Abstract
The development of new pharmaceuticals for the treatment of human disease is increasingly challenging. New methods such as quantitative systems pharmacology (QSP) and quantitative systems toxicology (QST) can help address drug development challenges. Despite its promise, QSP/QST is not without its challenges. An investment is required to collect the necessary input data and ensure key components are represented qualitatively and quantitatively well. One strategy for addressing these concerns is conducting model development within consortia. Consortia offer companies the ability to share data, seek feedback from health authorities collectively, guide model development, learn from others, and share platform development costs. This article highlights lessons learned from past experiences associated with The DILI-sim Initiative – a collaborative effort focused on developing DILIsym software for predicting drug-induced liver injury (DILI).
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