1. Introduction Predictive Biosimulation and Virtual Patients in Pharmaceutical R&D
In the automotive, telecommunication, and aerospace industries, modeling and simulation are used to understand the behavior and outcomes of a new design well before production begins, thereby avoiding costly failures. In the pharmaceutical industry, failures are not typically identified until a compound reaches the clinic. This fact has created a productivity crisis due to the high failure rate of compounds late in the development process. Modeling and simulation are now being adopted by the pharmaceutical industry to understand the complexity of human physiology and predict human response to therapies. Additionally, virtual patients are being used to understand the impact of patient variability on these predictions. Several case studies are provided to illustrate the technology's application to pharmaceutical R and D and healthcare.
This paper outlines the integration of four weekly one-hour simulations into a pediatric clerkship. Student knowledge increased 71±16% pretest to 90±9% posttest (p<0.001); self-assessed skills performance improved, and students were more likely to accept presence of family in an emergency situation (p < 0.001) after participating in the study.