XtalPi has outlined how Kodexia, its closed-loop platform, combines generative AI, biological modeling and automated experiments to accelerate the discovery of small interfering RNA therapies.

In an Oct. 6 announcement, the company highlighted six proprietary preclinical programs spanning metabolic, renal, respiratory and central nervous system diseases. More than half have completed animal efficacy testing, according to XtalPi. For pharmaceutical R&D teams, the potential benefit is a connected workflow in which experimental results inform the next round of AI-generated designs.

siRNA drugs work by silencing disease-driving genes before they produce proteins, potentially opening paths to targets that are difficult to address with conventional drugs. But designing effective sequences, selecting chemical modifications, proving activity in animals and delivering the molecules outside the liver remain major development challenges.

How Kodexia works

At the center of Kodexia is XtalPi’s proprietary siFormer architecture, which combines RNA interference biology with nucleic acid chemistry. The system uses factors such as RNA thermodynamics, strand loading, target accessibility and silencing efficiency when generating candidate molecules.

That matters because siRNA discovery is not simply a matter of finding a sequence that works in a laboratory test. A promising design must also survive the jump into an animal, maintain activity, avoid unwanted effects and potentially clear intellectual property hurdles.