AI Transforms Drug Discovery by Designing New Compounds and Enabling Personalized Medicine

At the Barcelona BioMed Conference, global experts revealed how AI is rapidly designing new drugs, automating lab synthesis, and driving a new era of precision medicine tailored to individual patients.

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Image Credit: IRB Barcelona

Between 31 March and 2 April, IRB Barcelona, supported by the BBVA Foundation, hosted the 43rd Barcelona BioMed Conference, entitled "AI in Drug Discovery and Biomedicine". Held in the emblematic Casa de Convalescència in Barcelona, and organized by Dr. Patrick Aloy (IRB Barcelona) and Dr. Trey Ideker (UC San Diego, US), the conference gathered 150 international researchers to explore the potential of artificial intelligence (AI) to transform drug discovery.

The technological revolution that is transforming biomedicine

AI has become one of the greatest technological revolutions of our time. In the field of biomedicine, its ability to process large datasets and generate predictive models unlocks possibilities ranging from a deeper understanding of cellular processes to the design of new compounds with clinical applications.

Over three days, renowned national and international experts presented their latest advances. They discussed key topics such as training "foundation models" with large-scale biological data, the importance of understanding medical predictions, the design of proteins and other therapeutic targets, and the experimental validation of these approaches, including robotic laboratories for the automated synthesis of molecules.

Drug design using generative AI

The conference also delved into generative AI strategies, which enable the de novo design of chemical compounds with specific properties. These techniques have already demonstrated their potential in advancing anticancer drugs and novel antibiotic structures to clinical trials. Currently, an estimated 15 machine-learning-designed drugs are in various stages of clinical testing. Additionally, discussions covered progress toward integrating robots capable of automatically synthesizing AI-designed compounds, further bridging the gap between theory and clinical application.

Finally, the speakers emphasized the significance of personalized medicine—a future in which therapies will be tailored to each patient’s unique molecular profile, harnessing the full power of AI and biological big data, rather than relying on the best available approved drug.

Among the prominent speakers were Dr. Fabian Theis (University of Munich TUM, Munich, Germany), an expert in automated learning applied to biological data; Dr. Marinka Zitnik (Harvard Medical School, Boston, US), an expert in AI and mass analysis of biomedical data; Dr. Ola Engkvist (AstraZeneca, Gothenburg, Sweden), a specialist in automated learning and AI for the development of new molecules; and Dr. Julio Sáez-Rodríguez (EMBL-EBI, Hinxton, UK), a leader in computational models for integrating biomedical data.

"We are witnessing a revolution where AI is not only accelerating drug design but also redefining how we understand and treat diseases. It is a transformative shift that opens the door to more effective and personalized medicine," says Dr. Patrick Aloy, ICREA researcher at IRB Barcelona and co-organizer of the conference.