CHE 542 Data Science in Pharmaceutical Development

The increased availability of digital data in the pharmaceutical industry has enabled the adoption of machine learning models to advance pharmaceutical development efforts. In addition, the emergence of open source languages with extensive libraries of powerful algorithms has transformed the way in which data science is adopted and practiced in pharmaceutical development organizations. This class provides the students with an introduction to pharmaceutical development aimed at contextualizing the incorporation of data science methodologies acquired in mathematical foundation courses (see requirements below). Industrial case studies in the public domain will be used as practice examples to demonstrate the incorporation of data science principles to industrially relevant applications.

Credits

3

Cross Listed Courses

MT 542

Prerequisite

Instructor Permission and MA 541 and (Grad Student (or Junior or Senior))

Distribution

Chemical Engineering Program Materials Science and Engineering Program

Typically Offered Periods

Spring Semester