This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: 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 for the research, the AI was fed scientific knowledge, including the yeast's genome, metabolism and previous studies. The study is published in the Journal of the Royal Society Interface.
"It is too much information for a human to analyze, 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 a decision-support tool, the AI scientist actively generates new scientific knowledge," says Ievgeniia Tiukova, a postdoctoral researcher in 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 experimental capabilities is unusual and cutting-edge in 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, a professor in the Department of Computer Science and Engineering at Chalmers and the University of Gothenburg and the study's senior author, autonomous laboratories will revolutionize 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 optimize the use of laboratory resources," says King. Both authors emphasize 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 King. Daniel Brunnsåker et al, Agentic AI integrated with scientific knowledge: laboratory validation in systems biology, Journal of the Royal Society Interface (2026). DOI: 10.1098/rsif.2026.0043 Journal information: Journal of the Royal Society Interface Provided by Chalmers University of Technology BSc Life Sciences & Ecology.
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