Biostate AI, ACP to develop AI models to predict MS progression
Adaptable models to address complexity of disease
Biostate AI is partnering with the nonprofit Accelerated Cure Project (ACP) to develop a series of artificial intelligence (AI) models that can predict multiple sclerosis (MS) progression and how patients may respond to treatment.
As part of the partnership, Biostate AI will use its high-throughput technology to profile RNA reads from ACP’s large collection of MS patient samples. RNA reads can be used as a measure of how active different genes are. The company will use those RNA reads to train AI models that can help personalize treatment for MS.
“Our goal is creating adaptable disease models tailored to individual patient biology, surpassing existing diagnostics,” Ashwin Gopinath, PhD, co-founder and chief technology officer of Biostate AI, said in a company press release. “MS’s complexity and variability make it an ideal candidate for our approach, and we’re eager to collaborate with ACP to develop clinically actionable tools.”
Sara Loud, CEO of ACP, said Biostate AI’s technology may transform the “understanding of MS progression and treatment response” and “unlock the full potential of our biorepository and accelerate innovations leading to better outcomes for people with MS.”
While there’s no cure for MS, a number of treatment options are available. But every patient experiences MS differently, which means each person’s treatment will be unique, too. That’s because MS can affect different parts of the brain and spinal cord, and cause a wide range of MS symptoms that can vary in severity.
Predicting MS progression could lead to personalized treatment
“Current MS management relies heavily on trial and error due to limited predictive tools,” said David Zhang, PhD, co-founder and CEO of Biostate AI.
With AI models based on each patient’s unique biology, Biostate AI expects to enable doctors to make more personalized decisions, faster and more accurately. This could lead to better outcomes and less time spent on ineffective treatments for any given patient.
“By combining high-throughput RNA sequencing with AI, we aim to equip clinicians with precise, data-driven guidance, ensuring patients receive appropriate therapy promptly,” Zhang said.
ACP’s biorepository contains blood samples from more than 1,700 MS patients across the U.S., along with detailed health and background data. Some of these blood samples were collected over time from the same individuals. This allows AI to be trained to detect patterns linked to when MS starts, worsens, or improves, and how it responds to treatment.
“At ACP, we’ve dedicated years to building a resource designed to advance breakthroughs in MS research,” said Stephanie Buxhoeveden, PhD, chief scientific officer of ACP. “By partnering with Biostate AI, we’re turning data into actionable insights that could revolutionize patient care.”
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