{"title":"Structure Activity Relationships (SARs) Using a Structurally Diverse Drug Database: Validating Success of Predictor Tools.","authors":"Malcolm J D'Souza, Fumie Koyoshi, Lynn M Everett","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>ADME/Tox (absorption, distribution, metabolism, elimination and toxicity) technology is traditionally associated as a tool in the drug discovery process which is often used to predict the efficiency of drug adsorption, distribution, metabolic pathways, and elimination. For the past four years we have been involved in an effort to evaluate readily available Food and Drug Administration (FDA) consumer drug profiles and pharmacological data. Portable Document Format (PDF) data from drug profiles available on the FDA Drug Information website were used to create a searchable FDA Consumer Drug Database<sup>©</sup> using Bio-Rad's KnowItAll<sup>®</sup> platform which includes ADME/Tox <i>in silico</i> predictors. 14 pertinent pharmaceutical and pharmacological properties were collected for 75 structurally diverse consumer prescription drugs, and for several drugs, not all properties were completely populated. The major objective of this investigation was to validate the platforms prediction models for plasma protein binding (PPB) and bioavailability (BIO).</p>","PeriodicalId":89454,"journal":{"name":"Pharmaceutical reviews","volume":"7 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605434/pdf/nihms199390.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmaceutical reviews","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
ADME/Tox (absorption, distribution, metabolism, elimination and toxicity) technology is traditionally associated as a tool in the drug discovery process which is often used to predict the efficiency of drug adsorption, distribution, metabolic pathways, and elimination. For the past four years we have been involved in an effort to evaluate readily available Food and Drug Administration (FDA) consumer drug profiles and pharmacological data. Portable Document Format (PDF) data from drug profiles available on the FDA Drug Information website were used to create a searchable FDA Consumer Drug Database© using Bio-Rad's KnowItAll® platform which includes ADME/Tox in silico predictors. 14 pertinent pharmaceutical and pharmacological properties were collected for 75 structurally diverse consumer prescription drugs, and for several drugs, not all properties were completely populated. The major objective of this investigation was to validate the platforms prediction models for plasma protein binding (PPB) and bioavailability (BIO).
结构活性关系(SARs)使用结构多样化的药物数据库:验证预测工具的成功。
ADME/Tox(吸收、分布、代谢、消除和毒性)技术传统上是药物发现过程中的一种工具,通常用于预测药物吸附、分布、代谢途径和消除的效率。在过去的四年里,我们一直在努力评估现成的食品和药物管理局(FDA)消费者药物概况和药理学数据。使用Bio-Rad的KnowItAll®平台创建可搜索的FDA消费者药物数据库©,该平台包括ADME/Tox芯片预测器。收集了75种结构多样的消费者处方药的14种相关药物和药理学性质,并且对于一些药物,并非所有性质都完全填充。本研究的主要目的是验证该平台对血浆蛋白结合(PPB)和生物利用度(BIO)的预测模型。
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