The disruptive potential of AI is only just beginning to be realized. Data analysis that once took weeks, months, or even years can now be performed much more quickly, yielding faster results. Life science research, the field that studies all life on Earth, from microbes, plants, animals, and humans to entire ecosystems, is poised to take advantage of this technological revolution. For example, machine learning algorithms that can analyze complex biological data are increasingly being used to create predictive health models, opening the door to more personalized healthcare. AI tools can also help simulate the potential effects of new treatments and drugs, identify promising molecules, and highlight potential side effects long before clinical trials begin. It is worth noting that the 2024 Nobel Prizes in Physics and Chemistry are essentially for AI in science, while the Nobel Prize in Chemistry was awarded for AI research on protein structure prediction. “I always thought that if we built AI the right way, it could be the ultimate tool to help scientists,” says DeepMind co-founder and Nobel laureate.(Opens in new window) Demis Hassabis. The ability to analyze vast amounts of disparate information from a variety of sources across health and medical fields greatly improves the decision-making process. For example, policymakers seeking to protect ecosystems must consider a range of complex issues before identifying the best way forward. AI-powered tools can help collate and structure such information in an easy-to-use and actionable way.
Strengthening innovation and competitiveness
This results pack presents a diverse portfolio of European Union-supported projects that demonstrate how the application of AI is driving new discoveries in the life sciences. AI in science in general and life sciences in particular is one of the European Commission's political priorities, as highlighted in President Ursula von der Leyen's mission letter.(Opens in new window) Secretary for Start-ups, Research and Innovation. In her letter, President von der Leyen calls for “a new interdisciplinary strategy for European life sciences.”(Opens in new window)“Unlocking high-value technologies to support green and digital transitions” and “Strategies to accelerate the adoption of AI by European scientists”. These new strategies are expected to be announced in 2025. The projects featured in this result pack support the European Union's efforts in this field and help maintain the EU's position as a global pioneer in science and AI. This is important to increase Europe's competitiveness and create new, sustainable jobs. The EU-funded project Pack featured here shows how the application of AI tools can improve understanding across the life sciences and lead to innovative solutions that address a range of complex challenges, while also helping policy makers and stakeholders fully understand the benefits associated with AI tools and take supportive action accordingly. For example, AI-PREVENT uses AI to enable more predictive and personalized healthcare. The AI tools developed at MIRIADE have the potential to transform dementia care by combining sensory data and lifestyle information. Meanwhile, Disc4All's AI and computer simulation-powered tools can provide clinical support to identify and address spinal degeneration. Meanwhile, FEMaLe has developed an AI-powered clinical decision support tool to help doctors detect endometriosis early. The project leverages both citizen science and AI technologies to better understand and prevent the transmission of mosquito-borne diseases, while MOOD developed an AI-powered healthcare platform to improve Europe's response to emerging infectious diseases. EPOCHAL also used AI to reconstruct past pollen exposure and develop new information to study health effects. To help policymakers better integrate biodiversity issues into their decision-making processes, Health CASCADE has applied digital technology and AI to integrate data on water use, ensure regulatory compliance, and ensure more optimal use of this precious resource. FoodSafeR used AI to collect data that indicates emerging food risks. Two other notable EU-funded projects to help professionals respond quickly and confidently are BMAI, which seeks to automate many repetitive tasks to improve cancer diagnosis, and d3pm, which is pioneering AI-powered image recognition to detect prenatal malformations.
