概述
For toxicologists and safety pharmacologists, in vitro data offer an early warning of clinical hazards. How can we extract the most actionable intelligence from these data? The answer is three-fold: by making the interpretation of risk evidence-based, consistent across projects, and a routine part of the design-make-test-analyze cycle.
Join our to webinar to learn how scientists can detect and interpret risks from pharmacological profiling as a part of lead optimization. We’ll explain how off-target activity, direction of modulation, projected unbound exposure, and clinical precedents all inform the prediction of clinical risk at the point of discovery.
We’ll also share how to embed risk stratification into the DMTA cycle, so teams can prioritize compounds more intelligently, guide chemistry away from liabilities, and reserve in vivo studies for candidates with the highest chance of success.
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David Lowis, DPhil
Executive Director of Scientific Informatics, D36015 年以来,David 一直领导 D360 的设计和开发,范围从小分子发现一直扩展到生物制剂和临床前研究。他是 D360 部署的主题专家,负责检查涉及发现和临床前、临床和转化科学的科学数据工作流程。

Will Redfern, PhD
Vice President, Quantitative Systems Toxicology and SafetyWill 带领 QSTS 团队应用计算方法来评估药物和其他化学品的安全性。他是一位经验丰富的安全药理学家,曾在 Syntex、Quintiles 和 AstraZeneca 任职。他是安全性药理学协会的前任主席。
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