Hyderabad: Kristen Fortney has been studying the genetics of supercentenarians (people who live to the age of 110 and beyond) at Stanford University with the help of bioinformatics. As the CEO and co-founder of BioAge, a clinical-stage biotech developing a pipeline of treatments to extend healthy lifespans by targeting molecular causes of ageing, Fortney is at the forefront of biotech efforts to turn longevity science knowledge into medicine.
This biological research has attracted some of the biggest minds and deepest pockets, according to Fortney. Wealthy people have been directing their resources to opportunities where they can make a positive impact on human health, said Fortney to CNBC, citing examples of the Chan-Zuckerberg Initiative, the Broad Institute and several other philanthropic efforts devoted to cancer research. To address a large number of people through medical innovation, and delay the incidence of multiple diseases at once, ageing biology might be a good place to start, and longevity science has enough resources to convert knowledge into therapy, according to Fortney.
The primary cause of many chronic diseases, devastating illnesses like cancers and Alzheimer's is attributed to ageing, but science has reached a stage where we can do something about it. Researchers have discovered multiple successful interventions in animal models that prove that healthspan can be extended. Fortney says that technological advancements and targeting ageing to treat diseases have attracted a lot of people's interest in the sector.
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Taking the "human data first" approach, BioAge understands ageing and the underlying mechanisms of healthy longevity of humans ageing well. The use of AI and Machine Learning (ML) in analyzing the distinctive molecular features of different people living the healthiest and longest lives to gather knowledge and develop therapies can help everyone age better. Modern technology helps in getting a comprehensive molecular picture of ageing and different ageing mechanisms.
AI and ML are the key technologies enabling researchers to pinpoint molecular differences that predict healthy and unhealthy ageing. Samples and detailed records of thousands of people are collected from various biobanks around the world. These samples are analyzed using modern technologies to measure proteins, RNAs and metabolites. AI is used to sift through the huge resultant data, to identify biological pathways and molecular factors underlying healthy longevity. The proteins that distinguish the most successful agers become the drug targets.
These targets will help combat diseases driven by ageing. Discovering and activating various pathways in certain ways results in a healthier person. Therefore, drugs aimed at these specific mechanisms might cure, slow down or prevent certain diseases. Researchers are using self-made biomarkers via machine learning to learn as much as possible about ageing through clinical trials.
Cognitive decline or decline in brain functions is also a universal aspect of the ageing process which ranges from mild memory impairment to severe diseases like Alzheimer's. ML helps in analyzing multiple pathways that are important in brain ageing and targeting these pathways could some aspects of brain ageing and treat or even prevent age-related neurological diseases.
