NEW YORK – GATC Health and clean energy company Akon Lighting on Tuesday announced a partnership to identify predisposition to diseases in people of African heritage through artificial intelligence-driven analysis of genetic and other biological data.
Using GATC's proprietary Multiomics Advanced Technology platform, the collaborators plan to develop personalized healthcare solutions and obtain population health insights by gathering and analyzing genetic, biological, and other health information of at least 1 million people from across Africa.
Through these analyses, GATC hopes to uncover previously unknown genetic variations which, when combined with other biological and health data, may reveal the causes of some diseases and enable the development of potential new therapeutics to threat them.
The initiative will generate predictive reports on specific health risks at both the individual and population level, aimed at enabling healthcare providers to be more proactive with individual patients and at helping multiple African organizations understand where their resources might better impact public health.
Under the agreement, GATC will exclusively process genetic and other biological data, while Akon Lighting will provide localized implementation and operations, as well as manage relationships with frontline healthcare professionals.
"Having access to broad sets of health data is critical to uncovering health risks within communities and quickly developing needed medicines," Brandon Martin Sr., CEO and cofounder of Akon, said in a statement. "Our goal is to eventually collect as many as 5 million biological samples for GATC Health's analysis to help close healthcare gaps that exist for many Africans and to help develop new therapeutics that treat these diverse communities."
The firm has been expanding its offerings, which currently include predictive tests for general health and wellness, cardiac health, depression treatment, and viral immunity, among others. Tests for diabetes, PTSD, and some cancers are forthcoming.