National excellence cluster in AI-driven antibiotic innovation

Research Project, 2025 – 2026

Antimicrobial resistance is a major challenge of our time. Without effective interventions, the world will see a considerable loss of human lives and a drastically increased financial burden on the health system.Despite multilateral efforts, drug development is not meeting this need. The core issue is the unsustainably high compound drop-out rate over the course of the development pipeline due to the extensive experimental effort required to transform lead compounds into mature drug candidates not being economically viable.We aim to harness the transformative power of artificial intelligence (AI) to address this problem. Current AI models focus on the first step of drug discovery, overlooking the main issue of screening hits not meeting essential drug criteria beyond on-target activity. Our mission is to provide accurate, data-driven predictions of new drugs with desirable properties, to increase hits and reduce failure rates over the entire pipeline.To achieve this, our cluster connects experts in each step of the pipeline, from drug design to clinical studies, with AI and ethics experts to holistically address the issue.We will identify needs for specific training data, map out routes to efficient data acquisition, assess the suitability of existing and the need for innovative AI models, rule out the best production and testing pipelines, and assess ethical and policy-related concerns to achieve an optimal integration of experimental, theoretical, and social sciences.