'I see the type of intervention they're working on as more powerful of an influence on global health and global economies than the discovery of antibiotics in the mid-20th century or the dissemination of vaccines beginning in the 1960s.”
“To those of us in public health that have a deep sense of history and how medical and public health breakthroughs in the past have influenced human longevity, we see this line of research as the next big thing. It should be evident that the field is gaining traction rapidly since both government and outside funding sources are dramatically ramping up their interest and investment,” Olshansky said.
The work that Alex and his colleagues are doing, along with the rest of the research community in aging biology, is on a forefront of the next great revolution in public health,” Olshansky continued. “Once they succeed, they will have created a mechanism that will yield more years of healthy life than just about any previous intervention in the history of public health. I see this new intervention as the next form of Primary Prevention with a capital P.
But there is still a lot of work to be done and old habits to overcome. And although the research looks promising, it is still a proof of concept. Drugs designed using AI have not been created yet, let alone sold to patients. The company plans to continue working on its drug discovery engine, to develop even better AI that can learn from very little data, and “imagine” new molecules or synthetic human data without any new training sets by developing the conceptual understanding of what a molecule with the desired properties looks like. It also plans to develop joint ventures with a number of companies specializing in specific diseases.
Insilico supports a network of biotechnology, pharmaceutical companies and academic institutions. Since its inception in 2014, the company has published or co-published over 70 papers in peer-reviewed journals and AI conferences. In its latest research paper published in, Insilico demonstrated animal validation of new molecules generated using the deep generative tensorial reinforcement learning models in human cells and in animals.
In 2013, Zhavoronkov published “The Ageless Generation,” a book in which he postulated that in order to prevent the coming global financial catastrophe, scientists and companies worldwide must unite to increase productive longevity of the US population.
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