This webinar covers the rise of deep learning in drug development. Biology and medicine now generate immense datasets that are impossible or difficult to incorporate into the drug development process through human evaluation or traditional statistical methods alone. Recent progress indicates that applications of deep learning could transform drug development by speeding up the process of human investigations.
At the end of this webinar attendees should have a better understanding of:
- The relationships among artificial intelligence, machine learning, and deep learning
- Challenges and opportunities
- Select applications of deep learning in drug development
- The properties of deep learning algorithms that have enabled major performance improvements in several computational tasks
Meet the Speaker
Jason R. Pirone, Ph.D.
Principal Scientist, Pharmacometrics
Dr. Pirone has nearly two decades of experience building mathematical models of physiological and molecular systems. He is experienced in population pharmacokinetic modeling, physiologically based pharmacokinetic (PBPK) modeling, as well as in the application of statistical and machine learning techniques to analyze high-dimensional datasets from gene expression and high throughput toxicity assays.