Applying theoretical physics to Longevity drug discovery

Peter Fedichev’s Gero raising $10 million for anti-aging drug discovery and clinical trials.

The use of AI in Longevity drug discovery is nothing new, Insilico Medicine and Netramark are just two of the companies that spring to mind that leverage machine learning in this way. We recently spoke to a company that claims to bring a new dimension to its AI discovery platform – theoretical physics.

Singapore-based Gero is the brainchild of Peter Fedichev, one of Russia’s most renowned physicists, and has developed a platform that “combines dynamical systems theory and the physics of complex systems to build predictive models of aging for biomarkers of aging discovery.” [1]

The company recently gained worldwide media coverage for its fast work to identify several potential drug candidates for COVID-19 that could be used immediately in humans. We caught up with Gero’s co-founder Maxim Kholin to find out more about what sets the company apart.

“We not only develop descriptive, but also explanatory, models of aging and diseases,” he says. “We have added the ability to find cause and effect in big data and to discover multi-target drugs, which are key to complex diseases.”


 

“We saw that some machine learning and artificial intelligence technologies had limitations because they are mostly about correlations, whereas we focus on cause and effect.”

 


 

Having initially started out making molecular modelling software, licensing it to Big Pharma, and developing traditional drug candidates in-house, the company made a shift to focus on aging in 2015.

“We saw that some machine learning and artificial intelligence technologies had limitations because they are mostly about correlations, whereas we focus on cause and effect,” says Kholin. “In addition to advanced machine learning, we use complex dynamics systems physics, similar to what is used in weather prediction and weather modelling, where you take measurements and try to predict the state of the complex system in the future.”

Using data from UK Biobank, Gero was able to confirm that it was onto something.

“We used our approach for big and not so big, biological, medical and different omics data,” says Kholin. “And the metric worked.”


 

“With one injection we recorded a reduction in frailty index and senescence markers in peripheral blood, as well as increased senaptoplasticity and improved survival, with the effects persistent two months after the treatment.”

 


 

In addition to working with leading clinical stage pharmaceutical companies to help with their development efforts, Gero already claims a “promising pipeline” of drug candidates and compelling preclinical results in mouse studies at Brian Kennedy’s lab at the National University of Singapore (NUS).

“With one injection we recorded a reduction in frailty index and senescence markers in peripheral blood, as well as increased senaptoplasticity and improved survival, with the effects persistent two months after the treatment,” says Kholin of the NUS mouse study. “We also used the platform to predict four drugs for extending the lifespan of nematodes and all of them were able to achieve 30% extension, so it looks like the tool works. We have our own proprietary data sets – from humans to mice to nematodes – and all our previous tests were successful. So now we go to the clinic to test our hypothesis there.”

The arrival of COVID-19 has further convinced Gero that the company has made the right choice by focusing on aging.

“We made some calculations and it is not only our opinion, but also a growing opinion in the wider anti-aging community, that anti-aging drugs could be very useful to reduce mortality in the elderly due to coronavirus and other infections,” says Kholin. “So there is potentially an extra-fast regulatory pathway to clinical trials and hopefully to market – this is maybe only a once-in-a-lifetime opportunity for anti-aging drugs.”


 

“We’re currently raising about $10 million, which will support our progress into clinical trials and to get a proof of concept in humans.”

 


 

While open to collaborations to apply its AI for drug repurposing and de-novo drug discovery in variety of indications, Gero’s primary focus is now on its in-house drug development and the company is seeking funding, having already raised around $7 million for its early work.

“We’re currently raising about $10 million, which will support our progress into clinical trials and to get a proof of concept in humans,” says Kholin. “We’d like a strategic professional investor to lead the round that can help us develop the project in the best possible way, and we already have a soft commitments of about $5 million, including existing investors, successful international serial pharmaceutical and AI entrepreneurs ready to join the round.”

Assuming all goes well with the funding, Kholin is hopeful that things can get moving quickly.

“We should have the preclinical compound ready by the end of this year and hopefully will start preclinical trials at the end of this year or the beginning of next,” he says. “Unless we go directly to the clinic with something that we in-licence. We are trying to in-licence several discontinued drugs from big and mid-size pharma, which would give us several years’ advance and could go directly to clinical trial.”

[1] https://www.frontiersin.org/articles/10.3389/fgene.2018.00483/full

Image courtesy of Gero
Danny Sullivan
Contributing Editor Danny has worked in technology communications for more than 15 years, spanning Europe and North America. From bionics and lasers to software and pharmaceuticals – and everything in between – he’s covered it all. Danny has wide experience of technology publishing and technical writing and has specific interest in the transfer from idea to market.

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