Gerhart Jacqueline G, Carreño Fernando O, Edginton Andrea N, Sinha Jaydeep, Perrin Eliana M, Kumar Karan R, Rikhi Aruna, Hornik Christoph P, Harris Vincent, Ganguly Samit, Cohen-Wolkowiez Michael, Gonzalez Daniel
Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, 301 Pharmacy Lane, Campus Box #7569, Chapel Hill, NC, 27599-7569, USA.
School of Pharmacy, University of Waterloo, Waterloo, ON, Canada.
Clin Pharmacokinet. 2022 Feb;61(2):307-320. doi: 10.1007/s40262-021-01072-4. Epub 2021 Oct 7.
While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity.
To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models.
Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens.
Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.
在美国，五分之一的儿童肥胖，超过四分之三的儿童在童年时期至少服用过一种药物，但针对这一脆弱患者群体的给药指导有限。基于生理的药代动力学建模可以通过纳入已知的儿童肥胖相关生理变化，弥补对药代动力学（包括药物分布和清除）如何随肥胖而变化的理解差距。本研究的目的是开发一个肥胖儿童虚拟群体，以实现基于生理的药代动力学建模，然后将这个新的虚拟群体与先前开发的克林霉素和甲氧苄啶/磺胺甲恶唑模型结合使用，以更好地理解这些药物在肥胖儿童中的给药情况。
为了实现基于生理的药代动力学建模，利用全国调查、电子健康记录、临床试验数据以及从文献中提取的数据，开发了一个肥胖儿童虚拟群体。该虚拟群体考虑了与药代动力学相关的关键肥胖相关生理变化，包括体型增大、身体成分、器官大小和血流量、血浆蛋白浓度以及肾小球滤过率。然后使用该虚拟群体，通过先前开发的基于生理的药代动力学模型，预测肥胖儿童中克林霉素和甲氧苄啶/磺胺甲恶唑的药代动力学。
模型模拟对观察到的浓度预测良好，克林霉素、甲氧苄啶和磺胺甲恶唑的总体平均倍数误差分别为1.09、1.24和1.53。与非肥胖儿童相比，肥胖儿童的克林霉素和甲氧苄啶/磺胺甲恶唑体重标准化清除率和分布容积降低，在推荐的基于儿童体重的给药方案下绝对剂量更高。
模型模拟支持目前推荐的肥胖儿童中克林霉素和甲氧苄啶/磺胺甲恶唑基于体重的给药，因为尽管清除率和分布容积发生了这些变化，但它们仍达到了目标暴露水平。
