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Yuan Y, Li L, Earp J, Ma L, Bhattaram VA, Sharma V, Tong A, Wang Y, Liu J, Zhu H. Application of Model-Informed Drug Development in Dose Selection and Optimization for siRNA Therapies. J Clin Pharmacol 2024; 64:799-809. [PMID: 38426370 DOI: 10.1002/jcph.2418] [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: 11/29/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024]
Abstract
The application of model-informed drug development (MIDD) has revolutionized drug development and regulatory decision making, transforming the process into one that is more efficient, effective, and patient centered. A critical application of MIDD is to facilitate dose selection and optimization, which play a pivotal role in improving efficacy, safety, and tolerability profiles of a candidate drug. With the surge of interest in small interfering RNA (siRNA) drugs as a promising class of therapeutics, their applications in various disease areas have been extensively studied preclinically. However, dosing selection and optimization experience for siRNA in humans is limited. Unique challenges exist for the dose evaluation of siRNA due to the temporal discordance between pharmacokinetic and pharmacodynamic profiles, as well as limited available clinical experience and considerable interindividual variability. This review highlights the pivotal role of MIDD in facilitating dose selection and optimization for siRNA therapeutics. Based on past experiences with approved siRNA products, MIDD has demonstrated its ability to aid in dose selection for clinical trials and enabling optimal dosing for the general patient population. In addition, MIDD presents an opportunity for dose individualization based on patient characteristics, enhancing the precision and effectiveness of siRNA therapeutics. In conclusion, the integration of MIDD offers substantial advantages in navigating the complex challenges of dose selection and optimization in siRNA drug development, which in turn accelerates the development process, supports regulatory decision making, and ultimately improves the clinical outcomes of siRNA-based therapies, fostering advancements in precision medicine across a diverse range of diseases.
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Affiliation(s)
- Ye Yuan
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Liang Li
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Justin Earp
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Lian Ma
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Venkatesh Atul Bhattaram
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Vishnu Sharma
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Alexander Tong
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Yaning Wang
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Jiang Liu
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
| | - Hao Zhu
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA
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2
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Meesters K, Balbas-Martinez V, Allegaert K, Downes KJ, Michelet R. Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians. Paediatr Drugs 2024; 26:365-379. [PMID: 38755515 DOI: 10.1007/s40272-024-00633-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/25/2024] [Indexed: 05/18/2024]
Abstract
The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.
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Affiliation(s)
- Kevin Meesters
- Department of Pediatrics, University of British Columbia, 4480 Oak Street, Vancouver, BC, V6H 3V4, Canada.
- Vaccine Evaluation Center, BC Children's Hospital Research Institute, Vancouver, BC, Canada.
| | | | - Karel Allegaert
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium
- Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
- Department of Hospital Pharmacy, Erasmus MC, Rotterdam, The Netherlands
| | - Kevin J Downes
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Infectious Diseases, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Robin Michelet
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universität Berlin, Berlin, Germany
- qPharmetra LLC, Berlin, Germany
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3
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Gotta V, Bielicki JA, Paioni P, Csajka C, Bräm DS, Berger C, Giger E, Buettcher M, Posfay-Barbe KM, Van den Anker J, Pfister M. Pharmacometric in silico studies used to facilitate a national dose standardisation process in neonatology - application to amikacin. Swiss Med Wkly 2024; 154:3632. [PMID: 38635904 DOI: 10.57187/s.3632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024] Open
Abstract
BACKGROUND AND AIMS Pharmacometric in silico approaches are frequently applied to guide decisions concerning dosage regimes during the development of new medicines. We aimed to demonstrate how such pharmacometric modelling and simulation can provide a scientific rationale for optimising drug doses in the context of the Swiss national dose standardisation project in paediatrics using amikacin as a case study. METHODS Amikacin neonatal dosage is stratified by post-menstrual age (PMA) and post-natal age (PNA) in Switzerland and many other countries. Clinical concerns have been raised for the subpopulation of neonates with a post-menstrual age of 30-35 weeks and a post-natal age of 0-14 days ("subpopulation of clinical concern"), as potentially oto-/nephrotoxic trough concentrations (Ctrough >5 mg/l) were observed with a once-daily dose of 15 mg/kg. We applied a two-compartmental population pharmacokinetic model (amikacin clearance depending on birth weight and post-natal age) to real-world demographic data from 1563 neonates receiving anti-infectives (median birth weight 2.3 kg, median post-natal age six days) and performed pharmacometric dose-exposure simulations to identify extended dosing intervals that would ensure non-toxic Ctrough (Ctrough <5 mg/l) dosages in most neonates. RESULTS In the subpopulation of clinical concern, Ctrough <5 mg/l was predicted in 59% versus 79-99% of cases in all other subpopulations following the current recommendations. Elevated Ctrough values were associated with a post-natal age of less than seven days. Simulations showed that extending the dosing interval to ≥36 h in the subpopulation of clinical concern increased the frequency of a desirable Ctrough below 5 mg/l to >80%. CONCLUSION Pharmacometric in silico studies using high-quality real-world demographic data can provide a scientific rationale for national paediatric dose optimisation. This may increase clinical acceptance of fine-tuned standardised dosing recommendations and support their implementation, including in vulnerable subpopulations.
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Affiliation(s)
- Verena Gotta
- SwissPedDose/SwissPedNet collaboration expert team, Zürich/Basel/Lausanne, Switzerland
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
- Pediatric Clinical Pharmacy, University of Basel Children's Hospital, Basel Switzerland
| | - Julia Anna Bielicki
- Paediatric Research Centre and Paediatric Infectious Diseases and Vaccinology Division, University of Basel Children's Hospital, Basel, Switzerland
- Centre for Neonatal and Paediatric Infection, St George's University, London, United Kingdom
| | - Paolo Paioni
- SwissPedDose/SwissPedNet collaboration expert team, Zürich/Basel/Lausanne, Switzerland
- Division of Infectious Diseaeses, University Children's Hospital Zurich, Zurich, Switzerland
| | - Chantal Csajka
- SwissPedDose/SwissPedNet collaboration expert team, Zürich/Basel/Lausanne, Switzerland
- Centre for Research and Innovation, University Hospital and University of Lausanne, Lausanne, Switzerland
- School of Pharmaceutical Sciences, University of Geneva and University of Lausanne, Geneva/Lausanne, Switzerland
| | - Dominic Stefan Bräm
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
| | - Christoph Berger
- Division of Infectious Diseaeses, University Children's Hospital Zurich, Zurich, Switzerland
- SwissPedDose, Zurich, Switzerland
| | | | - Michael Buettcher
- SwissPedDose/SwissPedNet collaboration expert team, Zürich/Basel/Lausanne, Switzerland
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
- Paediatric Infectious Diseases, Lucerne Children's Hospital, Cantonal Hospital Lucerne, and Faculty of Health Sciences and Medicine, University Lucerne, Lucerne, Switzerland
| | - Klara M Posfay-Barbe
- General Pediatrics and Pediatric Infectious Diseases Unit, Department of Woman, Child and Adolescent, University Hospitals of Geneva and Medical School of Geneva, Geneva, Switzerland
| | - John Van den Anker
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
| | - Marc Pfister
- Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
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4
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Ahmed MA, Burnham J, Dwivedi G, AbuAsal B. Achieving big with small: quantitative clinical pharmacology tools for drug development in pediatric rare diseases. J Pharmacokinet Pharmacodyn 2023; 50:429-444. [PMID: 37140724 DOI: 10.1007/s10928-023-09863-x] [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: 03/04/2023] [Accepted: 04/26/2023] [Indexed: 05/05/2023]
Abstract
Pediatric populations represent a major fraction of rare diseases and compound the intrinsic challenges of pediatric drug development and drug development for rare diseases. The intertwined complexities of pediatric and rare disease populations impose unique challenges to clinical pharmacologists and require integration of novel clinical pharmacology and quantitative tools to overcome multiple hurdles during the discovery and development of new therapies. Drug development strategies for pediatric rare diseases continue to evolve to meet the inherent challenges and produce new medicines. Advances in quantitative clinical pharmacology research have been a key component in advancing pediatric rare disease research to accelerate drug development and inform regulatory decisions. This article will discuss the evolution of the regulatory landscape in pediatric rare diseases, the challenges encountered during the design of rare disease drug development programs and will highlight the use of innovative tools and potential solutions for future development programs.
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Affiliation(s)
- Mariam A Ahmed
- Takeda Development Center Americas Inc, 125 Binney St, Cambridge, MA, 02142-1123, USA.
| | | | - Gaurav Dwivedi
- Takeda Development Center Americas Inc, 125 Binney St, Cambridge, MA, 02142-1123, USA
| | - Bilal AbuAsal
- US Food and Drug Administration, 10903, New Hampshire Ave, Silver Spring, MD, 20993, USA
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5
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Ye J, Bi Y, Ting N. How to select the initial dose for a pediatric study? J Biopharm Stat 2023; 33:844-858. [PMID: 36476267 DOI: 10.1080/10543406.2022.2149770] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022]
Abstract
In typical clinical development programs, a new drug is first developed for the adult use. Drugs are often approved for adult use or in the process of obtaining approval in adults in the target indication before pediatric development is initiated. In designing the first pediatric clinical trial, one of the challenges is to select the initial dose to be tested. The ICH E11 R1 guidance advises that chronologic age alone may not always be the most appropriate categorical determinant to define developmental subgroups in pediatric studies. In this manuscript, the approaches to utilize available data in adults related to those factors beyond age to inform the starting dose selection in pediatric drug development are discussed. Practical considerations and approaches are provided for informing pediatric starting dose. Additional considerations to use pre-clinical information are provided in the case when adult information is limited or not available.
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Affiliation(s)
- Jingjing Ye
- Global Statistics and Data Science (GSDS), Fulton, MD, USA
| | - Youwei Bi
- Division of Pharmacometrics, Office of Translational Sciences (OTS), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, MD, USA
| | - Naitee Ting
- Biostatistics and Data Science, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA
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6
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Zhao J, Zhu X, Tan S, Chen C, Kaddoumi A, Guo XL, Lin YW, Cheung SYA. Editorial: Model-informed drug development and evidence-based translational pharmacology. Front Pharmacol 2022; 13:1086551. [PMID: 36578539 PMCID: PMC9791580 DOI: 10.3389/fphar.2022.1086551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Affiliation(s)
- Jinxin Zhao
- Biomedicine Discovery Institute, Infection and Immunity Program and Department of Microbiology, Monash University, Melbourne, VIC, Australia
| | - Xiao Zhu
- Department of Clinical Pharmacy and Pharmacy Administration, School of Pharmacy, Fudan University, Shanghai, China
| | - Songwen Tan
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
| | - Chuanpin Chen
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
| | - Amal Kaddoumi
- Department of Drug Discovery and Development, Harrison College of Pharmacy, Auburn University, Auburn, AL, United States,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
| | - Xiu-Li Guo
- Department of Pharmacology, School of Pharmaceutical Science, Shandong University, Jinan, China,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
| | - Yu-Wei Lin
- Biomedicine Discovery Institute, Infection and Immunity Program and Department of Microbiology, Monash University, Melbourne, VIC, Australia,Malaya Translational and Clinical Pharmacometrics Group, Faculty of Pharmacy, University of Malaya, Kuala Lumpur, Malaysia,Department of Clinical Pharmacy and Pharmacy Practice, Faculty of Pharmacy, University of Malaya, Kuala Lumpur, Malaysia,Integrated Drug Development, Certara, NJ, United States,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
| | - S. Y. Amy Cheung
- Integrated Drug Development, Certara, NJ, United States,*Correspondence: Songwen Tan, ; Chuanpin Chen, ; Amal Kaddoumi, ; Xiu-Li Guo, ; Yu-Wei Lin, ; S. Y. Amy Cheung,
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7
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Li R, Ma L, Li F, Li L, Bi Y, Yuan Y, Li Y, Xu Y, Zhang X, Liu J, Bhattaram VA, Wang J, Schuck R, Pacanowski M, Zhu H. Model‐Informed Approach Supporting Drug Development and Regulatory Evaluation for Rare Diseases. J Clin Pharmacol 2022; 62 Suppl 2:S27-S37. [DOI: 10.1002/jcph.2143] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 08/15/2022] [Indexed: 12/04/2022]
Affiliation(s)
- Ruo‐Jing Li
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Lian Ma
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Fang Li
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Liang Li
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Youwei Bi
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Ye Yuan
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Yangbing Li
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Yuan Xu
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Xinyuan Zhang
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Jiang Liu
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Venkatesh Atul Bhattaram
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Jie Wang
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Robert Schuck
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Michael Pacanowski
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
| | - Hao Zhu
- Office of Clinical Pharmacology Center for Drug Evaluation and Research Food and Drug Administration Silver Spring Maryland USA
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8
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Madabushi R, Seo P, Zhao L, Tegenge M, Zhu H. Review: Role of Model-Informed Drug Development Approaches in the Lifecycle of Drug Development and Regulatory Decision-Making. Pharm Res 2022; 39:1669-1680. [PMID: 35552984 PMCID: PMC9097888 DOI: 10.1007/s11095-022-03288-w] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/04/2022] [Indexed: 11/28/2022]
Abstract
Model-informed drug development (MIDD) is a powerful approach to support drug development and regulatory review. There is a rich history of MIDD applications at the U.S. Food and Drug Administration (FDA). MIDD applications span across the life cycle of the development of new drugs, generics, and biologic products. In new drug development, MIDD approaches are often applied to inform clinical trial design including dose selection/optimization, aid in the evaluation of critical regulatory review questions such as evidence of effectiveness, and development of policy. In the biopharmaceutics space, we see a trend for increasing role of computational modeling to inform formulation development and help strategize future in vivo studies or lifecycle plans in the post approval setting. As more information and knowledge becomes available pre-approval, quantitative mathematical models are becoming indispensable in supporting generic drug development and approval including complex generic drug products and are expected to help reduce overall time and cost. While the application of MIDD to inform the development of cell and gene therapy products is at an early stage, the potential for future application of MIDD include understanding and quantitative evaluation of information related to biological activity/pharmacodynamics, cell expansion/persistence, transgene expression, immune response, safety, and efficacy. With exciting innovations on the horizon, broader adoption of MIDD is poised to revolutionize drug development for greater patient and societal benefit.
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Affiliation(s)
- Rajanikanth Madabushi
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
| | - Paul Seo
- Division of Biopharmaceutics, Office of New Drug Products, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Liang Zhao
- Division of Quantitative Methods and Modeling, Office of Research and Standards, Office of Generic Drugs, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Million Tegenge
- Division of Clinical Evaluation and Pharmacology/Toxicology, Office of Tissue and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Hao Zhu
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA.
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9
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Allegaert K, Abbasi MY, Annaert P, Olafuyi O. Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates. Expert Opin Drug Metab Toxicol 2022; 18:301-312. [PMID: 35796504 DOI: 10.1080/17425255.2022.2099836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates. AREAS COVERED Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered. EXPERT OPINION Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.
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Affiliation(s)
- Karel Allegaert
- Department of Pharmaceutical and Pharmacological Sciences.,Department of Development and Regeneration, and.,Leuven Child and Youth Institute, KU Leuven, Leuven Belgium.,Department of Clinical Pharmacy, Erasmus MC, Rotterdam, the Netherlands
| | - Mohammad Yaseen Abbasi
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Pieter Annaert
- Department of Pharmaceutical and Pharmacological Sciences
| | - Olusola Olafuyi
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
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10
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Johnson TN, Small BG, Rowland Yeo K. Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations. CPT Pharmacometrics Syst Pharmacol 2022; 11:373-383. [PMID: 35174656 PMCID: PMC8923731 DOI: 10.1002/psp4.12764] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 01/10/2022] [Accepted: 01/13/2022] [Indexed: 12/16/2022] Open
Abstract
There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics. The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P‐PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P‐PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P‐PBPK modeling increased 33‐fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P‐PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug–drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P‐PBPK models.
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Affiliation(s)
| | - Ben G Small
- Certara UK Limited (Simcyp Division), Sheffield, UK
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11
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Anderson N, Clarke S, von Ungern-Sternberg BS. Aerosolized drug delivery in awake and anesthetized children to treat bronchospasm. Paediatr Anaesth 2022; 32:156-166. [PMID: 34862993 DOI: 10.1111/pan.14354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 11/29/2021] [Accepted: 12/01/2021] [Indexed: 11/25/2022]
Abstract
Bronchospasm is a common respiratory adverse event in pediatric anesthesia. First-line treatment commonly includes inhaled salbutamol. This review focuses on the current best practice to deliver aerosolized medications to awake as well as anesthetized pediatric patients and discusses the advantages and disadvantages of various administration techniques. Additionally, we detail the differences between various airway devices used in anesthesia. We highlight the unmet need for innovation of orally inhaled drug products to deliver aerosolized medications during pediatric respiratory critical events such as bronchospasm. It is therefore important that clinicians remain up to date with the best clinical practice for aerosolized drug delivery in order to prevent and efficiently treat pediatric patients experiencing life-threatening respiratory emergencies.
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Affiliation(s)
- Natalie Anderson
- Perioperative Medicine, Telethon Kids Institute, Nedlands, WA, Australia.,School of Population Health, Curtin University, Bentley, WA, Australia
| | - Sarah Clarke
- Emergency Department, Perth Children's Hospital, Perth, WA, Australia
| | - Britta S von Ungern-Sternberg
- Perioperative Medicine, Telethon Kids Institute, Nedlands, WA, Australia.,Department of Anaesthesia and Pain Management, Perth Children's Hospital, Perth, WA, Australia.,Division of Emergency Medicine, Anaesthesia and Pain Medicine, Medical School, The University of Western Australia, Perth, WA, Australia
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12
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Wang K, Jiang K, Wei X, Li Y, Wang T, Song Y. Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development. AAPS PharmSciTech 2021; 22:208. [PMID: 34312742 PMCID: PMC8312709 DOI: 10.1208/s12249-021-02076-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 06/16/2021] [Indexed: 12/30/2022] Open
Abstract
Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.
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Chan PL, McFadyen L, Quaye A, Leister‐Tebbe H, Hendrick VM, Hammond J, Raber S. The use of extrapolation based on modeling and simulation to support high-dose regimens of ceftaroline fosamil in pediatric patients with complicated skin and soft-tissue infections. CPT Pharmacometrics Syst Pharmacol 2021; 10:551-563. [PMID: 33687148 PMCID: PMC8213416 DOI: 10.1002/psp4.12608] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/29/2021] [Accepted: 01/31/2021] [Indexed: 12/14/2022] Open
Abstract
A model-informed drug development approach was used to select ceftaroline fosamil high-dose regimens for pediatric patients with complicated skin and soft-tissue infections caused by Staphylococcus aureus with a ceftaroline minimum inhibitory concentration (MIC) of 2 or 4 mg/L. Steady-state ceftaroline concentrations were simulated using a population pharmacokinetics (PK) model for ceftaroline fosamil and ceftaroline including data from 304 pediatric subjects and 944 adults. Probability of target attainment (PTA) for various simulated pediatric high-dose regimens and renal function categories were calculated based on patients achieving 35% fT>MIC (S. aureus PK/pharmacodynamic target for 2-log10 bacterial killing). For extrapolation of efficacy, simulated exposures and PTA were compared to adults with normal renal function receiving high-dose ceftaroline fosamil (600 mg 2-h infusions every 8 h). For safety, predicted ceftaroline exposures were compared with observed pediatric and adult data. Predicted ceftaroline exposures for the approved pediatric high-dose regimens (12, 10, or 8 mg/kg by 2-h infusions every 8 h for patients aged >2 to <18 years with normal/mild, moderate, or severe renal impairment, respectively; 10 mg/kg by 2-h infusions every 8 h for patients aged ≥2 months to <2 years with normal renal function/mild impairment) were well matched to adults with normal renal function. Median predicted maximum concentration at steady state (Cmax,ss ) and area under the plasma concentration-time curve over 24 h at steady state pediatric to adult ratios were 0.907-1.33 and 0.940-1.41, respectively. PTAs (>99% and ≥81% for MICs of 2 and 4 mg/L, respectively) matched or exceeded the adult predictions. Simulated Cmax,ss values were below the maximum observed data in other indications, including a high-dose pediatric pneumonia trial, which reported no adverse events related to high exposure.
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Rashid M, Sarfraz M, Arfat M, Hussain A, Abbas N, Hussain K, Bukhari NI. Prediction of pharmacokinetic parameters and dose of pregabalin gastroretentive formulation in healthy adults, healthy pediatrics and renal-impaired geriatrics. J Drug Deliv Sci Technol 2021. [DOI: 10.1016/j.jddst.2021.102548] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Chan PLS, Marshall SF, McFadyen L, Liu J. Pregabalin Population Pharmacokinetic and Exposure-Response Analyses for Focal Onset Seizures in Children (4-16 years) and Adults, to Support Dose Recommendations in Children. Clin Pharmacol Ther 2020; 110:132-140. [PMID: 33280106 PMCID: PMC8359225 DOI: 10.1002/cpt.2132] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 11/21/2020] [Indexed: 02/05/2023]
Abstract
Pregabalin is approved in multiple countries as adjunctive therapy for adult patients with focal onset seizures (FOS; previously termed partial onset seizures). This study used population pharmacokinetic (PK) and exposure–response (E‐R) analyses from pooled pregabalin concentration and efficacy data to compare pregabalin exposure and E‐R relationships in pediatric and adult patients with FOS, to support pediatric dosage recommendations. A one‐compartment disposition model was used, with first‐order absorption and body surface area‐normalized creatinine clearance on clearance. Individual pregabalin average steady‐state concentrations were predicted and used in an E‐R analysis of efficacy. The E‐R relationship of pregabalin was similar in pediatric (4–16 years) and adult patients with FOS after accounting for differences in baseline natural log‐transformed 28‐day seizure rate and placebo effect. Population PK simulations showed that children aged 4–16 years and weighing ≥ 30 kg required pregabalin 2.5–10 mg/kg/day to achieve similar pregabalin exposure at steady‐state to adult patients receiving the approved doses of 150–600 mg/day. For children 4–16 years weighing < 30 kg, a higher pregabalin dose of 3.5–14 mg/kg/day was required to achieve equivalent exposure at steady‐state. The results support the dosage guidance provided in the pregabalin prescribing label, whereby pediatric patients (4–16 years) weighing < 30 kg should receive a 40% higher pregabalin dose (per kg of body weight) than patients weighing ≥ 30 kg to achieve similar exposure. Our combined modeling approach may provide guidance for future extrapolation assessment from adult to pediatric patients.
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Affiliation(s)
| | | | | | - Jing Liu
- Pfizer, Groton, Connecticut, USA
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Powell JR, Cook J, Wang Y, Peck R, Weiner D. Drug Dosing Recommendations for All Patients: A Roadmap for Change. Clin Pharmacol Ther 2020; 109:65-72. [PMID: 32453862 PMCID: PMC7818440 DOI: 10.1002/cpt.1923] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 05/15/2020] [Indexed: 12/16/2022]
Abstract
Most drug labels do not contain dosing recommendations for a significant portion of real‐world patients for whom the drug is prescribed. Current label recommendations predominately reflect the population studied in pivotal trials that typically exclude patients who are very young or old, emaciated or morbidly obese, pregnant, or have multiple characteristics likely to influence dosing. As a result, physicians may need to guess the correct dose and regimen for these patients. It is now feasible to provide dose and regimen recommendations for these patients by integrating available scientific knowledge and by utilizing or modifying current regulatory agency‐industry practices. The purpose of this commentary is to explore several factors that should be considered in creating a process that will provide more effective, safe, and timely drug dosing recommendations for most, if not all, patients. These factors include the availability of real‐world data, development of predictive models, experience with the US Food and Drug Administration (FDA)’s pediatric exclusivity program, development of clinical decision software, funding mechanisms like the Prescription Drug Users Fee Act (PDUFA), and harmonization of global regulatory policies. From an examination of these factors, we recommend a relatively simple, efficient expansion of current practices designed to predict, confirm, and continuously improve drug dosing for more patients. We believe implementing these recommendations will benefit patients, payers, industry, and regulatory agencies.
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Affiliation(s)
- J Robert Powell
- Clinical Pharmacology Consultant, Chapel Hill, North Carolina, USA
| | - Jack Cook
- Clinical Pharmacology, Pfizer Inc, Groton, Connecticut, USA
| | - Yaning Wang
- Office of Clinical Pharmacology, Office of Translational Sciences, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Richard Peck
- Roche Innovation Center Basel, Pharma Research & Early Development (pRED), Basel, Switzerland
| | - Dan Weiner
- Pharmacometrics Consultant, Chapel Hill, North Carolina, USA
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Adiwidjaja J, Boddy AV, McLachlan AJ. Implementation of a Physiologically Based Pharmacokinetic Modeling Approach to Guide Optimal Dosing Regimens for Imatinib and Potential Drug Interactions in Paediatrics. Front Pharmacol 2020; 10:1672. [PMID: 32082165 PMCID: PMC7002565 DOI: 10.3389/fphar.2019.01672] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Accepted: 12/23/2019] [Indexed: 12/18/2022] Open
Abstract
Long-term use of imatinib is effective and well-tolerated in children with chronic myeloid leukaemia (CML) yet defining an optimal dosing regimen for imatinib in younger patients is a challenge. The potential interactions between imatinib and coadministered drugs in this "special" population also remains largely unexplored. This study implements a physiologically based pharmacokinetic (PBPK) modeling approach to investigate optimal dosing regimens and potential drug interactions with imatinib in the paediatric population. A PBPK model for imatinib was developed in the Simcyp Simulator (version 17) utilizing in silico, in vitro drug metabolism, and in vivo pharmacokinetic data and verified using an independent set of published clinical pharmacokinetic data. The model was then extrapolated to children and adolescents (aged 2-18 years) by incorporating developmental changes in organ size and maturation of drug-metabolising enzymes and plasma protein responsible for imatinib disposition. The PBPK model described imatinib pharmacokinetics in adult and paediatric populations and predicted drug interaction with carbamazepine, a cytochrome P450 (CYP)3A4 and 2C8 inducer, with a good accuracy (evaluated by visual inspections of the simulation results and predicted pharmacokinetic parameters that were within 1.25-fold of the clinically observed values). The PBPK simulation suggests that the optimal dosing regimen range for imatinib is 230-340 mg/m2/d in paediatrics, which is supported by the recommended initial dose for treatment of childhood CML. The simulations also highlighted that children and adults being treated with imatinib have similar vulnerability to CYP modulations. A PBPK model for imatinib was successfully developed with an excellent performance in predicting imatinib pharmacokinetics across age groups. This PBPK model is beneficial to guide optimal dosing regimens for imatinib and predict drug interactions with CYP modulators in the paediatric population.
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Affiliation(s)
- Jeffry Adiwidjaja
- Sydney Pharmacy School, The University of Sydney, Sydney, NSW, Australia
| | - Alan V. Boddy
- School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, Australia
- University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, Australia
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