AI-powered computer model may predict disease progression during aging: Study

Buffalo : A team of researchers from the University of Buffalo have developed a novel system that models the progression of chronic diseases as patients’ age with the use of artificial intelligence.
The study has been published in the ‘Journal of Pharmacokinetics and Pharmacodynamics’.
The model assessed metabolic and cardiovascular biomarkers – measurable biological processes such as cholesterol levels, body mass index, glucose and blood pressure – to calculate health status and disease risks across a patient’s lifespan.
The findings are critical due to the increased risk of developing metabolic and cardiovascular diseases with ageing, a process that has adverse effects on cellular, psychological and behavioural processes.
“There is an unmet need for scalable approaches that can provide guidance for pharmaceutical care across the lifespan in the presence of ageing and chronic co-morbidities,” said lead author Murali Ramanathan, PhD, professor of pharmaceutical sciences in the UB School of Pharmacy and Pharmaceutical Sciences.
“This knowledge gap may be potentially bridged by innovative disease progression modelling,” he added.