiologically Based Modeling in Open Systems Pharmacology (OSP) Suite: A Retrospective Analysis of Bevacizumab. Pharmaceutics 2023; 15:2129. [PMID: 37631343 PMCID: PMC10459442 DOI: 10.3390/pharmaceutics15082129] [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: 07/03/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/27/2023] Open
Abstract
Interspecies translation of monoclonal antibodies (mAbs) pharmacokinetics (PK) in presence of target-mediated drug disposition (TMDD) is particularly challenging. Incorporation of TMDD in physiologically based PK (PBPK) modeling is recent and needs to be consolidated and generalized to provide better prediction of TMDD regarding inter-species translation during preclinical and clinical development steps of mAbs. The objective of this study was to develop a generic PBPK translational approach for mAbs using the open-source software (PK-Sim® and Mobi®). The translation of bevacizumab based on data in non-human primates (NHP), healthy volunteers (HV), and cancer patients was used as a case example for model demonstration purpose. A PBPK model for bevacizumab concentration-time data was developed using data from literature and the Open Systems Pharmacology (OSP) Suite version 10. PK-sim® was used to build the linear part of bevacizumab PK (mainly FcRn-mediated), whereas MoBi® was used to develop the target-mediated part. The model was first developed for NHP and used for a priori PK prediction in HV. Then, the refined model obtained in HV was used for a priori prediction in cancer patients. A priori predictions were within 2-fold prediction error (predicted/observed) for both area under the concentration-time curve (AUC) and maximum concentration (Cmax) and all the predicted concentrations were within 2-fold average fold error (AFE) and average absolute fold error (AAFE). Sensitivity analysis showed that FcRn-mediated distribution and elimination processes must be accounted for at all mAb concentration levels, whereas the lower the mAb concentration, the more significant the target-mediated elimination. This project is the first step to generalize the full PBPK translational approach in Model-Informed Drug Development (MIDD) of mAbs using OSP Suite.
Collapse
Affiliation(s)
- Blaise Pasquiers
- Inserm UMR-S1144, Faculty of Pharmacy, Université Paris Cité, 75006 Paris, France (A.P.)
- PhinC Development, 91300 Massy, France
| | | | | | - David Ternant
- Faculty of Medicine, Université de Tours, EA 4245 T2I, 37032 Tours, France
- Service de Pharmacologie Médicale, CHRU de Tours, 37000 Tours, France
| | - Xavier Declèves
- Inserm UMR-S1144, Faculty of Pharmacy, Université Paris Cité, 75006 Paris, France (A.P.)
- Biologie du Médicament—Toxicologie, Hôpital Cochin, Assistance Publique Hôpitaux de Paris, 75014 Paris, France
| | - Alicja Puszkiel
- Inserm UMR-S1144, Faculty of Pharmacy, Université Paris Cité, 75006 Paris, France (A.P.)
- Biologie du Médicament—Toxicologie, Hôpital Cochin, Assistance Publique Hôpitaux de Paris, 75014 Paris, France
| |
Collapse
|
2
|
Beaudoin JJ, Clemens L, Miedel MT, Gough A, Zaidi F, Ramamoorthy P, Wong KE, Sarangarajan R, Battista C, Shoda LKM, Siler SQ, Taylor DL, Howell BA, Vernetti LA, Yang K. The Combination of a Human Biomimetic Liver Microphysiology System with BIOLOGXsym, a Quantitative Systems Toxicology (QST) Modeling Platform for Macromolecules, Provides Mechanistic Understanding of Tocilizumab- and GGF2-Induced Liver Injury. Int J Mol Sci 2023; 24:9692. [PMID: 37298645 PMCID: PMC10253699 DOI: 10.3390/ijms24119692] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/25/2023] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Biologics address a range of unmet clinical needs, but the occurrence of biologics-induced liver injury remains a major challenge. Development of cimaglermin alfa (GGF2) was terminated due to transient elevations in serum aminotransferases and total bilirubin. Tocilizumab has been reported to induce transient aminotransferase elevations, requiring frequent monitoring. To evaluate the clinical risk of biologics-induced liver injury, a novel quantitative systems toxicology modeling platform, BIOLOGXsym™, representing relevant liver biochemistry and the mechanistic effects of biologics on liver pathophysiology, was developed in conjunction with clinically relevant data from a human biomimetic liver microphysiology system. Phenotypic and mechanistic toxicity data and metabolomics analysis from the Liver Acinus Microphysiology System showed that tocilizumab and GGF2 increased high mobility group box 1, indicating hepatic injury and stress. Tocilizumab exposure was associated with increased oxidative stress and extracellular/tissue remodeling, and GGF2 decreased bile acid secretion. BIOLOGXsym simulations, leveraging the in vivo exposure predicted by physiologically-based pharmacokinetic modeling and mechanistic toxicity data from the Liver Acinus Microphysiology System, reproduced the clinically observed liver signals of tocilizumab and GGF2, demonstrating that mechanistic toxicity data from microphysiology systems can be successfully integrated into a quantitative systems toxicology model to identify liabilities of biologics-induced liver injury and provide mechanistic insights into observed liver safety signals.
Collapse
Affiliation(s)
- James J. Beaudoin
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lara Clemens
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Mark T. Miedel
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Albert Gough
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Fatima Zaidi
- Metabolon Inc., Durham, NC 27713, USA (P.R.); (K.E.W.); (R.S.)
| | | | - Kari E. Wong
- Metabolon Inc., Durham, NC 27713, USA (P.R.); (K.E.W.); (R.S.)
| | | | - Christina Battista
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lisl K. M. Shoda
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Scott Q. Siler
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - D. Lansing Taylor
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Brett A. Howell
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| | - Lawrence A. Vernetti
- Department of Computational and Systems Biology, Drug Discovery Institute, University of Pittsburgh, Pittsburgh, PA 15219, USA (A.G.); (D.L.T.)
| | - Kyunghee Yang
- DILIsym Services Division, Simulations Plus Inc., Research Triangle Park, Durham, NC 27709, USA (S.Q.S.)
| |
Collapse
|
3
|
Lu D, Yadav R, Holder P, Chiang E, Sanjabi S, Poon V, Bernett M, Varma R, Liu K, Leung I, Bogaert L, Desjarlais J, Shivva V, Hosseini I, Ramanujan S. Complex PK-PD of an engineered IL-15/IL-15Rα-Fc fusion protein in cynomolgus monkeys: QSP modeling of lymphocyte dynamics. Eur J Pharm Sci 2023; 186:106450. [PMID: 37084985 DOI: 10.1016/j.ejps.2023.106450] [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: 10/27/2022] [Revised: 03/29/2023] [Accepted: 04/18/2023] [Indexed: 04/23/2023]
Abstract
XmAb24306 is a lymphoproliferative interleukin (IL)-15/IL-15 receptor α (IL-15Rα) Fc-fusion protein currently under clinical investigation as an immunotherapeutic agent for cancer treatment. XmAb24306 contains mutations in IL-15 that attenuate its affinity to the heterodimeric IL-15 receptor βγ (IL-15R). We observe substantially prolonged pharmacokinetics (PK) (half-life ∼ 2.5 to 4.5 days) in single- and repeat-dose cynomolgus monkey (cyno) studies compared to wild-type IL-15 (half-life ∼ 1 hour), leading to increased exposure and enhanced and durable expansion of NK cells, CD8+ T cells and CD4-CD8- (double negative [DN]) T cells. Drug clearance varied with dose level and time post-dose, and PK exposure decreased upon repeated dosing, which we attribute to increased target-mediated drug disposition (TMDD) resulting from drug-induced lymphocyte expansion (i.e., pharmacodynamic (PD)-enhanced TMDD). We developed a quantitative systems pharmacology (QSP) model to quantify the complex PKPD behaviors due to the interactions of XmAb24306 with multiple cell types (CD8+, CD4+, DN T cells, and NK cells) in the peripheral blood (PB) and lymphoid tissues. The model, which includes nonspecific drug clearance, binding to and TMDD by IL15R differentially expressed on lymphocyte subsets, and resultant lymphocyte margination/migration out of PB, expansion in lymphoid tissues, and redistribution to the blood, successfully describes the systemic PK and lymphocyte kinetics observed in the cyno studies. Results suggest that after 3 doses of every-two-week (Q2W) doses up to 70 days, the relative contributions of each elimination pathway to XmAb24306 clearance are: DN T cells > NK cells > CD8+ T cells > nonspecific clearance > CD4+ T cells. Modeling suggests that observed cellular expansion in blood results from the influx of cells expanded by the drug in lymphoid tissues. The model is used to predict lymphoid tissue expansion and to simulate PK-PD for different dose regimens. Thus, the model provides insight into the mechanisms underlying the observed PK-PD behavior of an engineered cytokine and can serve as a framework for the rapid integration and analysis of data that emerges from ongoing clinical studies in cancer patients as single-agent or given in combination.
Collapse
Affiliation(s)
- Dan Lu
- Genentech, Inc., South San Francisco, CA, USA.
| | | | | | | | | | - Victor Poon
- Genentech, Inc., South San Francisco, CA, USA
| | | | | | - Ke Liu
- Xencor, Inc. Monrovia, CA, USA
| | | | | | | | | | | | | |
Collapse
|
4
|
Hu S, Datta-Mannan A, D'Argenio DZ. Monoclonal Antibody Pharmacokinetics in Cynomolgus Monkeys Following Subcutaneous Administration: Physiologically Based Model Predictions from Physiochemical Properties. AAPS J 2022; 25:5. [PMID: 36456779 DOI: 10.1208/s12248-022-00772-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022] Open
Abstract
An integrated physiologically based modeling framework is presented for predicting pharmacokinetics and bioavailability of subcutaneously administered monoclonal antibodies in cynomolgus monkeys, based on in silico structure-derived metrics characterizing antibody size, overall charge, local charge, and hydrophobicity. The model accounts for antibody-specific differences in pinocytosis, transcapillary transport, local lymphatic uptake, and pre-systemic degradation at the subcutaneous injection site and reliably predicts the pharmacokinetics of five different wild-type mAbs and their Fc variants following intravenous and subcutaneous administration. Significant associations were found between subcutaneous injection site degradation rate and the antibody's local positive charge of its complementarity-determining region (R = 0.56, p = 0.0012), antibody pinocytosis rate and its overall positive charge (R = 0.59, p = 0.00063), and antibody paracellular transport and its overall charge together with hydrophobicity (R = 0.63, p = 0.00096). Based on these results, population simulations were performed to predict the relationship between bioavailability and antibody local positive charge. In addition, model simulations were conducted to calculate the relative contribution of absorption pathways (lymphatic and blood), pre-systemic degradation pathways (interstitial and lysosomal), and the influence of injection site lymph flow on antibody bioavailability and pharmacokinetics. The proposed physiologically based modeling framework integrates fundamental mechanisms governing antibody subcutaneous absorption and disposition, with structured-based physiochemical properties, to predict antibody bioavailability and pharmacokinetics in vivo.
Collapse
Affiliation(s)
- Shihao Hu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, 90089, USA
| | - Amita Datta-Mannan
- Department of Exploratory Medicine and Pharmacology, Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, Indiana, USA
| | - David Z D'Argenio
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, 90089, USA.
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Liu S, Shah DK. Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics. Drug Metab Dispos 2022; 50:867-878. [PMID: 35197311 PMCID: PMC11022906 DOI: 10.1124/dmd.121.000460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 01/31/2022] [Indexed: 11/22/2022] Open
Abstract
Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.
Collapse
Affiliation(s)
- Shufang Liu
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, Buffalo, New York
| | - Dhaval K Shah
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, Buffalo, New York
| |
Collapse
|
7
|
Haraya K, Tsutsui H, Komori Y, Tachibana T. Recent Advances in Translational Pharmacokinetics and Pharmacodynamics Prediction of Therapeutic Antibodies Using Modeling and Simulation. Pharmaceuticals (Basel) 2022; 15:ph15050508. [PMID: 35631335 PMCID: PMC9145563 DOI: 10.3390/ph15050508] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 04/18/2022] [Accepted: 04/20/2022] [Indexed: 02/05/2023] Open
Abstract
Therapeutic monoclonal antibodies (mAbs) have been a promising therapeutic approach for several diseases and a wide variety of mAbs are being evaluated in clinical trials. To accelerate clinical development and improve the probability of success, pharmacokinetics and pharmacodynamics (PKPD) in humans must be predicted before clinical trials can begin. Traditionally, empirical-approach-based PKPD prediction has been applied for a long time. Recently, modeling and simulation (M&S) methods have also become valuable for quantitatively predicting PKPD in humans. Although several models (e.g., the compartment model, Michaelis–Menten model, target-mediated drug disposition model, and physiologically based pharmacokinetic model) have been established and used to predict the PKPD of mAbs in humans, more complex mechanistic models, such as the quantitative systemics pharmacology model, have been recently developed. This review summarizes the recent advances and future direction of M&S-based approaches to the quantitative prediction of human PKPD for mAbs.
Collapse
Affiliation(s)
- Kenta Haraya
- Discovery Biologics Department, Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba 412-8513, Japan;
- Correspondence:
| | - Haruka Tsutsui
- Discovery Biologics Department, Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba 412-8513, Japan;
| | - Yasunori Komori
- Pharmaceutical Science Department, Translational Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba 412-8513, Japan; (Y.K.); (T.T.)
| | - Tatsuhiko Tachibana
- Pharmaceutical Science Department, Translational Research Division, Chugai Pharmaceutical Co., Ltd., 1-135 Komakado, Gotemba 412-8513, Japan; (Y.K.); (T.T.)
| |
Collapse
|
8
|
Bolleddula J, Brady K, Bruin G, Lee AJ, Martin JA, Walles M, Xu K, Yang TY, Zhu X, Yu H. Absorption, Distribution, Metabolism, and Excretion (ADME) of Therapeutic Proteins: Current Industry Practices and Future Perspectives. Drug Metab Dispos 2022; 50:837-845. [PMID: 35149541 DOI: 10.1124/dmd.121.000461] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 01/05/2022] [Indexed: 11/22/2022] Open
Abstract
Therapeutics proteins (TPs) comprise a variety of modalities including antibody-based drugs, coagulation factors, recombinant cytokines, enzymes, growth factors, and hormones. TPs usually cannot traverse cellular barriers and exert their pharmacological activity by interacting with targets on the exterior membrane of cells or with soluble ligands in the tissue interstitial fluid/blood. Due to large size, lack of cellular permeability, variation in metabolic fate, and distinct physicochemical characteristics, TPs are subject to different absorption, distribution, metabolism, and excretion (ADME) processes as compared to small molecules. Limited regulatory guidance makes it challenging to determine the most relevant ADME data required for regulatory submissions. The TP ADME working group (WG) was sponsored by the Translational and ADME Sciences Leadership Group (TALG) within the Innovation and Quality (IQ) consortium with objectives to: i) better understand the current practices of ADME data generated for TPs across IQ member companies, ii) learn about their regulatory strategy and interaction experiences, and iii) provide recommendations on best practices for conducting ADME studies. To understand current ADME practices and regulatory strategies, an industry-wide survey was conducted within IQ member companies. In addition, ADME data submitted to FDA was also collated by reviewing regulatory submission packages of TPs approved between 2011-2020. This article summarizes the key learnings from the survey and an overview of ADME data presented in BLAs along with future perspectives and recommendations for conducting ADME studies for internal decision making as well as regulatory submissions for TPs. Significance Statement This article provides comprehensive assessment of the current practices of absorption, distribution, metabolism, and excretion (ADME) data generated for therapeutic proteins across the Innovation and Quality (IQ) participating companies and the utility of the data in discovery, development, and regulatory submissions. The TP ADME working group (WG) working group also recommends the best practices for conducting ADME studies for internal decision making and regulatory submissions.
Collapse
Affiliation(s)
| | | | - Gerard Bruin
- Novartis Institutes for Biomedical Research, Switzerland
| | | | | | - Markus Walles
- DMPK, Novartis Institutes for Biomedical Research, Switzerland
| | | | | | | | - Hongbin Yu
- Boehringer Ingelheim Pharmaceuticals, Inc, United States
| |
Collapse
|
9
|
Ménochet K, Yu H, Wang B, Tibbitts J, Hsu CP, Kamath AV, Richter WF, Baumann A. Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper. MAbs 2022; 14:2145997. [PMID: 36418217 PMCID: PMC9704389 DOI: 10.1080/19420862.2022.2145997] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.
Collapse
Affiliation(s)
- Karelle Ménochet
- Quantitative Discovery and Development, UCB, Slough, UK,CONTACT Karelle Ménochet Quantitative Discovery and Development, UCB, Slough, UK
| | - Hongbin Yu
- R&D Project Management and Development Strategies, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA
| | - Bonnie Wang
- Nonclinical Disposition and Bioanalysis, Bristol Myers Squibb, Inc, Princeton, NJ, USA
| | - Jay Tibbitts
- Nonclinical Development, South San Francisco, CA, USA
| | - Cheng-Pang Hsu
- Preclinical Development and Clinical Pharmacology, AskGene Pharma Inc, Camarillo, CA, USA
| | - Amrita V. Kamath
- Preclinical and Translational Pharmacokinetics and Pharmacodynamics, Genentech Inc, South San Francisco, CA, USA
| | - Wolfgang F. Richter
- Roche Pharma Research and Early Development, Roche Innovation, Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Andreas Baumann
- R&D, Bayer Pharma AG, Berlin, Germany & Non-clinical Biotech Consulting, Potsdam, Germany °(° present affiliation)
| |
Collapse
|
10
|
Singh R, Moreno M, Stanimirovic D. Comparison of Various Approaches to Translate Non-Linear Pharmacokinetics of Monoclonal Antibodies from Cynomolgus Monkey to Human. Eur J Drug Metab Pharmacokinet 2021; 46:555-567. [PMID: 34120326 DOI: 10.1007/s13318-021-00691-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND AND OBJECTIVES The prediction of pharmacokinetics of monoclonal antibodies (mAbs) exhibiting non-linear pharmacokinetics in preclinical species to human is challenging, and very limited scientific work has been published in this field of research. Therefore, we have conducted an elaborate comparative assessment to determine the most reliable preclinical to clinical scaling strategy for mAbs with non-linear pharmacokinetics. METHODS We have compared three different scaling approaches to predict human pharmacokinetics from cynomolgus monkey. In the first approach, cynomolgus monkey pharmacokinetic parameters estimated using a two-compartment model with parallel linear and non-linear elimination were allometrically scaled to simulate human pharmacokinetics. In the second approach, allometric exponents were integrated with a minimal physiologically based pharmacokinetic (mPBPK) model to translate human pharmacokinetics. In the third approach, we have employed a species time-invariant method, wherein a two-compartment model with parallel linear and non-linear elimination was used as a framework model for simulation of the human profile. RESULTS Human exposure parameters projected by an integrated allometric method were only within two fold for approximately 45-70% of predictions at different doses of five mAbs evaluated, while approximately 70-80% of Cmax and AUC predictions by integrated mPBPK modelling as well as the species time-invariant method were within two-fold error. The average fold error for clearance predictions by the integrated mPBPK method was 1.10-1.45 fold, whilst for the species time-variant and integrated allometric methods, the average fold error was between 1.04 and 1.37 fold and 1.24 and 2.13 fold, respectively. CONCLUSIONS Our findings suggest that the species time-variant method and mPBPK proposed by us can be employed to reliably translate non-linear pharmacokinetics of mAbs from cynomolgus monkey to human.
Collapse
Affiliation(s)
- Renu Singh
- Translation Bioscience, Human Health Therapeutics, National Research Council of Canada, Ottawa, ON, Canada. .,Global DMPK, Research IVIVT, 1250 S. Collegeville Road, Collegeville, PA, 19426, USA. .,Translation Bioscience, Human Health Therapeutics, National Research Council of Canada, Montreal, QC, Canada.
| | - Maria Moreno
- Translation Bioscience, Human Health Therapeutics, National Research Council of Canada, Ottawa, ON, Canada
| | - Danica Stanimirovic
- Translation Bioscience, Human Health Therapeutics, National Research Council of Canada, Ottawa, ON, Canada
| |
Collapse
|
11
|
Glassman PM, Myerson JW, Ferguson LT, Kiseleva RY, Shuvaev VV, Brenner JS, Muzykantov VR. Targeting drug delivery in the vascular system: Focus on endothelium. Adv Drug Deliv Rev 2020; 157:96-117. [PMID: 32579890 PMCID: PMC7306214 DOI: 10.1016/j.addr.2020.06.013] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 06/12/2020] [Accepted: 06/13/2020] [Indexed: 12/16/2022]
Abstract
The bloodstream is the main transporting pathway for drug delivery systems (DDS) from the site of administration to the intended site of action. In many cases, components of the vascular system represent therapeutic targets. Endothelial cells, which line the luminal surface of the vasculature, play a tripartite role of the key target, barrier, or victim of nanomedicines in the bloodstream. Circulating DDS may accumulate in the vascular areas of interest and in off-target areas via mechanisms bypassing specific molecular recognition, but using ligands of specific vascular determinant molecules enables a degree of precision, efficacy, and specificity of delivery unattainable by non-affinity DDS. Three decades of research efforts have focused on specific vascular targeting, which have yielded a multitude of DDS, many of which are currently undergoing a translational phase of development for biomedical applications, including interventions in the cardiovascular, pulmonary, and central nervous systems, regulation of endothelial functions, host defense, and permeation of vascular barriers. We discuss the design of endothelial-targeted nanocarriers, factors underlying their interactions with cells and tissues, and describe examples of their investigational use in models of acute vascular inflammation with an eye on translational challenges.
Collapse
Affiliation(s)
- Patrick M Glassman
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America.
| | - Jacob W Myerson
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Laura T Ferguson
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America; Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Raisa Y Kiseleva
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Vladimir V Shuvaev
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Jacob S Brenner
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America; Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Vladimir R Muzykantov
- Department of Systems Pharmacology and Translational Therapeutics, Center for Targeted Therapeutics and Translational Nanomedicine of the Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America.
| |
Collapse
|
12
|
Chang HP, Kim SJ, Shah DK. Whole-Body Pharmacokinetics of Antibody in Mice Determined using Enzyme-Linked Immunosorbent Assay and Derivation of Tissue Interstitial Concentrations. J Pharm Sci 2020; 110:446-457. [PMID: 32502472 DOI: 10.1016/j.xphs.2020.05.025] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 05/06/2020] [Accepted: 05/20/2020] [Indexed: 12/20/2022]
Abstract
Here we have reported whole-body disposition of wild-type IgG and FcRn non-binding IgG in mice, determined using Enzyme-Linked Immunosorbent Assay (ELISA). The disposition data generated using ELISA are compared with previously published biodistribution data generated using radiolabelled IgG. In addition, we introduce a novel concept of ABCIS values, which are defined as percentage ratios of tissue interstitial and plasma AUC values. These values can help in predicting tissue interstitial concentrations of monoclonal antibodies (mAbs) based on the plasma concentrations. Tissue interstitial concentrations derived from our study are also compared with previously reported values measured using microdialysis or centrifugation method. Lastly, the new set of biodistribution data generated using ELISA are used to refine the PBPK model for mAbs.
Collapse
Affiliation(s)
- Hsuan-Ping Chang
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Se Jin Kim
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, Buffalo, NY, USA
| | - Dhaval K Shah
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, Buffalo, NY, USA.
| |
Collapse
|
13
|
Conner KP, Devanaboyina SC, Thomas VA, Rock DA. The biodistribution of therapeutic proteins: Mechanism, implications for pharmacokinetics, and methods of evaluation. Pharmacol Ther 2020; 212:107574. [PMID: 32433985 DOI: 10.1016/j.pharmthera.2020.107574] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 04/30/2020] [Indexed: 02/08/2023]
Abstract
Therapeutic proteins (TPs) are a diverse drug class that include monoclonal antibodies (mAbs), recombinantly expressed enzymes, hormones and growth factors, cytokines (e.g. chemokines, interleukins, interferons), as well as a wide range of engineered fusion scaffolds containing IgG1 Fc domain for half-life extension. As the pharmaceutical industry advances more potent and selective protein-based medicines through discovery and into the clinical stages of development, it has become widely appreciated that a comprehensive understanding of the mechanisms of TP biodistribution can aid this endeavor. This review aims to highlight the literature that has advanced our understanding of the determinants of TP biodistribution. A particular emphasis is placed on the multi-faceted role of the neonatal Fc receptor (FcRn) in mAb and Fc-fusion protein disposition. In addition, characterization of the TP-target interaction at the cell-level is discussed as an essential strategy to establish pharmacokinetic-pharmacodynamic (PK/PD) relationships that may lead to more informed human dose projections during clinical development. Methods for incorporation of tissue and cell-level parameters defining these characteristics into higher-order mechanistic and semi-mechanistic PK models will also be presented.
Collapse
Affiliation(s)
- Kip P Conner
- Dept. of Pharmacokinetics and Drug Metabolism, Amgen Inc, 1120 Veterans Blvd, South San Francisco, CA 94080, USA.
| | - Siva Charan Devanaboyina
- Dept. of Pharmacokinetics and Drug Metabolism, Amgen Inc, 1120 Veterans Blvd, South San Francisco, CA 94080, USA.
| | - Veena A Thomas
- Dept. of Pharmacokinetics and Drug Metabolism, Amgen Inc, 1120 Veterans Blvd, South San Francisco, CA 94080, USA.
| | - Dan A Rock
- Dept. of Pharmacokinetics and Drug Metabolism, Amgen Inc, 1120 Veterans Blvd, South San Francisco, CA 94080, USA.
| |
Collapse
|
14
|
Glassman PM, Balthasar JP. Physiologically-based modeling of monoclonal antibody pharmacokinetics in drug discovery and development. Drug Metab Pharmacokinet 2019; 34:3-13. [PMID: 30522890 PMCID: PMC6378116 DOI: 10.1016/j.dmpk.2018.11.002] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 09/11/2018] [Accepted: 11/19/2018] [Indexed: 12/20/2022]
Abstract
Over the past few decades, monoclonal antibodies (mAbs) have become one of the most important and fastest growing classes of therapeutic molecules, with applications in a wide variety of disease areas. As such, understanding of the determinants of mAb pharmacokinetic (PK) processes (absorption, distribution, metabolism, and elimination) is crucial in developing safe and efficacious therapeutics. In the present review, we discuss the use of physiologically-based pharmacokinetic (PBPK) models as an approach to characterize the in vivo behavior of mAbs, in the context of the key PK processes that should be considered in these models. Additionally, we discuss current and potential future applications of PBPK in the drug discovery and development timeline for mAbs, spanning from identification of potential target molecules to prediction of potential drug-drug interactions. Finally, we conclude with a discussion of currently available PBPK models for mAbs that could be implemented in the drug development process.
Collapse
Affiliation(s)
- Patrick M Glassman
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, 14214 United States; Department of Pharmacology, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104 United States
| | - Joseph P Balthasar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY, 14214 United States.
| |
Collapse
|
15
|
Hardiansyah D, Ng CM. Minimal physiologically-based pharmacokinetic model to investigate the effect of pH dependent FcRn affinity and the endothelial endocytosis on the pharmacokinetics of anti-VEGF humanized IgG1 antibody in cynomolgus monkey. Eur J Pharm Sci 2018; 125:130-141. [PMID: 30248389 DOI: 10.1016/j.ejps.2018.09.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 09/17/2018] [Accepted: 09/18/2018] [Indexed: 11/29/2022]
Abstract
In this study, we developed a first minimal physiologically-based pharmacokinetic (mPBPK) model to investigate the complex interaction effects of endocytosis rate/FcRn binding affinity at both acidic/physiological pH on the pharmacokinetics (PK) of the anti-VEGF IgG1 antibodies. The data used in this study were the PK of the native IgG and humanized anti-VEGF IgG1 antibodies with a wide range FcRn-binding at both acidic and physiological pH in the cynomolgus monkey. The basic structure of the developed mPBPK models consisted of plasma, tissue and lymph compartments. The tissue compartment was subdivided into vascular, endothelial and interstitial spaces. Non-equilibrium binding mechanism was used to describe the FcRn-IgG interaction in the endosome. The fittings in the final model with three pH systems in the endosome compartment showed a good fit based on the visualization of the fitted graphs and the coefficient of variations of the estimated parameters (CV < 50%). The quantitative endocytosis/FcRn binding affinity PK relationships was constructed using the final model to provide better understanding of complex interaction effects of endocytosis rate and FcRn binding on PK of anti-VEGF IgG1 antibodies. This result may serve as an important model-based drug discovery platform to guide the design and development of the future generation of anti-VEGF IgG1 or other therapeutic IgG1 antibodies. In addition, the mPBPK model developed in cynomolgus monkey was successfully used to predict the PK of the anti-VEGF IgG1 antibody (bevacizumab) in human subjects.
Collapse
Affiliation(s)
- Deni Hardiansyah
- College of Pharmacy, University of Kentucky, BioPharm Building, Room 341, 789 S. Limestone, Lexington, KY 40536, USA
| | - Chee Meng Ng
- College of Pharmacy, University of Kentucky, BioPharm Building, Room 341, 789 S. Limestone, Lexington, KY 40536, USA.
| |
Collapse
|
16
|
Li T, Balthasar JP. Development and Evaluation of a Physiologically Based Pharmacokinetic Model for Predicting the Effects of Anti-FcRn Therapy on the Disposition of Endogenous IgG in Humans. J Pharm Sci 2018; 108:714-724. [PMID: 30471293 DOI: 10.1016/j.xphs.2018.10.067] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 10/28/2018] [Accepted: 10/30/2018] [Indexed: 11/18/2022]
Abstract
This work scaled up a previously developed physiologically based pharmacokinetic model to predict the effects of anti-FcRn agents on the disposition of endogenous IgG in human subjects. Simulations were performed with the scaled model to predict the effects of single- and multiple-dose administration of anti-FcRn monoclonal antibodies (1-256 mg/kg) and high-dose intravenous immune globulin (0.4-2 g/kg). The model was evaluated for prediction accuracy through comparison to the effects of rozanolixizumab, an anti-FcRn monoclonal antibodies under current clinical evaluation, on the disposition of endogenous IgG in healthy human subjects. The model provided reasonably accurate predictions of the effects of rozanolixizumab. Prediction errors for the maximum reduction in endogenous IgG concentrations were -8.50% (90% model prediction interval: -14.0% to 1.44%), 3.33% (90% model prediction interval: -13.9% to 21.2%), and 6.85% (90% model prediction interval: -35.2% to 10.5%) for rozanolixizumab doses of 1, 4, and 7 mg/kg, respectively. Model simulations predict that anti-FcRn therapies will exhibit greater dose potency in healthy volunteers than in patients with elevated IgG production rates (e.g., as typically found in autoimmune disease). The model appears to have potential for use in assessing and predicting novel dosing strategies for anti-FcRn therapies.
Collapse
Affiliation(s)
- Tommy Li
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14214
| | - Joseph P Balthasar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14214.
| |
Collapse
|
17
|
Li T, Balthasar JP. Application of Physiologically Based Pharmacokinetic Modeling to Predict the Effects of FcRn Inhibitors in Mice, Rats, and Monkeys. J Pharm Sci 2018; 108:701-713. [PMID: 30423340 DOI: 10.1016/j.xphs.2018.10.065] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 10/28/2018] [Accepted: 10/30/2018] [Indexed: 01/06/2023]
Abstract
There is a growing interest in developing inhibitors of the neonatal Fc-receptor, FcRn, for use in the treatment for humoral autoimmune conditions. We have developed a new physiologically based pharmacokinetic model that is capable of characterizing the pharmacokinetics and pharmacodynamics of anti-FcRn monoclonal antibodies (mAb) in mice, rats, and monkeys. The model includes incorporation of FcRn recycling of immune gamma globulin (IgG) in hematopoietic cells in addition to FcRn recycling of IgG in vascular endothelial cells and considers FcRn turnover and intracellular cycling. The model captured antibody disposition in wild-type and FcRn-knockout mice and rats, and also predicted the effects of intravenous immune globulin and anti-FcRn mAb on IgG disposition. Simulations predicted the change in IgG clearance in response to intravenous immune globulin with good accuracy in rats (mean prediction error of 7.15% ± 7.67%). In monkeys, prediction windows for simulated IgG concentration versus time data, as generated through Monte Carlo simulation, were able to capture the effects of anti-FcRn mAb on endogenous IgG. The model may have utility in guiding preclinical evaluations of anti-FcRn therapies in development, potentially assisting in the identification of optimal dosing strategies for this emerging class of immunosuppressive drugs.
Collapse
Affiliation(s)
- Tommy Li
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14214
| | - Joseph P Balthasar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14214.
| |
Collapse
|
18
|
Polli JR, Engler FA, Balthasar JP. Physiologically Based Modeling of the Pharmacokinetics of "Catch-and-Release" Anti-Carcinoembryonic Antigen Monoclonal Antibodies in Colorectal Cancer Xenograft Mouse Models. J Pharm Sci 2018; 108:674-691. [PMID: 30321546 DOI: 10.1016/j.xphs.2018.09.037] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 09/21/2018] [Accepted: 09/24/2018] [Indexed: 10/28/2022]
Abstract
Engineered monoclonal antibodies (mAbs) with pH-sensitive target release, or "catch-and-release" (CAR) binding, have shown promise in decreasing the extent of target-mediated mAb elimination, increasing mAb exposure, and increasing dose potency. This study developed a mechanistic physiologically based pharmacokinetic (PBPK) model to evaluate the effects of pH-sensitive CAR target binding on the disposition of anti-carcinoembryonic antigen (CEA) mAbs in mouse models of colorectal cancer. The PBPK model was qualified by comparing model-predicted plasma concentration-time data with data observed in tumor-bearing mice following the administration of T84.66, a "standard" anti-CEA mAb that demonstrates strong binding at pH 7.4 and 5.5. Further simulations evaluated the effects CAR pH-dependent binding, with decreasing CEA affinity with decreasing pH, on anti-CEA mAb plasma pharmacokinetics. Simulated data were compared with data observed for a novel CAR mAb, 10H6. The PBPK model provided precise parameter estimates, and excellent data characterization (median prediction error 18.4%) following fitting to T84.66 data. Simulations well predicted 10H6 data (median prediction error 21.4%). Sensitivity analyses demonstrated that key determinants of the disposition of CAR mAbs include the following: antigen binding affinity, the rate constant of mAb-CEA dissociation in acidified endosomes, antigen concentration, and the tumor vasculature reflection coefficient.
Collapse
Affiliation(s)
- Joseph Ryan Polli
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14215
| | - Frank A Engler
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14215
| | - Joseph P Balthasar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, Buffalo, New York 14215.
| |
Collapse
|
19
|
Hardiansyah D, Ng CM. Effects of the FcRn developmental pharmacology on the pharmacokinetics of therapeutic monoclonal IgG antibody in pediatric subjects using minimal physiologically-based pharmacokinetic modelling. MAbs 2018; 10:1144-1156. [PMID: 29969360 DOI: 10.1080/19420862.2018.1494479] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
The aim of this study was to investigate neonatal Fc receptor (FcRn) concentration developmental pharmacology in adult and pediatric subjects using minimal physiologically-based pharmacokinetic (mPBPK) modelling. Three types of pharmacokinetic (PK) data for three agents (endogenous/exogenous native IgG, bevacizumab and palivizumab) were used. The adult group contained six subjects with weights from 50 to 100 kg. For pediatric subjects, seven age groups were assumed, with five subjects each having the weight of 95%, 75%, 50%, 25% and 5% percentile of the population. A first evidence-based rating system to evaluate the quality of the source data used to derive pediatric-specific mPBPK model parameter was proposed. A stepwise approach was used to examine the best combination of age/weight effect on the parameters of the mPBPK model in adult and pediatric subjects. IgG synthesis rate (Ksyn), extravasation rate (ER) and FcRn were fitted simultaneously to the PK of bevacizumab and native-IgG in both adult and pediatric. All fitting showed good fits based on the graphs and the coefficient of variation of the fitted parameters (< 50%). Estimated weight-normalized Ksyn increased while weight-normalized FcRn and ER decreased with increasing age. The age and weight effect on FcRn were successfully estimated from the data. The final mPBPK model developed with native IgG and bevacizumab was able to predict the PK of palivizumab in pediatric subjects. Implementation of the mPBPK model enables us to analyze the relationships of age, weight, FcRn, ER and Ksyn in both adult and pediatric subject. This information may benefit the understanding of complex interaction between the FcRn developmental pharmacology and PK parameters, and improve the prediction of the antibody disposition in pediatric subjects.
Collapse
Affiliation(s)
- Deni Hardiansyah
- a College of Pharmacy , University of Kentucky , Lexington , USA
| | - Chee Meng Ng
- a College of Pharmacy , University of Kentucky , Lexington , USA
| |
Collapse
|
20
|
Application of Pharmacokinetics Modelling to Predict Human Exposure of a Cationic Liposomal Subunit Antigen Vaccine System. Pharmaceutics 2017; 9:pharmaceutics9040057. [PMID: 29215597 PMCID: PMC5750663 DOI: 10.3390/pharmaceutics9040057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 11/18/2017] [Accepted: 12/04/2017] [Indexed: 12/02/2022] Open
Abstract
The pharmacokinetics of a liposomal subunit antigen vaccine system composed of the cationic lipid dimethyldioctadecylammonium bromide (DDA) and the immunostimulatory agent trehalose 6,6-dibehenate (TDB) (8:1 molar ratio) combined with the Ag85B-ESAT-6 (H1) antigen were modelled using mouse in-vivo data. Compartment modelling and physiologically based pharmacokinetics (PBPK) were used to predict the administration site (muscle) and target site (lymph) temporal concentration profiles and factors governing these. Initial estimates using compartmental modelling established that quadriceps pharmacokinetics for the liposome demonstrated a long half-life (22.6 days) compared to the associated antigen (2.62 days). A mouse minimal-PBPK model was developed and successfully predicted quadriceps liposome and antigen pharmacokinetics. Predictions for the popliteal lymph node (PLN) aligned well at earlier time-points. A local sensitivity analysis highlighted that the predicted AUCmuscle was sensitive to the antigen degradation constant kdeg (resulting in a 3-log change) more so than the fraction escaping the quadriceps (fe) (resulting in a 10-fold change), and the predicted AUCPLN was highly sensitive to fe. A global sensitivity analysis of the antigen in the muscle demonstrated that model predictions were within the 50th percentile for predictions and showed acceptable fits. To further translate in-vitro data previously generated by our group, the mouse minimal-PBPK model was extrapolated to humans and predictions made for antigen pharmacokinetics in muscle and PLN. Global analysis demonstrated that both kdeg and fe had a minimal impact on the resulting simulations in the muscle but a greater impact in the PLN. In summary, this study has predicted the in-vivo fate of DDA:TDB:H1 in humans and demonstrated the roles that formulation degradation and fraction escaping the depot site can play upon the overall depot effect within the site of administration.
Collapse
|
21
|
Physiologically Based Pharmacokinetic Modeling of Therapeutic Proteins. J Pharm Sci 2017; 106:2270-2275. [DOI: 10.1016/j.xphs.2017.03.038] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 03/28/2017] [Accepted: 03/30/2017] [Indexed: 01/12/2023]
|
22
|
Li M, Qiang W, Hu L, Wang L, Cheng Z. A novel model for the pharmacokinetic studies of bevacizumab and etanercept in healthy volunteers and patients. Biochem Pharmacol 2017; 145:169-177. [PMID: 28822784 DOI: 10.1016/j.bcp.2017.08.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 08/11/2017] [Indexed: 01/19/2023]
Abstract
Therapeutic monoclonal antibodies (mAbs) have been successfully applied to treat various diseases and shown a promising prospect in medical treatment. MAbs have some unique characteristics when compared with small chemical drugs, and their pharmacokinetic (PK) properties are much more complex than those of small chemical drugs, whose eliminations are usually linear. In this study, a new model was established through taking into account the mechanisms of the elimination of mAbs. The proposed model was applied to the modeling and simulation of two kinds of mAbs, including bevacizumab and etanercept, in PK studies of healthy volunteers and eligible patients, and the classical linear compartment model was set as control. The goodness-of-fit of the fitting concentration-time curve of mAbs was calculated to verify the accuracy of both models during the modeling and simulation. The accuracy of the proposed model was better than that of classical linear compartment model in healthy volunteers and even much better in patients. The proposed model demonstrates a stronger ability in the modeling and simulation of mAbs, and may provide a new option for the PK studies of those reagents.
Collapse
Affiliation(s)
- Meizhen Li
- Research Institute of Drug Metabolism and Pharmacokinetics, School of Xiangya Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, China
| | - Wei Qiang
- Research Institute of Drug Metabolism and Pharmacokinetics, School of Xiangya Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, China
| | - Li Hu
- Department of Rheumatology, Shenzhen People's Hospital, Shenzhen, Guangzhou 518020, China
| | - Lei Wang
- Research Institute of Drug Metabolism and Pharmacokinetics, School of Xiangya Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, China; School of Life Sciences, Central South University, Changsha, Hunan 410013, China.
| | - Zeneng Cheng
- Research Institute of Drug Metabolism and Pharmacokinetics, School of Xiangya Pharmaceutical Sciences, Central South University, Changsha, Hunan 410013, China.
| |
Collapse
|
23
|
Ait-Oudhia S, Ovacik MA, Mager DE. Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity. MAbs 2017; 9:15-28. [PMID: 27661132 PMCID: PMC5240652 DOI: 10.1080/19420862.2016.1238995] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Revised: 09/02/2016] [Accepted: 09/14/2016] [Indexed: 10/21/2022] Open
Abstract
Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients.
Collapse
Affiliation(s)
- Sihem Ait-Oudhia
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL, USA
| | - Meric Ayse Ovacik
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| | - Donald E. Mager
- Department of Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA
| |
Collapse
|
24
|
Glassman PM, Balthasar JP. Physiologically-based modeling to predict the clinical behavior of monoclonal antibodies directed against lymphocyte antigens. MAbs 2016; 9:297-306. [PMID: 27892793 DOI: 10.1080/19420862.2016.1261775] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
Abstract
Many clinically approved and investigational monoclonal antibody (mAb)-based therapeutics are directed against proteins located in the systemic circulation, including cytokines, growth factors, lymphocyte proteins, and shed antigens. Interaction between mAb and target may lead to non-linear pharmacokinetics (PK), characterized by rapid, target-mediated elimination. Several groups have reported that determinants of target-mediated elimination could include mAb-target binding, target expression, and target turnover. Recently, we scaled a physiologically-based pharmacokinetic model for mAb disposition to man and used it to predict the non-linear PK of mAbs directed against tumor epithelial proteins. In this work, we extended the previously described model to account for the influence of lymphocyte proteins on mAb PK in man. To account for the dynamic behavior of lymphocytes in the circulation, lymphocyte cycling between blood and lymphoid organs was described using first-order transfer rate constants. Use of lymphocyte cycling and reported target turnover rates in the model allowed the accurate prediction of the pharmacokinetics and pharmacodynamics (PD) of 4 mAbs (TRX1, MTRX1011a, rituximab, daclizumab) directed against 3 lymphocyte targets (CD4, CD20, CD25). The results described here suggest that the proposed model structure may be useful in the a priori prediction of the PK/PD properties of mAbs directed against antigens in the circulation.
Collapse
Affiliation(s)
- Patrick M Glassman
- a Department of Pharmaceutical Sciences , School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York , Buffalo , NY , USA
| | - Joseph P Balthasar
- a Department of Pharmaceutical Sciences , School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York , Buffalo , NY , USA
| |
Collapse
|
25
|
Glassman PM, Balthasar JP. Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies. J Pharmacokinet Pharmacodyn 2016; 43:427-46. [DOI: 10.1007/s10928-016-9482-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Accepted: 06/28/2016] [Indexed: 12/18/2022]
|
26
|
Glassman PM, Balthasar JP. Application of a catenary PBPK model to predict the disposition of "catch and release" anti-PCSK9 antibodies. Int J Pharm 2016; 505:69-78. [PMID: 27041125 DOI: 10.1016/j.ijpharm.2016.03.066] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2016] [Revised: 03/14/2016] [Accepted: 03/31/2016] [Indexed: 10/22/2022]
Abstract
The development of 'catch and release', or pH-sensitive, monoclonal antibodies (mAb) has become of interest to groups seeking to reduce the influence of target-mediated elimination on pharmacokinetics and pharmacodynamics. In this work, a catenary physiologically-based pharmacokinetic (PBPK) model is described to predict the pharmacokinetic benefit conferred by engineering mAbs for 'catch and release' binding. Our previously published PBPK model was adapted for consideration of the production and elimination of proprotein convertase subtilisin/kexin type 9 (PCSK9) in mice, and the model was then applied to predict the pharmacokinetics of anti-PCSK9 mAb with pH-stable (J10) and pH-sensitive binding (J17). The model was able to generate reasonable predictions of both J10 and J17 plasma pharmacokinetics. For J10, mean (±standard deviation) predicted vs. observed areas under the plasma concentration curve (AUCinf) were: 217 (77.1) vs. 103nMday (1mg/kg), 1.14×10(3) (858) vs. 769nMday (3mg/kg), and 6.60×10(3) (5.58×10(3)) vs. 2.86×10(3)nMday (10mg/kg), and for J17 the values were: 838 (161) vs. 818nMday (1mg/kg), 2.30×10(3) (441) vs. 2.57×10(3)nMday (3mg/kg), and 8.42×10(3) (1.50×10(3)) vs. 9.17×10(3)nMday (10mg/kg). Further simulations with the model predicted that target turnover and the magnitude of change in the complex dissociation rate constant between pH 7.4 and pH 6.0 are key determinants of the improvements in pharmacokinetics associated with 'catch and release' mAbs. The model described here may be useful for prediction of the pharmacokinetics of 'catch and release' mAbs directed against other targets.
Collapse
Affiliation(s)
- Patrick M Glassman
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY 14214, United States
| | - Joseph P Balthasar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, The State University of New York, Buffalo, NY 14214, United States.
| |
Collapse
|
27
|
Perspectives on the history and scientific contributions of Gerhard Levy. J Pharmacokinet Pharmacodyn 2015; 42:429-46. [DOI: 10.1007/s10928-015-9442-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Accepted: 09/03/2015] [Indexed: 02/07/2023]
|