Generative AI in life sciences is helping us reimagine the future of human health

Humanity is entering an era where biology and computation are converging. Generative artificial intelligence (GenAI) has emerged as one of the most powerful catalysts accelerating progress in life sciences, amplifying other biotechnologies such as CRISPR and cell engineering.

AI is becoming integral to the human experience, with applications already shaping daily life. The rapid adoption of tools such as ChatGPT illustrates how deeply AI can augment human capabilities.

Like many transformative technologies, AI has experienced its share of “winters.” However, confidence is higher than ever that we are at a true inflection point in the life sciences. As these technologies mature, the boundaries between disciplines are beginning to blur.

Large foundation models, multimodal datasets and advances in the study of large-scale biological molecules, such as DNA and proteins are enabling breakthroughs at a pace once thought impossible.

While the pharmaceutical industry has yet to achieve the equivalent of “Moore’s law” for drug development, we now have vastly better tools to decode life’s secrets.

A landmark example is the solution to the protein-folding problem: deep learning enabled the accurate prediction of 3D protein structures, a breakthrough recognized with the 2024 Nobel Prize in Chemistry, awarded to David Baker, Demis Hassabis and John Jumper.

Proteomics – the large-scale study of the proteome or proteins – has become a new cornerstone of discovery. Single-cell proteomics now makes it possible to characterize protein expression at the resolution of individual cells, uncovering novel cell types and revealing true mechanisms of disease. This insight enables more rational molecule design.

Organoids, as customizable, scaleable model systems, bridge the gap between in vitro and in vivo research. They support high-throughput screening and personalized drug testing more accurately and cost-effectively.

The Virtual Cell framework is another transformative development. By integrating biological data with AI foundation models, scientists can simulate living cells across multiple scales. This allows biologists and computer scientists to collaborate in building computational models of cell behaviour, greatly accelerating drug discovery and biomedical research.

The following breakthroughs highlight fundamental ways in which AI is reshaping how scientists explore, test and interpret biology.

Virtual cell models simulate fundamental rules and components to generate complex, life-like behaviours such as cell division, migration and death. For example, ageing can be studied computationally without waiting for years of natural progression.

This evolution toward “virtual patients” and “virtual clinical trials” allows researchers to predict treatment outcomes while reducing time and cost compared to traditional experiments.

Biological perturbation, an alteration of the function of a biological system, can occur at the level of genes, proteins or molecules. A central challenge in drug development is reproducibility – results can differ drastically between labs or even individual researchers.

Automation and robotics offer a solution, standardizing workflows and embedding quality control into each step of experimentation, especially critical in cell and gene therapies.

If ChatGPT represents a breakthrough in decoding human language, when will we achieve the same for DNA and proteins? Foundation models for biology are rapidly emerging, with specialized applications in neuroscience to decode the brain and metabolism to guide health and lifestyle interventions.

These models can uncover biological “rules” from vast datasets without human predefinition, opening entirely new frontiers of interpretation.

Building on these approaches, GenAI is already driving tangible progress across multiple domains of life sciences.

GenAI is accelerating both discovery and development. In discovery, it identifies novel targets and optimizes molecular design. In development, it streamlines preclinical validation, designs safer and more effective delivery systems for cell and gene therapies, and creates smarter clinical trials.

By simulating patient populations, predicting outcomes and synthesizing real-world data from electronic health records and wearables, AI shortens the path from concept to clinic and enhances regulatory readiness.

AI personal assistants can analyze multimodal data in real time, providing doctors with longitudinal, 360-degree patient insights. Acting as “longevity assistants,” they support personalized care in ageing societies where scalable medical teams are impossible.

By continuously tracking progress at marginal cost, AI ensures individualized diagnosis, monitoring and treatment.

AI is enabling seamless neural decoding, translating brain signals into interaction with external devices.

This creates bidirectional communication between biological cognition and computational systems – unlocking assistive technologies for patients and pioneering new human-machine interfaces that expand human potential.

GenAI brings a modular, “plug-and-play” approach to designing biological systems. It predicts how engineered cells, organisms or molecules will behave, enabling rapid development of novel organisms, new materials and chemical properties.

These advances accelerate innovation across medicine, food and agriculture, and industrial biotechnology.

As these technologies mature, the boundaries between disciplines will blur even further. Biologists, data scientists, clinicians and engineers are now part of a shared ecosystem where progress in one domain accelerates breakthroughs in others.

The convergence of AI with life science is not just about speed or efficiency; it is about reimagining what is possible.

This comes with opportunities and also challenges:

Ethical frameworks, equitable access and careful stewardship of data will determine whether these advances serve humanity as a whole.

GenAI presents a unique opportunity to redefine the foundations of humanity. The challenge – and the promise – is to wield it wisely, with vision and with courage.