Rapid development of novel drugs can be greatly aided by simulation. Currently, the FDA recommends the use of modeling and simulation for the development and regulatory evaluation of pharmaceuticals for example to predict clinical outcomes, inform clinical trial designs, support evidence of effectiveness, identify relevant patients to study, and predict safety. However, getting the most out of the use of simulations requires efficient use of the available simulation budget as well as validating that the in-silico results agree with in-vitro and in-vivo results. This webinar will discuss the role modern design of experiments and machine learning tools such as statistical calibration can play in validating and maximizing the knowledge gained from pharmaceutical simulations.
The webinar will include a live demonstration of SmartUQ and end with a Q&A session.
