Computer-Aided Drug Design and Workload Automation

Watch it On Demand

What you’ll learn:

  • Why high performance computing (HPC) platforms built for the cloud, are key to providing on-demand access to the latest software and hardware for today’s evolving drug discovery workloads
  • A guide to simplifying the building of advanced and innovative drug discovery pipelines with generative AI
  • Strategies for optimizing complex computational workloads to accelerate simulation, modeling, and analysis at unprecedented scale
  • How to leverage AI frameworks to streamline model development and reduce experimental bottlenecks
  • And more

Discover New Possibilities for Drug Design with Rescale, NVIDIA, and AWS

Computer-aided drug design (CADD) that combines computational chemistry, molecular modeling, and rational drug design with artificial intelligence (AI) and machine learning is rapidly changing the technological landscape of drug discovery.

This session dives deep into these advanced computational methods. We’ll take an exciting look at how they are enabling more sophisticated analysis of molecular interactions and better predictions of drug behavior, reducing the time and cost associated with the drug development process.

Nikhil Venkat
Customer Success Engineer

Nikhil Venkat is a Customer Success Engineer at Rescale, where he partners with leading healthcare and life sciences organizations to accelerate R&D through cloud-based HPC. With a background in mechanical engineering and deep expertise in GPU-accelerated workloads, Nikhil helps teams scale AI/ML and physics-based simulations for applications such as crystal structure prediction (CSP), molecular dynamics, and drug delivery modeling. His work enables faster, more efficient R&D workflows—empowering researchers to reduce time to insight and make smarter, data-driven decisions. Nikhil collaborates closely with partners like NVIDIA and AWS to deliver optimized, scalable solutions that advance drug discovery and diagnostics.

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