New frontiers: the Crick's next decade

The next decade of discovery at the Crick will be shaped by advances in technology and techniques.

Questions that once seemed out of reach are being answered, and entirely new areas of research are emerging.

Biology is becoming increasingly integrated, quatitative and data-rich, and the ability to combine experiments, computation and human data at scale is laying the foundations for future scientific breakthroughs.

New ways of doing science

Reimagining scientific discovery in the age of AI

Mihaela van der Schaar

The next decade of biology will be shaped by how well scientists and AI learn to think together.

At the Crick, our ambition goes beyond using AI to analyse data faster or speed up established workflows. We want to build AI for discovering biology: a continuously learning partnership that helps scientists look beyond the questions and explanations already in view.

AI can widen what we notice, remember and connect across experiments, scales and laboratories. Biologists bring the questions, tacit knowledge, imagination and judgement that give those connections scientific meaning. Together, we will be able to ask bigger and bolder questions, challenge our favoured explanations and design experiments whose outcomes change what we believe.

Our strategy rests on three connected efforts. The Crick Discovery Engine will turn unexplained observations into verified hypotheses and foresighted experimental programmes. Crick Living Worlds will build causal models of interacting biological entities, from molecules to cells, tissues and organisms, that scientists can inspect, challenge and revise. Crick AI Collaborators will provide the persistent scientific memory and critical reasoning that link this work across laboratories and over time, so that the Crick learns as an institute, not as a collection of separate projects.

Because the Crick generates both the data and the AI, we can hold ourselves to a demanding standard. Our models will commit to claims before the experiment is done, and we will test them against reality, often within the same programme and building. Our goal is for the Crick to become the place where we learn what AI must become to understand life, and where scientists and AI together make discoveries that neither could make alone.

Studying biology in context

James Briscoe

Most mutant cells never form tumours. Most infections resolve. Most inflammatory responses heal. Disease arises when a tissue or the body can no longer keep these changes in check. Whether that happens depends on context. Genetic effects are influenced by environmental factors, including lifestyle, diet, infection, pollution, and the microbial communities that inhabit our bodies.

They are also shaped by factors such as biological sex, age, and medical history. The same genetic variant can have different consequences in different tissues and at different times of life. The same infection can resolve in one person and become chronic in another. Understanding how these influences interact, combine or conflict is critical to explaining why health and disease can vary so widely between individuals and across populations.

New technologies are making it possible to capture this complexity in much greater detail. Advances in imaging, genomics, and spatial biology, to name but a few, are generating vast multimodal datasets at scale. Instead of studying the activity of single genes or cells in isolation or at single time points, researchers can now follow biological processes as they unfold in real time, across molecules, cells, tissues, organs, whole organisms and even populations. And AI, integrated into experimental science, supplied with biological data, is helping scientists make unanticipated connections, design experiments and validate results.

The challenge for biomedical scientists is to integrate these multiple layers of information and turn them into helpful biological understanding and applied medical insight. This scientific and technological revolution is an opportunity to move beyond describing life's complexity towards explaining it.

Training clinician scientists in the age of AI

Charlie Swanton

Many human diseases evolve over decades. AI can help us understand why risk and resilience differ between people based on their genetics, sex, age, infections and exposures.

The possibilities are enormous and the need is urgent. Long-term health conditions account for a huge proportion of health and social care spending because too much of modern medicine is restricted to managing disease once it's established. AI can help shift the focus earlier, to the biology that sets disease in motion.

The technologies emerging from studies like those at the Crick are changing both how medicine is practised and how research is conducted. Future clinician-scientists will need to combine expertise in patient care with an understanding of human biology, data science, genomics and artificial intelligence to ensure that these tools remain fucsed on patient needs and real-world challenges.

This is why, along with our established doctoral and postdoctoral clinical fellowship programmes, we're developing a new specialist AI and machine learning clinical training programme, supported by Cancer Research UK and Wellcome, designed to bring clinicians into closer contact with AI-enabled biology, equip them to ask better research questions and help them shap the next generation of data-driven healthcare.

Questions shaping the next decade

The most significant advances in biological understanding often reveal entirely new research questions. For biomedical researchers, several new fundamental challenges are coming into focus that could shape the direction of discovery for years to come.

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Explore more from our first decade

In November 2026, we're celebrating the 10th anniversary of the Crick's official opening.