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.
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?
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.”
At Debiopharm, we’re embracing the AI revolution to stay competitive in R&D. Our commitment is 2-fold: we invest in AI-driven health tech start-ups and we integrate AI-based technology in our R&D.
We recognize that AI tools can add value across the entire drug development lifecycle, from early target discovery to biomarker identification, and on to clinical validation. So, our Digital Health Fund strategically invests in start-ups with high potential impact and our scientific teams are using specifically designed technology to accelerate processes. We’re aiming to leverage specialized AI tools to develop new treatments for patients, faster.
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
Collaboration with our portfolio startups
Risklick and DebiopharmSuccessful completion of a key milestone within their pilot project Genialis and Debiopharm
Set Up Biomarker Discovery Collaboration Nucleai and Debiopharm
Launch Research Collaboration Investments' Portfolio
Insights from our Experts
Global pharmaceutical AI facts and figures
7.2B
$2.8B
$2.2B
25%
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7577280/
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