Van Neste Martje, Macente Julia, Nauwelaerts Nina, Ameye Lieveke, Bogaerts Annick, Smits Anne, Annaert Pieter, Allegaert Karel
Clinical pharmacology and Pharmacotherapy, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
L-C&Y, KU Leuven Child and Youth Institute, Leuven, Belgium.
Clin Pharmacokinet. 2025 Nov;64(11):1599-1619. doi: 10.1007/s40262-025-01583-4. Epub 2025 Nov 7.
Physiologically based pharmacokinetic (PBPK) modelling and simulation allows prediction of drug exposure in specific populations, such as infants during lactation. However, the influence of feeding type (e.g., human milk vs formula) on physiology has not yet been implemented in current PBPK platforms. We conducted a systematic search to compile datasets during the first year of life of infants who were exclusively breastfed for at least 4 months to incorporate in the virtual breastfed infant populations of PBPK platforms. Physiological data in exclusively breastfed infants were extracted from 223 included articles. This article reports the results on sex-specific height and weight data, collected from 35 and 43 articles, respectively, and assesses these data for girls and boys separately. The datasets were converted to pooled means ± standard deviation and subsequently to mathematical equations describing height and weight trajectories for exclusively breastfed infants. For the purpose of external verification, the novel function was compared with Flemish height and weight profiles stratified by maternal origin, revealing the most similarity with breastfed infants from European mothers. Furthermore, to assess the differences in current functions from PBPK software, data from the literature showed that current PBPK height and weight equations often overestimate relative to the novel equations for breastfed infants from 6 months onwards. These overestimations may result in differences in PBPK predictions. Systematic searches to assess maturational processes of other physiological parameters (e.g., body composition) in exclusively breastfed infants is likely warranted. These patterns should be incorporated in PBPK platforms to more adequately represent infant exposure to medicines, specifically for lactation-related medicine systemic exposure.
基于生理的药代动力学(PBPK)建模与模拟能够预测特定人群(如哺乳期婴儿)的药物暴露情况。然而,目前的PBPK平台尚未考虑喂养类型(如母乳与配方奶)对生理状况的影响。我们进行了系统检索,以汇总至少4个月纯母乳喂养婴儿出生后第一年的数据,纳入PBPK平台的虚拟母乳喂养婴儿群体。从223篇纳入文章中提取了纯母乳喂养婴儿的生理数据。本文报告了分别从35篇和43篇文章中收集的按性别分类的身高和体重数据结果,并分别对女孩和男孩的数据进行了评估。将数据集转换为合并均值±标准差,随后转换为描述纯母乳喂养婴儿身高和体重轨迹的数学方程。为了进行外部验证,将新函数与按母亲籍贯分层的佛兰芒身高和体重曲线进行了比较,结果显示与欧洲母亲的母乳喂养婴儿最为相似。此外,为了评估当前PBPK软件功能的差异,文献数据表明,从6个月起,当前PBPK的身高和体重方程相对于新方程,往往会高估母乳喂养婴儿的情况。这些高估可能导致PBPK预测结果出现差异。可能有必要进行系统检索,以评估纯母乳喂养婴儿其他生理参数(如身体成分)的成熟过程。应将这些模式纳入PBPK平台,以更充分地反映婴儿对药物的暴露情况,特别是与哺乳期相关的药物全身暴露情况。