Scientists Achieve First-Ever Use of AI in Designing Genetic Circuits
Published: 10 Mar 2026
Author: Precedence Research
Researchers at Rice University have demonstrated the first successful use of artificial intelligence to design genetic circuits in living cells. This development represents a major step forward in synthetic biology, where scientists attempt to program cells to perform specific biological functions.
Genetic circuits are networks of DNA elements that control how genes behave inside cells. Designing these circuits has traditionally been difficult because scientists must determine which DNA sequences will produce the desired cellular behavior. The new AI-based method helps solve this challenge by analyzing large amounts of biological data.
According to Towards Healthcare, the synthetic gene circuits market is projected to experience significant growth, with estimates suggesting the market size will increase from USD 2.06 billion in 2026 to approximately USD 1.8 billion by 2035, representing a compound annual growth rate (CAGR) of 14.55% from 2026 to 2035. This growth may support the advancement of programmable biological systems and accelerate the development of next-generation biotechnology applications.
The CLASSIC Technology
The breakthrough centers on a technique called CLASSIC, which enables researchers to test and analyze large libraries of genetic circuits inside human cells. This method allows scientists to connect specific DNA designs with the behaviors they produce in cells.
To achieve this, researchers built massive collections of DNA circuit designs and inserted them into cells. Advanced sequencing methods then mapped each design and its function, producing large datasets that AI systems could analyze to understand which circuits worked best.
Role of Artificial Intelligence
Artificial intelligence plays a key role by learning patterns from experimental data and predicting how new genetic circuits might behave. Instead of relying solely on trial-and-error laboratory testing, scientists can now use machine learning to guide circuit design.
The research team also combined long-read and short-read DNA sequencing technologies to generate detailed and accurate genetic maps. These datasets helped train AI models to predict the performance of circuits that had never been tested experimentally.
Potential Applications in Biotechnology
The ability to design genetic circuits more efficiently could transform biotechnology and medical research. Scientists may eventually program cells to detect diseases, produce therapeutic molecules, or create advanced cell-based treatments.
Researchers believe this AI-driven approach will accelerate the development of synthetic biology solutions for healthcare and other industries. By enabling large-scale testing and prediction of DNA designs, the technique could significantly speed up discoveries in gene engineering and personalized medicine.
A recent report by Towards Healthcare highlights that the synthetic gene circuits market supports technologies that enable scientists to design and engineer genetic networks capable of controlling cellular behavior. These systems allow cells to sense environmental signals, process information, and produce targeted biological responses. The report also indicates that synthetic gene circuit technology is associated with improved capabilities in areas such as therapeutic development, diagnostics, and precision medicine.