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首页> 外文期刊>Current opinion in drug discovery & development >Informed toxicity assessment in drug discovery: systems-based toxicology.
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Informed toxicity assessment in drug discovery: systems-based toxicology.

机译:药物发现中的知情毒性评估:基于系统的毒理学。

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Technological advances in the biological, chemical and in silico sciences have transformed many scientific disciplines, including toxicology. A vast new palate of toxicity testing tools is now available to investigators, enabling the generation of enormous amounts of data using only small amounts of test sample and at relatively low cost. In addition to these tools, the pharmaceutical industry has an urgent need for toxicity testing earlier in the process, based on the recognition that safety issues are the single largest cause of drug candidate attrition from development portfolios and the marketplace. However, along with the opportunity provided by new testing tools comes the dilemma of deciding which tools to use and, equally as important, when and why to use them. It may well be unwise to apply a new toxicity test or screening system simply because one can, as both false positive and false negative outcomes can quickly negate the value of a toxicity test system and may even have a net negative impact on drug discovery productivity. This can be true even of test systems that are considered to be 'validated' in the traditional sense. How then is an investigator or drug discovery organization to decide which of the new tools to use, and when to use them? Proposed herein is a strategy for identifying high-value toxicity testing systems and strategies based on program knowledge and informed decision-making. The decision to apply a certain toxicity testing system in this strategy is informed by knowledge of the pharmacological target, the chemical features of molecules active at the pharmacological target, and existing public domain or institutional learning. This 'fit-for-purpose' approach limits non-targeted or 'uninformed' toxicity screening to only those few test systems with high specificity, strong outcome concordance and molecular relevance to frequently encountered toxicity risks (eg, genotoxicity). Additional toxicity testing and screening is then conducted to address specific known or potentialtoxicity risks, based on existing knowledge of the target pharmacology and secondary pharmacology or chemical attributes with known or suspect risk, and by active 'interrogation' of both the target and active chemical moieties during the drug discovery process. This model for toxicity testing decision-making is illustrated by two case studies from recent experience.
机译:生物,化学和计算机科学领域的技术进步改变了包括毒理学在内的许多科学学科。现在,研究人员可以使用大量新的毒性测试工具,从而能够仅使用少量测试样品并以相对较低的成本生成大量数据。除了这些工具以外,制药行业还迫切需要在过程的早期进行毒性测试,这是基于以下认识:安全问题是开发组合和市场上候选药物消耗的唯一最大原因。但是,随着新的测试工具提供的机会,随之而来的难题是决定使用哪些工具,以及同样重要的是何时以及为什么使用它们。简单地应用新的毒性测试或筛查系统可能是不明智的,因为一个人可以(因为假阳性和假阴性结果都可能很快使毒性测试系统的价值无效),甚至可能对药物开发效率产生净负面影响。即使在传统意义上被认为是“经过验证”的测试系统中也是如此。然后,研究者或药物发现组织如何决定使用哪些新工具以及何时使用它们?本文提出了一种基于程序知识和明智决策来识别高价值毒性测试系统和策略的策略。在药理学目标,在药理学目标上有活性的分子的化学特征以及现有的公共领域或机构知识的掌握,决定在该策略中应用某种毒性测试系统的决定。这种“适合目的”的方法将非靶向或“不知情”的毒性筛查仅限于少数具有高特异性,很强的结果一致性以及与经常遇到的毒性风险(例如遗传毒性)具有分子相关性的测试系统。然后,根据目标药理学和具有已知或可疑风险的二级药理学或化学属性的现有知识,以及通过主动“询问”靶标和活性化学部分,进行额外的毒性测试和筛选,以解决特定的已知或潜在毒性风险在药物发现过程中。最近的两个案例研究说明了这种毒性测试决策模型。

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