Allegaert Karel, van den Anker John
Department of Development and Regeneration, KU Leuven, Leuven, Belgium.
Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.
J Clin Pharmacol. 2021 Jun;61 Suppl 1(Suppl 1):S152-S160. doi: 10.1002/jcph.1827.
The efficacy and safety of a drug is dose or exposure related, and both are used to assess the benefit-risk balance of a given drug and ultimately to decide on the specific drug license, including its dose and indication(s). Unfortunately, both efficacy and safety are much more difficult to establish in neonates, resulting in very few drugs licensed for use in this vulnerable population. This review will focus on dose-related adverse events in neonates. Besides the regulatory classification on seriousness, adverse event assessment includes aspects related to signal detection, causality, and severity. Disentangling confounders from truly dose-related adverse drug events remains a major challenge, as illustrated for drug-induced renal impairment, drug-induced liver injury, and neurodevelopmental outcome. Causality assessment, using either routine tools (Naranjo algorithm, World Health Organization's Uppsala Monitoring Center causality tool) or a Naranjo algorithm tailored to neonates, still does not sufficiently and reliably document causality in neonates. Finally, very recently, a first neonatal severity-grading tool for neonates has been developed. Following the development of advanced pharmacokinetic approaches and techniques to predict and assess drug exposure, additional efforts are needed to truly and fully assess dose adverse drug events. To further operationalize the recently developed tools on causality and severity, reference databases on a palette of biomarkers and outcome variables and their covariates are an obvious next step. These databases should subsequently be integrated in modeling efforts to truly explore safety outcome, including aspects associated with or caused by drug dose or exposure.
药物的疗效和安全性与剂量或暴露相关,二者均用于评估特定药物的效益风险平衡,并最终决定具体的药品许可,包括其剂量和适应症。不幸的是,在新生儿中确定疗效和安全性要困难得多,导致获批用于这一脆弱人群的药物极少。本综述将聚焦于新生儿中与剂量相关的不良事件。除了根据严重程度进行监管分类外,不良事件评估还包括与信号检测、因果关系和严重程度相关的方面。将混杂因素与真正与剂量相关的药物不良事件区分开来仍然是一项重大挑战,药物性肾损伤、药物性肝损伤和神经发育结局就是例证。使用常规工具(纳伦霍算法、世界卫生组织乌普萨拉监测中心因果关系工具)或针对新生儿定制的纳伦霍算法进行因果关系评估,仍无法充分且可靠地证明新生儿中的因果关系。最后,就在最近,已开发出首个用于新生儿的严重程度分级工具。在先进的药代动力学方法和技术得以发展以预测和评估药物暴露之后,还需要做出更多努力来真正全面地评估与剂量相关的药物不良事件。为了进一步实施最近开发的关于因果关系和严重程度的工具,建立一系列生物标志物、结局变量及其协变量的参考数据库是下一步的明显举措。随后应将这些数据库整合到建模工作中,以真正探索安全性结局,包括与药物剂量或暴露相关或由其引起的方面。