In addition to overcoming technical challenges, anti-aging technologies must also undergo strict regulatory procedures and face social controversies. Companies must consider all the challenges when forming their strategies. It is at the intersection of computer science and anti-aging technology that we find the future trends in anti-aging – in particular, the use of artificial intelligence (AI) to assist in drug discovery, eHealth and mHealth, and personalized approaches.
Technology challenges, regulatory hurdles, and social controversies
Like other innovative technologies, anti-aging biotechnology faces many technical hurdles on the pathway to clinical application. Like the rest of the healthcare industry, it is subject to strict FDA regulations. At the same time, life expectancy is also a critical social and political issue.
In the first edition of the Supertrends in Anti-aging dynamic report, we discussed technology challenges and the road to success for the nine hallmarks of aging, each of which faces different levels of challenges. The strategies for overcoming those challenges were also presented in the Supertrends dynamic report.
The process of obtaining FDA approval for a new drug is complicated and can take decades. This is especially true for anti-aging solutions because aging is a unique process, with death as the study endpoint. Former president of Pfizer Global Research and Development John LaMattina commented that nowhere is the challenge greater than running a clinical trial to prove a drug’s anti-aging properties.23 To be economically feasible, most of the anti-aging biotech start-ups chose age-related diseases rather than aging itself as their target conditions. A few of the drug candidates are already in phase 3 clinical studies. Other firms have decided to focus on developing age assessment kits. Clinical trials designed with age assessment rather than death as their endpoint will be much more practical and will make it possible to recruit middle-aged people as the target population for trials.
From social security and economic considerations to healthcare resources and personal life planning, it is easy to see that a life expectancy of 100 years would have a massive impact on our society at all levels. A discussion of longevity’s social implications is beyond the scope of this document. Lars Tvede, the co-founder of Supertrends, has touched on this topic in the epilogue of the Supertrends in Anti-aging dynamic report.
Future trends in the business of anti-aging
As the Supertrends co-founder, Lars Tvede, often points out, the intersection of different technologies is where innovation develops. The intersection of computer science, including AI, machine learning, data analysis, etc. and anti-aging technology is where we can find many of the major future trends in the business of anti-aging.
AI-assisted drug discovery
Discovering new, effective drugs has become much harder in the last two decades. The average cost of bringing a new drug to market was US$2.6 billion in 2013, and the average time was 12 years, with only one out of ten drug candidates making it to the market. Against this background, the use of AI as a tool for drug development has been received with a lot of enthusiasm from the pharmaceutical industry. By 2019, every major pharmaceutical company had formed a partnership with at least one AI-based drug-discovery start-up.24
Of the 150 anti-aging companies listed in our report, six have built AI-based platforms to identify potential drug candidates. In March 2021, Hong Kong-based Insilico Medicine became the first company to discover both a drug target and a molecule with its AI platform. It took Insilico only 11 months and US$2 million to get a preclinical candidate, a process could have cost more than US$400 million and taken two years using a conventional approach.25 The drug candidate that Insilico developed targeted idiopathic pulmonary fibrosis. The company hopes to target age-related diseases in the next step.
Investments in AI-based drug discovery start-ups have been red hot in the past year. In 2020, US$13.8 billion was invested in this field, more than 4.5 times the amount invested in 2019.26 Anti-aging start-ups working with AI-based platforms certainly are some of the most interesting ones.
eHealth and mHealth
eHealth and mHealth are recent terms in healthcare. They describe healthcare practices supported by electronic processes and communication. eHealth covers virtually everything related to computers and medicine. Adding mobile capabilities to eHealth gives us mHealth. In the business of anti-aging, eHealth and mHealth companies are often already engaged in commercial operations because they can offer direct-to-consumer assessments or lifestyle recommendations that do not require FDA approval.
There are three eHealth and four mHealth anti-aging companies on our list. AgeCurve, BioViva, and Centers for Age Control are three start-ups that provide services on biological age testing through biomarkers. Altoida and Neuro Track are mHealth companies that offer apps for testing, monitoring, and improving cognitive performance, which is an interesting intersection of computer science and cognitive health. Eterly and Humanity have both launched apps using digital markers, biomarkers, and genetic markers to monitor the aging process and provide lifestyle recommendations.
All seven eHealth and mHealth start-ups are at the commercial or pre-commercial stage.
Personalized approach
The personalized approach in healthcare is one of the latest trends in the medical field. Personalized solutions for longevity are made possible by the maturation of genetic sequencing technology, coupled with AI and bioinformatics tools.
The personalized approach is reflected in three of the anti-aging startups on our list. Genetic, epigenetic, and biological data were collected and analyzed to arrive at personalized medical advice or treatment. Since each of these companies has a different operational size and approach, their commercial model is not yet clear.
References
23. LaMattina J., The challenges in bringing an anti-aging pill to market. Forbes. 2019. https://www.forbes.com/sites/johnlamattina/2019/02/13/the-challenges-in-bringing-an-anti-aging-pill-to-market/?sh=5d04c19c36cf
24. LaMattina J., The challenges in bringing an anti-aging pill to market. Forbes. 2019. https://www.forbes.com/sites/johnlamattina/2019/02/13/the-challenges-in-bringing-an-anti-aging-pill-to-market/?sh=5d04c19c36cf
25. Insilico. A breakthrough milestone in AI – powered drug discovery reached. Feb 24, 2021 https://insilico.com/blog/pcc
26. Kahn J. Money is pouring into AI-assisted drug discovery, while fewer AI startups are getting VC backing. Fortune, March 3, 2021. https://fortune.com/2021/03/03/artificial-intelligence-ai-index-venture-capital-startup-funding/