Large Quantitative Models

SandboxAQ generates proprietary data using physics-based methods, and trains Large Quantitative Models (LQMs) on that data, leading to new insights in areas, such as life sciences, energy, chemicals, and financial services. While Large Language Models (LLMs) have recently captured widespread attention, the next wave of AI — LQMs — promises an even greater impact.
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Biopharma

Accelerate drug discovery with faster, more accurate predictions for lead generation and hitting targets.
Generative AI-based output of new drugs optimized for multiple objectives including synthesizability.
Causal reasoning over multi-omics and literature-omics data to model biology and address scientific hypotheses directly.

New Materials

Develop new materials for cars, planes and construction.
Deliver increased efficiency, affordability, and sustainability.
Create new compounds, including innovative battery chemistries.

AQBioSim – Accelerating drug discovery from molecule to medicine

Our AQBioSim technology stack allows us to accurately predict the behavior of molecules, to generate new molecular structures with desired properties, and to combine these predictions into biologically-relevant insights. It includes AQ-FEP, the fastest available free energy perturbation solution, able to deliver unprecedented accuracy in affinity prediction even to the hit finding stage of drug discovery with no need for congeneric reference data.

LQM models trained on our physics-based technology go on to produce entirely new molecules from scratch with desired sets of properties. By combining our molecular simulation insights with biological pathway analysis inferred from literature, simulated, and omics data streams, we are able to connect the biological to the molecular scale, making predictions about target identification, toxicity, and qualitative disease mode of action (MOA).

AQChemSim – Large Quantitative Models for Chemicals & Materials

Designing and manufacturing new materials and chemicals has traditionally been slow, expensive, and challenging. AI can revolutionize discovery by creating novel molecules in seconds, but it relies on high-quality data, which is scarce. SandboxAQ addresses this through Large Quantitative Models, generating its own training data in silico and guiding AI with physics. This improves speed and accuracy, bringing products to market faster while reducing cost.

The AQ Difference

SandboxAQ has built a global team with some of the world’s foremost experts in AQ, including physicists, biologists, computational and medicinal chemists. We are working with global enterprises and government organizations to deliver practical solutions to the market today. Our expertise and deep ties with quantum leaders in academia, industry and the government make SandboxAQ uniquely qualified to develop unmatched AI simulation applications.

Our Scientific Advisory Board

Current and former attributions

Dr. Steven Deitcher, CEO, Bespoke Biotherapeutics
Dr. Nikhil Gupta, Professor of Mechanical Engineering, New York University
Dr. Samir N Khleif, Immunologist, Oncologist, Drug Discovery, NIH, Georgetown, Georgiamune
Dr. Geoff Ling, CEO, OnDemand Pharmaceuticals, Professor of Neurology, Johns Hopkins, DARPA Biotech
Dr. Chris Marianetti, Professor of Materials Science, Applied Physics, and Applied Mathematics, Columbia University

Dr. Dane Morgan, Professor of Materials Science and Engineering, University of Wisconsin
Dr. Adrian Roitberg, Professor of Chemistry, University of Florida
Dr. Mark Smith, PhD - Head of Medicinal Chemistry, Stanford, Sarafan ChEM-H, Roche
‍Dr. Patricia Weber, PhD - SBDD expert
Dr. Eva Zurek, Professor of Chemistry, University of Buffalo

Resources

CNBC: SandboxAQ CEO on the Firm’s Partnership with Sanofi

CNBC: Partnering on Large Quantitative Models

AI Explained - Using AI to Simulate Data

How Does Quantum Simulation Help Create New Drugs?

How AI & Quantum Simulation are Revolutionizing Medical Breakthroughs

AI & Quantum, Powering the Life Sciences - with Jack Hidary

AI Beyond LLMs: The Next Wave of Intelligent Solutions

SandboxAQ Supports the Open Molecular Software Foundation to Advance Simulation in Life Sciences and Materials Science

How the AI and Quantum Revolution Will Transform Drug Discovery and Medical Diagnostics

Beyond ChatGPT: AI Simulation Is The Next Frontier Of Advanced Computing

Biopharma’s Quantum Leap

Quantum Algorithms Meet AI Chips: A Breakthrough in Simulation

SandboxAQ Transforms Simulation Landscape with Good Chemistry Acquisition

Clarivate Named SandboxAQ a “Company to Watch” for AI/ML use in Drug Discovery and Life Sciences

Accelerating Drug Development and De-risking Drug Portfolios with AI+Quantum

What Should Be the AI Industry’s Top Focus? 5 Leaders Weigh in on the Next Year

SandboxAQ Helps Unlock the Next Generation of AI-Driven Chemistry with NVIDIA Technology

SandboxAQ Partners with U.S. Army DEVCOM to Support AI-Enabled Materials Discovery to Advance Armored Vehicle Alloys and Battery Design

SandboxAQ Acquires Good Chemistry to Accelerate AI Simulation Platform for Drug Discovery and Material Science

SandboxAQ Announces AI Simulation Collaboration with NVIDIA to Impact the Physical World

NOVONIX and SandboxAQ Collaborate on Breakthrough AI Solutions for Battery Technology

SandboxAQ Announces Biopharma Molecular Simulation Division to Speed Life-Saving Drugs to Patients

Guided Multi-Objective Generative AI to Enhance Structure-based Drug Design

Accelerated Organic Crystal Structure Prediction with Genetic Algorithms and Machine Learning

Massively Parallel Quantum Chemistry: PFAS on Over 1 Million Cloud vCPUs

Machine Learning Guided AQFEP: A Fast & Efficient Absolute Free Energy Perturbation Solution for Virtual Screening