EMA perspective on the value of model-informed drug development for labeling recommendations regarding medicine use during pregnancy and breastfeeding

IF 3.1 3区 医学 Q2 PHARMACOLOGY & PHARMACY CPT: Pharmacometrics & Systems Pharmacology Pub Date : 2024-08-13 DOI:10.1002/psp4.13214
Efthymios Manolis, Flora Tshinanu Musuamba, Corinne S. de Vries, Pieter J. Colin, Martin B. Oleksiewicz
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While post-authorization studies are sometimes requested to collect safety data in pregnant and breastfeeding individuals, usually, routine pharmacovigilance (signal detection and post-authorization safety update reports) is relied upon for generating information in this population once the products are on the market.<span><sup>1, 2</sup></span> The overall consequence is possible under-prescription of medicines in these individuals and missing or ambiguous pregnancy-specific dosing recommendations in the SmPC (Summary of Product Characteristics).<span><sup>3, 4</sup></span> Hence, before, and long after real-world evidence is available, the use of medicinal products tends to be discouraged during pregnancy and breastfeeding.</p><p>This has been recognized as an unhelpful situation by regulators around the world,<span><sup>5</sup></span> leading within the European Medicines Agency (EMA) to the development and implementation of a strategy<span><sup>6</sup></span> to enhance the SmPC information on the benefits and risks of medicines in pregnancy and breastfeeding. Central to reaching this objective is to improve the related data collection (breadth and informativeness) during the product lifecycle. Important milestones include the agreement achieved by the International Conference of Harmonization (ICH) to draft a guideline for responsibly including, or permitting to remain, pregnant and breastfeeding individuals in clinical trials,<span><sup>7</sup></span> and the reopening of the Committee for Human Medicinal products (CHMP) guideline on labeling in pregnancy and breastfeeding.<span><sup>8</sup></span></p><p>We anticipate that regulatory developments such as those mentioned above, coupled with the significant development and innovation in nonclinical drug development methodologies and MIDD over the last decades, will shift the current labeling paradigms, to improve accessibility and safe use of medicines during pregnancy and breastfeeding. Several regulatory initiatives are underway, and these will be publicized on a dedicated webpage on the EMA public website in summer 2024.</p><p>MIDD comprises the strategic use of computational modeling and simulation approaches that integrate data, prior information, and knowledge, including drug, nonclinical, clinical, and disease characteristics, to generate evidence. When adequately implemented, modeling and simulation is considered a powerful tool for characterizing the efficacy and safety of drugs in subgroups underrepresented in clinical studies such as pregnant and breastfeeding participants, who also deserve timely access to safe and effective medicines.</p><p>From a physiology and pharmacology point of view, pregnant and breastfeeding individuals represent complex and dynamic systems.<span><sup>9</sup></span> MIDD approaches, including population pharmacokinetics/pharmacodynamics, physiologically-based pharmacokinetic modeling, and quantitative systems pharmacology, can integrate available knowledge on the drug pharmacology, in vitro or in vivo nonclinical data and clinical data to quantify these complex systems and enable predictions of drug exposure and clinical response during pregnancy and lactation. These models can be continuously improved based on new data collected in clinical studies that enroll pregnant and breastfeeding individuals. Depending on the remaining uncertainty in the models and related parameters, they can be used to either improve operating characteristics of clinical trials enrolling pregnant and lactating participants or support regulatory claims by complementing (non) clinical evidence for benefit/risk, labeling and need for potential additional risk mitigation measures in these special populations.</p><p>Among the different MIDD approaches, physiology-based pharmacokinetic (PBPK) modeling is expected by drug developers and regulators alike to have a prominent role in drug development in pregnant and breastfeeding individuals, given its ability to distinctly describe physiological and pharmacological processes.<span><sup>10, 11</sup></span> Already, different software providers are including pregnancy and lactation modules in their platforms.<span><sup>12-14</sup></span></p><p>PBPK can serve for early-in-development PK prediction by integrating drug parameters, systems knowledge (i.e., changes in absorption, distribution, metabolism, excretion (ADME) in pregnancy, lactating mother, neonate-infant, transplacental or/and mammary gland drug transfer), in vitro data (permeability, metabolism, active transporters, etc.) and in vivo data from nonclinical and clinical experiments. This prediction of drug exposure in special populations, coupled with an understanding of nonclinical toxicology exposure margins and exposure-response relationships (depending on the stage of drug development), can inform decision-making regarding the enrolment of pregnant and lactating participants in clinical studies and contribute to the weight-of-evidence approach advocated in the EMA guidelines. Even in cases where it is not possible to enroll pregnant and lactating individuals, this quantitative framework can facilitate decisions regarding labeling and risk management in these populations.</p><p>Despite these developments being welcomed at EMA, the current experience in EMA submissions with PBPK and broader MIDD in this context remains limited. In addition, the MIDD framework proposed above does not come without challenges. Focusing on PBPK, the model predictions in pregnancy and lactation are associated with high uncertainty because of poor understanding and quantification of system parameters and mechanisms involved in transplacental and mammary gland transfer, physiological changes in pregnancy, lactation, and the maturing child. Likewise, the in vitro methods to enable reliable PBPK predictions in these special populations are not well characterized.</p><p>The current uncertainties with PBPK in pregnancy and lactation impede their unconditional use and regulatory acceptance. 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Abstract

At the time of marketing authorization, pregnancy/breastfeeding labeling typically relies mainly on preclinical data. While post-authorization studies are sometimes requested to collect safety data in pregnant and breastfeeding individuals, usually, routine pharmacovigilance (signal detection and post-authorization safety update reports) is relied upon for generating information in this population once the products are on the market.1, 2 The overall consequence is possible under-prescription of medicines in these individuals and missing or ambiguous pregnancy-specific dosing recommendations in the SmPC (Summary of Product Characteristics).3, 4 Hence, before, and long after real-world evidence is available, the use of medicinal products tends to be discouraged during pregnancy and breastfeeding.

This has been recognized as an unhelpful situation by regulators around the world,5 leading within the European Medicines Agency (EMA) to the development and implementation of a strategy6 to enhance the SmPC information on the benefits and risks of medicines in pregnancy and breastfeeding. Central to reaching this objective is to improve the related data collection (breadth and informativeness) during the product lifecycle. Important milestones include the agreement achieved by the International Conference of Harmonization (ICH) to draft a guideline for responsibly including, or permitting to remain, pregnant and breastfeeding individuals in clinical trials,7 and the reopening of the Committee for Human Medicinal products (CHMP) guideline on labeling in pregnancy and breastfeeding.8

We anticipate that regulatory developments such as those mentioned above, coupled with the significant development and innovation in nonclinical drug development methodologies and MIDD over the last decades, will shift the current labeling paradigms, to improve accessibility and safe use of medicines during pregnancy and breastfeeding. Several regulatory initiatives are underway, and these will be publicized on a dedicated webpage on the EMA public website in summer 2024.

MIDD comprises the strategic use of computational modeling and simulation approaches that integrate data, prior information, and knowledge, including drug, nonclinical, clinical, and disease characteristics, to generate evidence. When adequately implemented, modeling and simulation is considered a powerful tool for characterizing the efficacy and safety of drugs in subgroups underrepresented in clinical studies such as pregnant and breastfeeding participants, who also deserve timely access to safe and effective medicines.

From a physiology and pharmacology point of view, pregnant and breastfeeding individuals represent complex and dynamic systems.9 MIDD approaches, including population pharmacokinetics/pharmacodynamics, physiologically-based pharmacokinetic modeling, and quantitative systems pharmacology, can integrate available knowledge on the drug pharmacology, in vitro or in vivo nonclinical data and clinical data to quantify these complex systems and enable predictions of drug exposure and clinical response during pregnancy and lactation. These models can be continuously improved based on new data collected in clinical studies that enroll pregnant and breastfeeding individuals. Depending on the remaining uncertainty in the models and related parameters, they can be used to either improve operating characteristics of clinical trials enrolling pregnant and lactating participants or support regulatory claims by complementing (non) clinical evidence for benefit/risk, labeling and need for potential additional risk mitigation measures in these special populations.

Among the different MIDD approaches, physiology-based pharmacokinetic (PBPK) modeling is expected by drug developers and regulators alike to have a prominent role in drug development in pregnant and breastfeeding individuals, given its ability to distinctly describe physiological and pharmacological processes.10, 11 Already, different software providers are including pregnancy and lactation modules in their platforms.12-14

PBPK can serve for early-in-development PK prediction by integrating drug parameters, systems knowledge (i.e., changes in absorption, distribution, metabolism, excretion (ADME) in pregnancy, lactating mother, neonate-infant, transplacental or/and mammary gland drug transfer), in vitro data (permeability, metabolism, active transporters, etc.) and in vivo data from nonclinical and clinical experiments. This prediction of drug exposure in special populations, coupled with an understanding of nonclinical toxicology exposure margins and exposure-response relationships (depending on the stage of drug development), can inform decision-making regarding the enrolment of pregnant and lactating participants in clinical studies and contribute to the weight-of-evidence approach advocated in the EMA guidelines. Even in cases where it is not possible to enroll pregnant and lactating individuals, this quantitative framework can facilitate decisions regarding labeling and risk management in these populations.

Despite these developments being welcomed at EMA, the current experience in EMA submissions with PBPK and broader MIDD in this context remains limited. In addition, the MIDD framework proposed above does not come without challenges. Focusing on PBPK, the model predictions in pregnancy and lactation are associated with high uncertainty because of poor understanding and quantification of system parameters and mechanisms involved in transplacental and mammary gland transfer, physiological changes in pregnancy, lactation, and the maturing child. Likewise, the in vitro methods to enable reliable PBPK predictions in these special populations are not well characterized.

The current uncertainties with PBPK in pregnancy and lactation impede their unconditional use and regulatory acceptance. Regulators would expect to be able to quantify the risk of making a wrong decision, for example, in this case agreeing on a dose that leads to under- or overexposure in pregnant women or breastfed infants/neonates with associated risks.

The science is still evolving, but promising efforts are underway to improve knowledge by systematic collection of physiology data, development, and characterization of new in vitro cell lines for passive and active transport, nonclinical and clinical data generation.15, 16

PBPK is emerging as a tool of choice in this context. However, there is limited regulatory experience with these methods in the specific lactation/pregnancy context of use. In this regard, regulatory activities are ongoing to facilitate use of MIDD approaches and improve pregnancy/lactation labeling for medicines. European regulators are willing to engage early in discussions with platform developers and consortia, via the qualification procedure,17 to agree on development and application of PBPK models in pregnancy and lactation.

No funding was received for this work.

The authors declared no competing interests for this work.

The views expressed in this article are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of the regulatory agencies or other organizations with which the authors are affiliated. The authors are employees of the European Medicines Agency or of a National Competent Authority.

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从 EMA 的角度看以模型为依据的药物开发对有关孕期和哺乳期用药的标签建议的价值。
在获得上市许可时,妊娠/哺乳标签通常主要依赖临床前数据。虽然有时会要求进行授权后研究,以收集妊娠和哺乳期患者的安全性数据,但通常情况下,产品一经上市,就会依靠常规药物警戒(信号检测和授权后安全性更新报告)来生成该人群的信息、2 总体后果是,这些人群的用药处方可能不足,SmPC(产品特征摘要)中针对妊娠期的用药建议缺失或含糊不清。世界各地的监管机构都认识到这种情况是不利的5 ,因此欧洲药品管理局(EMA)制定并实施了一项战略6 ,以加强关于孕期和哺乳期用药的益处和风险的 SmPC 信息。实现这一目标的核心是改进产品生命周期内的相关数据收集(广度和信息量)。重要的里程碑事件包括:国际协调会议 (ICH) 同意起草一份关于负责任地将怀孕和哺乳期妇女纳入或允许其继续参与临床试验的指导原则,7 以及人类医药产品委员会 (CHMP) 重新开放关于怀孕和哺乳期妇女用药标签的指导原则8。我们预计,如上所述的监管发展,加上过去几十年来非临床药物开发方法和 MIDD 的重大发展和创新,将改变目前的标签范式,从而提高孕期和哺乳期药物的可及性和安全使用。MIDD 包括计算建模和模拟方法的战略性使用,这些方法整合了数据、先前信息和知识,包括药物、非临床、临床和疾病特征,以生成证据。从生理学和药理学的角度来看,孕妇和哺乳期妇女是一个复杂的动态系统。MIDD 方法,包括群体药代动力学/药效动力学、基于生理学的药代动力学建模和定量系统药理学,可以整合现有的药物药理学知识、体外或体内非临床数据和临床数据,以量化这些复杂系统,并预测妊娠期和哺乳期的药物暴露和临床反应。这些模型可以根据纳入妊娠期和哺乳期个体的临床研究中收集的新数据不断改进。根据模型和相关参数中剩余的不确定性,这些模型可用于改善纳入妊娠期和哺乳期参与者的临床试验的操作特性,或通过补充(非)临床证据来支持这些特殊人群的获益/风险、标签和潜在额外风险缓解措施的需求,从而支持监管要求。在不同的 MIDD 方法中,基于生理学的药代动力学(PBPK)建模因其能够清晰描述生理和药理过程,被药物开发商和监管机构寄予厚望,将在妊娠期和哺乳期个体的药物开发中发挥重要作用、12-14PBPK 可通过整合药物参数、系统知识(即妊娠、哺乳母亲、新生儿-婴儿、经胎盘或/和乳腺药物转移过程中吸收、分布、代谢、排泄(ADME)的变化)、体外数据(渗透性、代谢、活性转运体等)以及来自非临床和临床实验的体内数据,进行药物开发早期的 PK 预测。这种对特殊人群药物暴露的预测,加上对非临床毒理学暴露限度和暴露-反应关系(取决于药物开发阶段)的了解,可以为临床研究中妊娠和哺乳期参与者的入组决策提供依据,并有助于实现 EMA 指南中倡导的证据权重法。
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CiteScore
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自引率
11.40%
发文量
146
审稿时长
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