Accelerating Polymeric Vector Discovery via High-throughput Experimentation and Cheminformatic Models


Ramya has extensively employed data-driven approaches to map relationships between polymer properties and biological responses, such as proliferation rate, cellular uptake, toxicity and delivery efficiency. She is interested in establishing high-throughput experimental (HTE) workflows for biomaterial discovery and in applying statistical learning methodologies on large experimental datasets to derive structure-activity relationships. 

She wishes to combine high discovery rates afforded by parallelized experimentation as well as to efficiently test multiple mechanistic hypotheses concurrently, ultimately yielding hit polymers and revealing the structural basis for delivery performance.

Check out Ramya’s talk on developing materiomics approaches to polymeric gene delivery below: