By Nadia Harhen, General Manager, AQBioSim
Identifying, understanding, and treating disease requires more than just clinical and technical expertise. It requires teamwork across the entire healthcare ecosystem – from academic and commercial research labs to the financial and tech communities, to government agencies and global health organizations. With new drugs taking an average of 10-13 years and $1.4 billion to $4 billion to develop, collaborations that can accelerate R&D and reduce the 88% drug failure rate in the preclinical and clinical stages will help lower costs, improve equitable healthcare access, and bring more effective, life-saving treatments to market and patients faster.
To that end, we are particularly proud of our collaboration with global professional services leader, Deloitte, whose data science and life sciences experience combined with global business and technology acumen is helping transform nearly every facet of healthcare and life sciences.
Specifically, our collaboration joins Deloitte’s extensive life sciences experience, data and research capabilities with SandboxAQ’s leadership in Quantitative AI simulation and Large Quantitative Models (LQMs) to accelerate the discovery and mechanistic understanding of new drugs. LQMs, trained on massive amounts of chemistry data and molecular structure libraries, can accurately predict molecular behaviors, identifying molecules that successfully execute a desired mechanism of action (MoA).
The beneficiaries of this collaboration are large multinational pharmaceutical companies, in addition to research organizations who seek to understand causal biological hypotheses. These institutions and organizations have leveraged SandboxAQ’s technologies for AI-driven biomarker identification – an exciting combination of LQM’s and AI, that allows for extension of our proven technologies and approaches from drug discovery to clinical development.
Using LQMs in collaboration with Deloitte’s Atlas AI™ knowledge graph capabilities will allow SandboxAQ’s scientists to automatically extract new clinical hypotheses from literature, highlighting only those most likely to be correct. Deloitte’s Atlas AI team and SandboxAQ will also collaborate with pharmaceutical companies and other organizations on data evaluation, exploratory data analysis, and AI model testing and evaluation to enhance the speed and accuracy of the drug discovery processes. Along the way, SandboxAQ’s AI-powered molecular simulations will generate vast amounts of highly accurate, physics-based data, delivering new insights for drug development, target ID, and treatment response.
LQMs are already proving impactful in many life sciences applications, including molecular screening, drug repurposing, drug portfolio optimization and clinical de-risking. They are also leading to new breakthroughs in treatment research for some of the most challenging medical conditions such as Alzheimer’s, Parkinson’s and various cancers.
Together, we hope to enhance researchers’ understanding of human biology at the molecular level and improve their ability to rapidly demonstrate the MoA, efficacy, and safety of investigational medicines and targets currently in the pharmaceutical company’s portfolio and pipeline.
