AI platform designed to monitor, predict ALS progression

After being challenged by an ALS group to study the disease closer by using data, a machine learning researcher has developed an AI platform designed to monitor and predict the progression of neurodegenerative diseases.

The new platform will initially focus on ALS and could help find the most effective treatments for specific ALS patient subgroups and in turn improve drug development processes, success rates of clinical trials and patient quality of life.

The technology was developed by Boaz Lerner, PhD, a machine learning professor in the Department of Industrial Engineering and Management at Ben-Gurion University, who was challenged four years ago by non-profit ALS group Prize4Life to use clinical data and study the disease closer. His drive to develop the technology was also inspired by a desire to advance disease understanding, improve the quality of life for patients and their families, promote disease treatment and advocate for personalized medicine for ALS patients.

“I’ve always been interested in advancing disease understanding and promote disease treatment. The decision to focus on neurodegenerative diseases was by pure chance once I was challenged by Prize4Life to explore ALS from data,” Lerner told AI in Healthcare. “(Since) then, I’ve recognized that the developed platform is generic and can advance research and patient treatment for other neurodegenerative disease as well.”

The platform is based on machine learning algorithms and uses retrospective clinical data of patients to stratify heterogeneous ALS populations into smaller homogenous subgroups to predict disease progression rates and patterns for the specific subgroups, Lerner explained. By finding markers for specific subgroups, the university hopes the platform can lead to better drug development, more successful clinical trials and improved patient quality of life.

“The platform would be a valuable tool for physicians because it will enable them to know where to begin specific treatment, whether and when to focus, e.g., on the respiratory system or physiotherapy…(and) for patients and caregivers because it allows prediction of disease state and progression rate that reduce uncertainty and improve life quality,” Lerner said. “If we can predict, for example, that the patient’s walking or speech ability will deteriorate in six months, he or she can organize the home to address their needs or move to a more appropriate environment, or start looking for a specific device to communicate with people.”

The university recently received funding from the Israel Innovation Authority to help researchers widely implement the platform on various applications, according to the press release. It’s also looking for industry partners to further develop and commercialize the “patent-pending technology.”

“AI is revolutionizing healthcare already now, as more clinical data is available to be analyzed by more powerful AI algorithms developed using higher computational resources available,” Lerner said. “As each of these ingredients keeps growing, the impact of AI in healthcare will only increase with time.”