How AI applications are facilitating new life science discoveries
The disruptive potential of AI is only just beginning to be realised. Data analyses that might once have taken weeks, months or even years can now be performed far quicker, leading to faster results. Research into life sciences – an area that studies all life on our planet, from microorganisms, plants, animals and humans to whole ecosystems – is primed to take advantage of this technological revolution. For example, machine learning algorithms capable of analysing complex biological data are increasingly being used to make predictive health models, opening the door to more personalised healthcare. AI tools can also help to simulate the potential effect of novel treatments and drugs, identifying promising molecules and highlighting potential side effects well before clinical trials begin. It is notable that the 2024 Nobel Prizes in Physics and Chemistry were essentially for AI in science, with the Nobel Prize in Chemistry being awarded for AI research into protein structure prediction. “I’ve always thought if we could build AI in the right way, it could be the ultimate tool to help scientists,” says DeepMind cofounder and Nobel Laureate(opens in new window) Demis Hassabis. Beyond the fields of health and medicine, the ability to analyse vast amounts of disparate information from a range of sources can significantly improve decision-making processes. Policymakers trying to protect ecosystems for example need to take account of a range of complex issues before identifying the best path forward. AI-powered tools can help to collate and structure such information in a usable and practical manner.
Boosting innovation and competitiveness
This Results Pack presents a diverse portfolio of projects supported by the European Union, which demonstrate how the application of AI is facilitating new discoveries in life sciences. AI in science in general, and life sciences in particular, are among the political priorities of the European Commission, as highlighted by President Ursula von der Leyen’s Mission Letter(opens in new window) to the Commissioner for Start-ups, Research and Innovation. In the letter, President von der Leyen calls for “a new multi-disciplinary Strategy for European Life Sciences(opens in new window), to unlock high-value technologies in support of green and digital transitions”, as well as for “a strategy to increase the uptake of AI by European scientists”. These new strategies will be published in 2025. The projects highlighted in this Results Pack support the European Union’s work in this field and will help to maintain the EU’s position as a global pioneer in science and in AI. This will be critical to boosting European competitiveness and the creation of new sustainable jobs. The EU-funded projects highlighted in this Pack demonstrate how the application of AI tools is deepening our understanding across the life sciences, potentially leading to groundbreaking solutions to address a range of complex challenges. The knowledge generated is also helping policymakers and stakeholders to fully understand the benefits associated with AI tools, and to take supportive action accordingly. Many of these projects have had an important health aspect. AI-PREVENT for example applied AI to datasets covering health and other lifestyle factors, to achieve more predictive and personalised healthcare. Similarly, AI-SPRINT used machine learning to develop models for stroke risk assessment, combining sensory data with lifestyle information. The AI tools pioneered in MIRIADE could transform dementia care by enabling earlier diagnoses, while Disc4All’s AI- and computer simulation-driven tools could provide clinical support to identify and address spinal degeneration. EAR meanwhile focused on AI-enabled wearable mobile devices, designed to track health through analysing body sounds. FEMaLe developed clinical decision support tools – powered by AI – to help doctors identify endometriosis earlier. H-MIP applied both citizen science and AI techniques to better understand – and prevent – the transmission of mosquito-borne ailments, while MOOD leveraged data science to boost Europe’s readiness against emerging infectious diseases. GATEKEEPER developed an AI-powered healthcare platform to prevent, manage and treat age-related conditions. Projects also applied AI tools to a range of datasets, bringing together diverse information. EPOCHAL used AI to reconstruct historic pollen exposures for research into health impacts, while GUARDEN developed new AI-driven tools to help policymakers better integrate biodiversity issues in the decision-making process. Health CASCADE applied digital technologies and AI to enhance and support scientific training across a number of related disciplines. WaterSENSE integrated data on water usage to ensure regulatory compliance, helping to ensure more optimal use of this valuable resource. Another environment-focused project was MAELSTROM, which used artificial intelligence and other digital technologies to prevent plastic waste from entering the ocean. FoodSafeR used AI to collect data for early signs of emerging food risks, helping experts to respond quickly and confidently. Two other EU-funded projects worth noting are BMAI, which has sought to automate a number of repetitive tasks to improve cancer diagnostics, and d3pm, which has pioneered AI-powered image recognition to detect prenatal malformations.
