Drug development

My take on Data Challenges in Immuno-oncology, the Role of the Cloud, and Growing a Computational Biology Team

The original link. https://connect.corrdyn.com/blog/ming-tang-on-data-challenges-in-immuno-oncology-the-role-of-the-cloud-and-growing-a-computational-biology-team Guest Profile Tommy Tang’s career began when he pursued his Ph.D. in genetics and genomics at the University of Florida. Initially trained in molecular biology in the wet lab, he was driven to explore computational biology after encountering the limitations of traditional analysis methods. Through self-study, Tommy developed skills that enabled him to analyze complex genomic data sets. Following his Ph.D., Tommy joined MD Anderson Cancer Center and later moved to Harvard and the Dana Farber Cancer Institute, where he worked on single-cell RNA sequencing.

Has AI changed the course of Drug Development?

What’s the drug development process? Has AI changed the course of Drug Development? To answer this question, we need first to understand the drug development process. The whole process includes the following: target identification target pharmacology and biomarker development lead identification, lead optimization Clinical research & development regulatory review of IND (investigational new drug) and later phase clinical trials post-marketing knowledge Biologics/antibodies drug development follows a similar path (you can find the map in the same link).