AI scientist autonomously generates and validates new biological discoveries
Researchers at Chalmers University of Technology in Sweden have developed an AI scientist capable of generating scientific hypotheses, designing experiments, and interpreting results. Making new biological discoveries with minimal human intervention is an important advance in self-driving laboratories.
By combining advances in large language models, automated reasoning and laboratory automation, the researchers created a closed-loop AI laboratory, capable of conducting research on brewer’s yeast, Saccharomyces Cerevisiae. As the basis of the research, the AI was input scientific knowledge, including the yeast’s genome, metabolism and previous studies.
“It is too much information for a human to analyse, but our AI scientist could identify promising biological questions, recommend experiments to test them, evaluate experimental outcomes and iteratively refine its understanding based on new evidence. Rather than serving solely as decision supporting tools, the AI scientist actively generates new scientific knowledge”, says Ievgeniia Tiukova, postdoctoral researcher at the department of Life Sciences at Chalmers University of Technology, and one of the authors of the new study.
Integrating the thinking power of AI with an experimental capability is unusual, and cutting edge within a rapidly expanding area, where AI scientists autonomously perform extensive research. Tiukova compares the development to that of self-driving cars, where AI and machine learning are also used to process information, draw conclusions, and take action.
According to Ross King, Professor at the Department of Computer Science and Engineering at Chalmers and the University of Gothenburg, and the study’s senior author, autonomous laboratories will revolutionise research by systematically investigating biological systems much faster than is possible today.
“AI Scientists will collaborate with human scientists to accelerate discoveries across biology, medicine and biotechnology. Such AI systems have the potential to reduce the time required to explore complex scientific questions, and optimise the use of laboratory resources”, says Professor King.
Both authors emphasise that autonomous AI will, for now, augment rather than replace scientists, by increasingly undertaking the routine cycles of hypothesis generation and experimental testing.
“Human scientists remain essential for defining research priorities, interpreting broader scientific significance and ensuring ethical oversight. Future generations of autonomous discovery systems will become increasingly capable of collaborating with human scientists, becoming valuable partners in addressing some of the most challenging questions in biology and medicine”, says Professor King.
Captions:
Top collage: Researchers have created a closed-loop AI laboratory, capable of conducting research on brewer’s yeast. It could identify biological questions, recommend experiments and evaluate experimental outcomes. The images shows the robot scientist Eve at Chalmers University of Technology in Sweden, which was specifically designed for drug discovery, and which has now been updated with large language models and automated reasoning. Credit: NIH Image Gallery/Chalmers University of Technology
Attached image: Ievgeniia Tiukova and the Robot scientist Eve at Chalmers University of Technology in Sweden
About AI scientists
Professor Ross King was the first to develop the concept of a general-purpose robot scientist. His first robot scientist, Adam, was designed to autonomously carry out scientific experiments and generate new knowledge. He later developed a second robot scientist, Eve, which was specifically designed for drug discovery.
The underlying concept of using robotic systems to automate and accelerate scientific discovery has since been extended to other areas of research, including chemistry and other specialised scientific tasks.
More about the research:
The study Agentic AI integrated with scientific knowledge: laboratory validation in systems biology was published in the Journal of the Royal Society Interface.
The authors of the study are Daniel Brunnsåker, Alexander H. Gower, Prajakta Naval, Erik Y. Bjurström, Filip Kronström, Ievgeniia A. Tiukova and Ross D. King. The researchers are affiliated with Chalmers University of Technology, the University of Gothenburg and the University of Cambridge in the UK.
The study has received funding from the Wallenberg AI, Autonomous Systems and Software Program (WASP), the UK Engineering and Physical Sciences Research Council, Chalmers AI Research Centre (CHAIR), and the Swedish Research Council for Sustainable Development, Formas.
For more information, please contact:
Ievgeniia Tiukova, postdoctoral researcher at the Department of Life Sciences, Chalmers University of Technology: +46 728 - 36 33 93,
tiukova@chalmers.se
Ross King, Professor at the Department of Computer Science and Engineering, Chalmers University of Technology and the University of Gothenburg: +46 (0)31 772 17 60, rossk@chalmers.se
Ievgeniia Tiukova speaks Ukrainian, English and Swedish. Ross King speaks English. Chalmers has podcast studios and filming equipment on site and can provide assistance with requests for TV, radio, or podcast interviews.
Mia Halleröd Palmgren
Press Officer
+46-31-772 3252
mia.hallerodpalmgren@chalmers.se
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