Predictive modeling has the potential to aid in developing robust drug development and manufacturing platforms. However, realizing the full potential of the technology requires careful selection and application of in silico strategies and a deep understanding of how to interpret and derive the most valuable insights from the data. This report provides a framework for that understanding by outlining some of the processes that stand to gain the most from computational modeling and identifying the in silico capabilities that can be used to accelerate and de-risk each phase of development.

Some of the key modeling capabilities that will be discussed include:

·Predictive modeling for solubility and bioavailability enhancement
·Accelerated stability modeling for shelf life and packaging determination
·Materials science, compaction simulation, and process modeling
·ADME-PK modeling to predict the effect of API physicochemical properties and pharmacokinetics