AI Treatment for Noonan Syndrome | How a Family Found Hope

A Medical Race Against Time

Delaney Holian, an eight-month-old infant from Carlsbad, faces a rare form of Noonan syndrome that traditional medicine cannot yet treat. Born after a 37-week ultrasound revealed significant health complications, she arrived with hypertrophic cardiomyopathy. This condition thickens the heart muscle, severely restricting her ability to breathe and eat. Doctors gave her a grim outlook at birth, estimating only a 20% chance of reaching her first birthday.

She defied initial predictions by surviving the first 48 hours and a subsequent six-week stay in the Neonatal Intensive Care Unit. Despite being deaf and struggling with heart function, she is an active infant who engages with her three older siblings. Her parents remain focused on extending that progress as they navigate a medical path with few precedents or existing protocols.

Moving Into Uncharted Territory

Traditional therapeutic options for Delaney have been exhausted, as no approved standard treatment addresses her specific genetic mutation. Her current condition also prevents her from qualifying for a heart transplant, leaving the family to seek unconventional help. They have turned to artificial intelligence to identify a potential solution.

This search led them to Thesis, a bioengineering firm based in Rancho Santa Fe. The company uses AI models to analyze individual genetic codes, identifying unique pathways for intervention. The technology successfully mapped Delaney's specific mutation to design a genetic therapy tailored to the needs of her heart. This application of computational biology represents a departure from traditional drug development.

Expert Collaboration and Future Prospects

Dr. Bruce Gelb, a researcher at Mount Sinai known for his work on Noonan syndrome, is currently collaborating with the family and the engineering team. He is helping assess how the AI-driven data might translate into a viable clinical treatment. While the project remains in the early stages, the model offers a clear, data-backed approach to a problem that previously lacked any specific therapeutic target.

Securing this treatment requires substantial financial resources. The family established an online fundraiser to cover the costs associated with the experimental therapy. As Delaney nears her first birthday, the focus shifts to whether the medical community can move quickly enough to validate the AI findings and begin the proposed treatment regimen. The case highlights a growing trend of families using advanced algorithms to challenge the limitations of rare disease care.