In an article for the newspaper Asharq Al-Awsat, Dr. Alex Zhavoronkov argues that artificial intelligence is opening new horizons in longevity research, providing tools to precisely identify potential interventions and assess their effects on the human body.
According to the author, recent publications by his team in the journals Cell and Nature Biotechnology demonstrate how AI helps identify drug targets in the biology of aging and integrate "aging measurements" from blood tests into clinical trials of drugs created with the help of algorithms.
Zhavoronkov emphasizes: although it cannot be claimed that a specific drug will already extend anyone's life, this work points to a promising future for drug development, in which AI identifies candidates while their effects on aging processes and on target diseases are studied in parallel.
Artificial intelligence, the expert notes, significantly expands the range of what scientists can discover and measure, yet rigorous laboratory and clinical experiments, which confirm real health benefits, still play the decisive role.
The author distinguishes between two rhythms of drug discovery: the fast computational one, in which AI analyzes data, generates structures and proposes experiments, and the slow biological one, which requires synthesizing molecules, verifying delivery to tissues, assessing safety and conducting studies in humans.
As an example, Zhavoronkov cites the drug rentosertib, developed for idiopathic pulmonary fibrosis: AI helped find the biological target and create the molecule, and within just 18 months a preclinical candidate was obtained — a notable step forward compared with traditional timelines.
In conclusion, the expert formulates an ambition: in his view, AI may ultimately help double average human lifespan, although today this remains a goal rather than a proven forecast; the current opportunity is to create more effective drugs and the infrastructure to test them.
