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Dr David Cook - Articles and news items


Ensuring patient safety during clinical trials; translation to preclinical drug discovery

Contract Research, Issue 4 2012 / 3 September 2012 / David Cook & James Milligan, AstraZeneca

Ensuring patient safety during clinical trials is of paramount consideration with stringent monitoring built into trials (and beyond) and the design and interpretation of safety outcomes subject to a large amount of regulation. As a result, it is rare for clinical trials to produce extreme adverse drug reactions but it is also quite common for new medicines to fail in clinical testing due to unacceptable patient safety within a given indication. This is because once a new drug reaches clinical testing, its safety profile is already ‘locked in’, and clinical testing can only discover issues that already exist. The ideal way to ensure the safety of patients is to only progress new medicines into clinical testing which do not have unacceptable safety or tolerability issues. However, to reach this ideal means using learning in the clinic to influence design and development in the laboratory. In this short article, we discuss the practical challenges in doing this and in ‘translating’ patient safety observations such that they can impact on drug design and early development…

Figure 1 Overview of DILI-sim A. Schematic overview of the key biological processes represented in DILI-sim B. Overview of different modules within DILI-sim. Each module is itself a model that captures a specific area of relevant biology, pharmacology and metabolism. This modular approach to DILI-sim allows the overall model to be built in manageable, testable pieces C. Knowledge management aspects of DILI-sim. Under each of the models, the supporting evidence is explicitly captured and hence the model acts as a highly structured knowledge repository

Applying systems biology and computer simulations to predicting idiosyncratic DILI

Issue 4 2010, Toxicology / 19 August 2010 / David Cook, Associate Director, Global Safety Assessment, AstraZeneca

Idiosyncratic drug-induced liver injury (DILI) is a rare adverse drug reaction which accounts for a significant amount of patient suffering, including death. Currently, idiosyncratic DILI is unpredictable and as a result arises late in the drug development process or even post-marketing. The prediction of idiosyncratic DILI based on preclinical or early clinical data is a formidable challenge and this short review will discuss why and how new initiatives in systems biology and dynamic computational simulations can meet this challenge and predict the ‘unpredictable’.


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