Expanding RetroSynth: Dynamic AI-driven synthesis planning proven to move your designs from bench to synthesis
Date & Time 
Location - Virtual
Designing a high-quality lead is only half the battle – the true challenge lies in identifying a reliable, cost-effective synthetic route before your competition does. Traditional manual retrosynthesis often leads to “hallucinated chemistry” or expensive, multi-stage custom synthesis that stalls project momentum.
In this webinar, we revisit RetroSynth, Schrödinger’s AI-powered solution for intelligent synthesis planning. Our product managers will walk you through the exciting updates we have made and present real-world case studies to demonstrate RetroSynth’s immediate impact.
Join us to see a demonstration of these updates in action and learn how to integrate these workflows into your existing R&D pipeline to drive down costs and maximize lab productivity.
Key Highlights
- What’s new in RetroSynth: Our product manager will introduce new updates to RetroSynth, including vendor library integration
- See it in action: Join us for a demo on how you can generate reliable, cost effective synthesis routes with just a few clicks
- Real-world case study: Our medicinal chemist will walk you through how RetroSynth integrates into Schrödinger’s internal programs
Who Should Attend
- Medicinal Chemists looking to bypass manual route-finding and reduce synthesis failure rates
- Computational Chemists wanting to prioritize compounds based on synthetic accessibility and cost
- R&D IT and Platform Leads interested in integrating AI-driven synthesis planning into existing workflows
- Procurement and Lab Managers focused on optimizing project spend through strategic building block sourcing
Our Speakers
Nilesh Khedkar
Senior Scientist, Therapeutics Group, Schrödinger
Nilesh Khedkar, senior scientist in the therapeutics group, joined Schrödinger in 2023. As Medicinal Chemist at Schrödinger, where he applies advanced modeling and de novo design to drug discovery programs and oversees CRO chemistry efforts and helps develop the RetroSynth tool. With a Ph.D. from Manipal Academy of Higher Education, his career includes leadership roles at Aragen life science, and key medicinal chemist roles at Lupin, and Zydus. His expertise spans the entire lifecycle from hit identification to development candidates, backed by a strong portfolio of patents and publications.
Sathesh Bhat
Executive Director, Therapeutics Group, Schrödinger
Sathesh Bhat, Ph.D., executive director in the therapeutics group, joined Schrödinger in 2011. He is responsible for overseeing computational chemistry efforts on internal and partnered drug discovery programs at Schrödinger. Previously, Sathesh worked at both Merck and Eli Lilly leading computational efforts in several drug discovery programs. He obtained his Ph.D. from McGill University, which involved developing structure-based methods to predict binding free energies. Sathesh has co-authored multiple patents and publications and continues to publish on a wide variety of topics in computational chemistry.