Our Expertise in Artificial Intelligence & Drug Development

Over several years, we have been envisioning a future where advanced AI models and extensive data access power limitless in silico simulations of complex biology, enhancing in vitro and in vivo experiments and unlocking groundbreaking insights. In line with our vision, we integrate novel technology into our drug development to boost R&D. The objective is not only to shorten the time necessary to deliver innovative treatments to patients but also improve efficiency and reduce costs.

What is AI applied to Drug Development?

Artificial Intelligence (AI) in drug development involves using machine learning and computational models to improve the efficiency of drug discovery and development. AI can be used in a vareity of R&D applications, including to help identify potential drug targets, predict efficacy, optimize clinical trials, and accelerate the time-to-market for new drugs. Its use can result in reduced costs, errors, and time spent, ultimately speeding up delivery of therapeutics while supporting personalized treatments based on specific genetic profiles.

AI to accelerate and sharpen the R&D pathway

“Collaborating with AI startups can be transformative: Debiopharm enjoys a privileged access to the most innovative start-ups in this space thanks to the strategic investments led by our Innovation Fund, which inspire future-proof innovation.”

Because precision medicine must start with precision R&D strategies, we built strong convictions in the power of AI-driven biomarkers to help predict success in the early stages of clinical development.

How we're applying our expertise

Discovery of novel biomarkers

AI identifies patients that are most likely to benefit from a particular drug, increasing the success of a clinical trial

Optimized Trial design

Using digital twins, AI models can simulate clinical trials to predict outcomes, allowing pre-trial adjustments and saving resources and time

Accelerated patient recruitment

AI can accelerate the patient selection for clinical trials by using advanced analytics to identify suitable candidates based on genetics and disease

Global pharmaceutical AI facts and figures


1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577280/

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