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Setting course for a translational pharmacology and a predictive toxicology based on the numerical probability of clinical relevance
Environmental Toxicology and Pharmacology ( IF 4.2 ) Pub Date : 2022-09-06 , DOI: 10.1016/j.etap.2022.103968
Jose D Suarez-Torres 1 , Carlos E Ciangherotti 2 , Camilo A Orozco 3
Affiliation  

For a significant share of the chemicals, current bioassays mispredicted the outcomes in the reference methods they simulate. For any drug or chemical, and depending on the regulatory or corporate situation, three different approaches calculate the numerical probability by which agreement (or discrepancy) can be statistically expected between (1) the result of a predictive bioassay, and (2) the outcome on its reference method. If such concordance is expected with enough confidence based on a sufficient percentage probability, then specific results from that bioassay can be considered as correctly predictive. The statistical approaches analyzed in this article assist in valuable tasks, including (1) a better translation of the clinical relevance (or insignificance) of specific preclinical findings; (2) waiving unnecessary animal testing (or any other unpredictive testing; e.g., a given in vitro bioassay), and (3) in advancing only the most promising candidates in the pharmaceutical, pesticide, or chemical development process.



中文翻译:

根据临床相关性的数值概率设置转化药理学和预测毒理学课程

对于很大一部分化学品,当前的生物测定错误地预测了它们模拟的参考方法的结果。对于任何药物或化学品,根据监管或公司情况,三种不同的方法可以计算在(1)预测性生物测定的结果和(2)结果之间可以统计预期一致(或差异)的数值概率关于其参考方法。如果基于足够的百分比概率以足够的置信度预期这种一致性,那么来自该生物测定的特定结果可以被认为是正确预测的。本文分析的统计方法有助于完成有价值的任务,包括(1)更好地翻译特定临床前发现的临床相关性(或无关紧要性);(2)放弃不必要的动物试验(或任何其他不可预测的试验;例如,给定的体外生物测定),以及(3)仅推进药物、农药或化学开发过程中最有希望的候选者。

更新日期:2022-09-06
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