Kreir Mohamed, Putri Dea, Tekle Fetene, Pibiri Francesca, d'Ydewalle Constantin, Van Ammel Karel, Geys Helena, Teisman Ard, Gallacher David J, Lu Hua Rong
Global Toxicology and Safety Pharmacology, Preclinical Sciences and Translational Safety, Janssen Research and Development, Beerse, Belgium.
Statistics and Decision Sciences, Global Development, Janssen Research and Development, Beerse, Belgium.
Front Pharmacol. 2024 May 30;15:1308547. doi: 10.3389/fphar.2024.1308547. eCollection 2024.
We investigated drug-induced acute neuronal electrophysiological changes using Micro-Electrode arrays (MEA) to rat primary neuronal cell cultures. Data based on 6-key MEA parameters were analyzed for plate-to-plate vehicle variability, effects of positive and negative controls, as well as data from over 100 reference drugs, mostly known to have pharmacological phenotypic and clinical outcomes. A Least Absolute Shrinkage and Selection Operator (LASSO) regression, coupled with expert evaluation helped to identify the 6-key parameters from many other MEA parameters to evaluate the drug-induced acute neuronal changes. Calculating the statistical tolerance intervals for negative-positive control effects on those 4-key parameters helped us to develop a new weighted hazard scoring system on drug-induced potential central nervous system (CNS) adverse effects (AEs). The weighted total score, integrating the effects of a drug candidate on the identified six-pivotal parameters, simply determines if the testing compound/concentration induces potential CNS AEs. Hereto, it uses four different categories of hazard scores: non-neuroactive, neuroactive, hazard, or high hazard categories. This new scoring system was successfully applied to differentiate the new compounds with or without CNS AEs, and the results were correlated with the outcome of studies in mice for one internal program. Furthermore, the Random Forest classification method was used to obtain the probability that the effect of a compound is either inhibitory or excitatory. In conclusion, this new neuronal scoring system on the cell assay is actively applied in the early de-risking of drug development and reduces the use of animals and associated costs.
我们使用微电极阵列(MEA)对大鼠原代神经元细胞培养物进行研究,以探究药物诱导的急性神经元电生理变化。基于6个关键MEA参数的数据,分析了不同平板间的溶剂变异性、阳性和阴性对照的影响,以及来自100多种参考药物的数据,这些药物大多已知具有药理学表型和临床结果。最小绝对收缩和选择算子(LASSO)回归结合专家评估,有助于从许多其他MEA参数中识别出6个关键参数,以评估药物诱导的急性神经元变化。计算阴性和阳性对照对这4个关键参数影响的统计耐受区间,有助于我们开发一种新的加权风险评分系统,用于评估药物诱导的潜在中枢神经系统(CNS)不良反应(AE)。加权总分整合了候选药物对已识别的6个关键参数的影响,简单地确定测试化合物/浓度是否会诱导潜在的CNS AE。在此,它使用四种不同类别的风险评分:非神经活性、神经活性、风险或高风险类别。这种新的评分系统成功应用于区分有无CNS AE的新化合物,其结果与一个内部项目在小鼠中的研究结果相关。此外,随机森林分类方法用于获得化合物作用为抑制性或兴奋性的概率。总之,这种新细胞分析的神经元评分系统正积极应用于药物开发的早期风险降低,减少了动物的使用和相关成本。