Unlock hit discovery for DUST (Difficult, Unscreenable Systems & Targets) using SandboxAQ’s AI- and physics-driven Virtual Screening Platform.

Traditional high-throughput screening struggles to efficiently explore today’s vast chemical spaces, often requiring thousands to millions of assay measurements to find a small number of promising hits. SandboxAQ’s AQBioSim solution addresses this gap by combining AI, physics-based simulation, and biological context into an integrated, virtual screening workflow that can prioritize a small number of high-value compounds for testing while expanding accessible chemical space.

In this webinar, we will walk through how SandboxAQ’s end-to-end virtual screening workflow combines protein and library preparation, retrospective validation, and multi-modal screening (similarity, shape, pharmacophore, docking, FEP, and AI/ML methods) with active-learning and ADMET/developability filters. We will summarize hit rate statistics in multiple proprietary engagements (anonymized).

Key Topics Include:

  • Understand the core building blocks of SandboxAQ’s virtual screening workflow—from target and library preparation through retrospective validation, protocol selection, and large-scale screening—and how these components integrate into existing discovery pipelines.
  • Learn how combining physics-based simulations and AI/ML methods enables exploration of larger chemical spaces.
  • Review outcomes across therapeutic areas and target classes where virtual screening campaigns delivered enriched hit lists.
  • Learn how to assess whether a program is a strong fit for SandboxAQ’s standard virtual screening service or should draw on SandboxAQ’s experience to develop a customized approach.

Presenters

Vice President, Drug Discovery
SandboxAQ

Andrea Bortolato brings over 20 years of experience in computational chemistry and drug discovery. He has worked in biotechnology, pharmaceuticals, and agrochemistry throughout his career, holding more than 50 scientific patents and publications, including three in Nature. Andrea holds a PhD in computational chemistry, earned in partnership between the University of Padua in Italy and the University of Geneva in Switzerland. He then completed a postdoctoral fellowship at Mount Sinai School of Medicine in New York City.

Production Partner

SandboxAQ

SandboxAQ is a B2B company delivering solutions at the intersection of AI and quantum techniques. The company's Large Quantitative Models (LQMs) deliver critical advances in life sciences, navigation, and other sectors. The company emerged from Alphabet Inc. as an independent, growth-backed company funded by leading investors and strategic partners including funds and accounts advised by T. Rowe Price Associates, Inc., Alger, IQT, US Innovative Technology Fund, S32, Paladin Capital, BNP Paribas, Eric Schmidt, Breyer Capital, Ray Dalio, Marc Benioff, Thomas Tull, Yann LeCun, and others. For more information, visit http://www.sandboxaq.com.

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