Feb 27 2019
Scientists at the Ben-Gurion University of the Negev have created an innovative, artificial intelligence (AI)-based software to supervise and predict the development of neurodegenerative diseases. Prof. Boaz Lerner of the BGU Department of Industrial Engineering and Management and his team developed the platform.
Prof. Boaz Lerner. (Image credit: Ben-Gurion University of the Negev)
The objective is to identify markers in diseases like amyotrophic lateral sclerosis (ALS), also called Lou Gehrig’s disease, and other neurodegenerative diseases like Alzheimer’s and Parkinson’s, to help advance personalized patient care and enhance drug development.
ALS, a motor neuron disease, results in the death of neurons that control voluntary muscles, and as time passes, it develops almost consistently. It affects everyone regardless of their race and social class. According to the 2016 estimation by the Centers for Disease Control and Prevention, around 14,000–15,000 Americans suffer from ALS.
One of the big challenges of designing and managing clinical trials for ALS stems from the fact that not only is it a rare disease, but also the ALS population is very heterogeneous.
Prof. Boaz Lerner, Department of Industrial Engineering and Management, BGU.
This makes it challenging to recognize common markers and to customize specific treatments to all patients.
For example, a certain treatment could suit some patients, while it may lead to side effects for patients of other groups. Similarly, another treatment will suit only another group of patients.
Prof. Boaz Lerner, Department of Industrial Engineering and Management, BGU.
The platform analyzes demographic data, for example, age and sex, along with clinical data, such as vital signs (blood pressure and the location where the disease originated in the body), and lab test results. Factors are identified using data mining and machine learning algorithms, enabling the software to develop models that can estimate the pattern and rate of ALS progression.
The new software has the potential to classify the ALS patient population into “small homogeneous sub-groups of patients that are similar to each other in some aspect. This can help tailor a personalized treatment as well as design and manage clinical trials for patients of a specific homogeneous sub-group,” states Prof. Lerner.
The initial focus of technology will be on ALS, and eventually, it will be adapted to several other neurodegenerative diseases. BGN Technologies has applied for a patent for the technology.