In vivo models have been crucial for developing our understanding of key processes associated with human disease and developing novel therapeutics. These in vivo studies are becoming increasingly complex, requiring long-term efficacy data and additional supportive datasets such as pharmacokinetic profiles and analysis of multiple biomarkers of pharmacodynamic response and efficacy. Moreover, a new agent will be investigated in many different models and often in combination with other drugs. Despite advances across the industry integrating and analysing complex datasets, management of in vivo data remains an ongoing challenge across the industry. Here, we describe a project that has successfully delivered a working solution to integrate pharmacokinetic, biomarker and efficacy data, independent of therapy area.

体内模型对于发展我们对与人类疾病相关的关键过程的理解以及开发新的疗法至关重要。这些体内研究变得越来越复杂，需要长期的功效数据和其他支持性数据集，例如药代动力学概况以及药代动力学反应和功效的多个生物标志物的分析。而且，将以许多不同的模型来研究一种新的药物，并且通常将其与其他药物联合使用。尽管集成和分析复杂数据集在整个行业取得了进步，但体内管理数据仍然是整个行业的持续挑战。在这里，我们描述了一个项目，该项目已成功交付了一个工作解决方案，以整合药代动力学，生物标志物和功效数据，而与治疗领域无关。