By Pesach Benson • July 2, 2026
Jerusalem, 2 July, 2026 (TPS-IL) — Israeli scientists have created a method for turning human cells into programmable “decision-making” systems, allowing them to evaluate multiple biological signals at once before responding. The breakthrough could significantly advance the development of next-generation medical treatments, where engineered cells diagnose disease from within the body and deliver targeted therapy only when needed.
Researchers at the Hebrew University of Jerusalem have developed a method for engineering human cells into programmable “decision-making” systems that can process and respond to multiple biological signals simultaneously. The advance moves a step closer to what researchers describe as programmable living therapies.
Scientists have long sought to engineer cells that can recognize disease and respond automatically. However, traditional genetic circuits tend to become less efficient as they grow more complex. Each added layer of genetic “logic” introduces biological noise, reducing reliability and making such systems difficult to scale for clinical use.
The new approach, developed by PhD student Keren Roas and Dr. Lior Nissim, addresses this limitation by reducing the number of genetic steps required for cellular decision-making. Instead of relying on long chains of sequential reactions, the system uses RNA trans-splicing, a natural cellular process in which fragments of genetic messages are joined together. The researchers combined this with engineered regulatory elements that function like compact biological processors.
By restructuring the way genetic instructions are processed, the system allows cells to evaluate multiple biological signals at the same time rather than one after another. In practical terms, a cell can assess several conditions in parallel and respond only when the correct combination is present, improving efficiency while reducing the number of required genetic components.
To demonstrate the concept, the team built biological devices that mimic basic elements of computer systems. These included a biological “full adder,” capable of performing binary arithmetic, and a biological “multiplexer,” which selects between different input signals. Fluorescent proteins were used to visualize the outputs inside living cells, allowing the researchers to observe the engineered circuits functioning in real time.
The system also incorporates a built-in safety mechanism: if a cell detects an invalid or overloaded configuration, it produces a warning signal. The researchers say this feature could help identify errors and improve control in future experimental and therapeutic applications.
The researchers emphasized that the system remains at an experimental stage and has not yet been tested in clinical settings.
The approach could have future applications in targeted cancer therapy, in which engineered cells would be programmed to recognize specific combinations of tumor-related signals before releasing a therapeutic response. This conditional activation could help reduce harm to healthy tissue compared with some conventional treatments.
In immunotherapy research, the team demonstrated a version of the system in which cells were programmed to produce Interleukin-15 (IL-15), a protein that enhances the activity of cancer-fighting immune cells. Future iterations could enable more precise immune activation, limiting unnecessary stimulation elsewhere in the body.
Another potential application is localized drug delivery. Instead of distributing medication systemically, engineered cells could function as internal sensors and production units, generating therapeutic molecules only when specific disease conditions are detected in their immediate environment.
Researchers suggest the approach could eventually support the development of medicines designed more like software, in which biological “code” directs living cells to diagnose and treat disease. However, they stress that the work remains experimental.
The study was published in the peer-reviewed journal Nature Communications.
