CAMBRIDGE, Mass. — Ono Pharmaceutical Co., Ltd. has entered into a drug discovery partnership with Aitia, Inc. aimed at identifying new therapeutic targets and biomarkers for neurological diseases using causal artificial intelligence and digital twin technology.
Under the agreement, Aitia will use its REFS technology to develop Gemini Digital Twins, or GDTs, for neurological diseases. The virtual patient models are designed to reflect characteristics of real patients and help identify causal relationships associated with disease.
Ono will receive an exclusive worldwide option to research, develop and commercialize drug candidates directed at targets identified through the partnership.
The companies said the approach could be particularly useful in neurological diseases, where disease mechanisms can involve complex interactions among genetic, developmental, neural, immune and environmental factors.
“Ono has long been committed to creating innovative medicines for diseases with high unmet medical needs, including neurological diseases,” said Seishi Katsumata, Corporate Officer and Executive Vice President of Discovery & Research at Ono. “Through this collaboration, we are delighted to leverage cutting-edge REFS technology to identify true therapeutic targets in neurological diseases, where disease mechanisms are complex and not yet fully understood.”
Katsumata said the company believes the collaboration could accelerate the development of new medicines and support expansion of Ono’s neurology research pipeline.
Aitia said its REFS platform uses causal AI to go beyond conventional correlation-based approaches by attempting to infer relationships between biological factors and disease outcomes.
“We are honored to partner with Ono, a company with a strong track record in the neurology field,” said Colin Hill, CEO and co-founder of Aitia. “By utilizing our state-of-the-art causal AI-powered REFS technology, we are confident that we can build Gemini Digital Twins that uncover true disease mechanisms and therapeutic targets that could not be identified with conventional AI, thereby accelerating the development of new therapies.”
