{"title":"A property-response perspective on modern toxicity assessment and drug toxicity index (DTI).","authors":"Vaibhav A Dixit, Pragati Singh","doi":"10.1007/s40203-021-00096-9","DOIUrl":null,"url":null,"abstract":"<p><p>Toxicity related failures in drug discovery and clinical development have motivated scientists and regulators to develop a wide range of in-vitro, in-silico tools coupled with data science methods. Older drug discovery rules are being constantly modified to churn out any hidden predictive value. Nonetheless, the dose-response concepts remain central to all these methods. Over the last 2 decades medicinal chemists, and pharmacologists have observed that different physicochemical, and pharmacological properties capture trends in toxic responses. We propose that these observations should be viewed in a comprehensive property-response framework where dose is only a factor that modifies the inherent toxicity potential. We then introduce the recently proposed \"Drug Toxicity Index (DTI)\" and briefly summarize its applications. A webserver is available to calculate DTI values (https://all-tool-kit.github.io/Web-Tool.html).</p>","PeriodicalId":13380,"journal":{"name":"In Silico Pharmacology","volume":" ","pages":"37"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8124026/pdf/40203_2021_Article_96.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Pharmacology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40203-021-00096-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Toxicity related failures in drug discovery and clinical development have motivated scientists and regulators to develop a wide range of in-vitro, in-silico tools coupled with data science methods. Older drug discovery rules are being constantly modified to churn out any hidden predictive value. Nonetheless, the dose-response concepts remain central to all these methods. Over the last 2 decades medicinal chemists, and pharmacologists have observed that different physicochemical, and pharmacological properties capture trends in toxic responses. We propose that these observations should be viewed in a comprehensive property-response framework where dose is only a factor that modifies the inherent toxicity potential. We then introduce the recently proposed "Drug Toxicity Index (DTI)" and briefly summarize its applications. A webserver is available to calculate DTI values (https://all-tool-kit.github.io/Web-Tool.html).