Researchers from the Interdisciplinary Scientific and Educational School “Brain, Cognitive Systems, Artificial Intelligence” at Moscow State University (MSU) have developed a model based on Paramecium caudatum infusoria for testing agonists and blockers of adrenoceptors. The results were published in the journal Clinical Case Reports and Reviews.

Developing new drugs requires hundreds of millions of dollars and takes years. One of the most expensive stages is the initial compound screening, when researchers select candidates for further testing, reports Scientific Russia. Traditionally, this involves using cell cultures or animal models, which are costly and raise bioethical concerns.

MSU scientists proposed a simpler and more affordable system — the use of Paramecium caudatum. These unicellular organisms are sensitive to chemical influences and display reproducible behavioral changes when exposed to pharmacological agents.

The study examined the effects of adrenoceptor agonists and blockers — key targets of many drugs used in cardiology, neurology, and anesthesiology. The researchers found that infusoria reliably respond to such substances, showing changes in mobility, movement direction, and sensitivity to stimulation. These effects were comparable to those observed in mammalian tissue experiments.

“We proposed a simple and accessible model that allows rapid detection of pharmacological effects of compounds. Using infusoria helps reduce research costs and overcome ethical limitations associated with working on vertebrate animals,” emphasized Gleb Gruzdev, a research fellow at the Department of Higher Nervous Activity, Faculty of Biology, MSU.

The authors note that this system can be used not only in pharmacological laboratories but also in education: students can learn experimental biology techniques using living organisms without the need to work with vertebrates.

The study demonstrates that simple organisms can serve as valuable tools for modern biomedical research, helping to accelerate the development of new drugs while reducing reliance on more expensive and ethically sensitive models.