Predicting the future is very challenging, especially in the field of healthcare. By collating and studying current trends in research, markets, start-up ecosystems, and the investment landscape, we can arrive at the most likely future scenarios. With the assistance of the Supertrends app, we have created a future map of the anti-aging business. The most critical elements of this map are the right timing and the right companies.
The right timing
Below is a future timeline of the anti-aging industry that we created using the Supertrends app.
Our timeline revealed two critical periods when we can expect increased activities in the anti-aging business.
2021-2023: New therapies enter clinical trials
AI-assisted drug discovery can greatly benefit and shorten the period of pre-clinical trials. Given the rapid developments at this intersection, we expect that more drug candidates targeting aging or age-related diseases will enter the pipeline. Insilico’s preclinical drug candidate, which took 11 months to develop, is just one of the examples.
Keeping in mind that the journey from phase I clinical trials to receiving FDA approval takes eight years on average,26 successful drug candidates are expected to reach the market around 2030.
2024-2026: New therapies targeting age-related diseases enter the market
Aging is not yet classified as a disease by the WHO. In order to gain early commercial profit, anti-aging companies often set age-related diseases rather than aging itself as their therapy goals. Some of the companies have already reached stage-2 or stage-3 clinical trials. If these are successful, we can expect the first group of therapies to receive approval from regulators in about five years. Therapies treating age-related hearing loss, sarcopenia (muscle loss due to age), osteoarthritis, etc. could be among this first group.
At the same period, we can also expect an effective assessment toolkit to be developed for aging evaluation. That means that clinical trials targeting aging don’t have to use death as an endpoint, which can shorten the trial period remarkably.
The right companies
Based on the technology and research stages, we have some recommendations on the right type of companies for short-, mid-, and long-term investment.
Companies for short-term investment
As we discussed previously, the intersection of computer science and anti-aging biotechnology is where some of the most prominent future trends are located. AI-assisted drug discovery and eHealth and mHealth companies are among the companies to consider for short-term investment. However, caution is advised, since the value of a particular company may already be inflated. In the following, we list some of the active companies in these fields. A complete company list can be found on our database.
Examples of active players in the field of AI-assisted drug discovery:
- BioAge Labs
- Fountain Therapeutics
- Insilico Medicine
- Spring Discovery
- Rubedo Life Sciences
Examples of active players in the field of eHealth and mHealth:
- Altoida
- Neuro Track
Companies for mid- and long-term investment
For middle-term investment, we recommend companies testing drug candidates in phase 2 or 3 clinical trials. Most of the companies testing drug candidates in phase 1 clinical trials or at the pre-clinical stage are still at the stage of attracting seed financing and as such are candidates for long-term investment.
One should keep in mind that the success rate for pre-clinical and clinical trials varies according to different phases, with the pre-clinical phase showing the lowest success rate.27 Naturally, companies at an earlier stage have a higher risk of failure. The success rate from phase 1 to approval varies from indication to indication and from year to year. The overall success rate from 2000 to 2015 was reported to be 13.8 percent. Studies also found that using biomarkers in patient selection has a higher success rate. Companies using a personalized approach in anti-aging drug development are more likely to see success.28
Source for the two figures above: Chi Heem Wong, Kien Wei Siah, Andrew W Lo, Estimation of clinical trial success rates and related parameters, Biostatistics, Volume 20, Issue 2, April 2019, Pages 273–286, doi: 10.1093/biostatistics/kxx069
Supertrends conclusion
In an age when anti-aging medicine could well revolutionize the healthcare system, some of us may be fortunate enough to witness and even benefit from the breakthroughs in anti-aging technology. For many people, financial profit is not the only reason for seeking business opportunities in anti-aging. Access to the latest anti-aging interventions and the opportunity to contribute to the advancement of humankind in general are also important incentives.
Our knowledge of aging is growing rapidly. AI, machine learning, data analysis, and genetic sequencing technology will be some of the biggest powerhouses in driving anti-aging technology. Companies using these technologies in drug discovery and patient selection could see rapid value growth. Although we may still be a decade away from the approval of drugs that directly target aging, we are already witnessing the launch of several eHealth and mHealth companies providing diagnostic services on both physical aging and mental aging. We will also start to see therapies using one of the hallmarks of aging to target age-related diseases in a few years.
By combining the right timing and right candidates, you can make the best sense of this once-in-a-lifetime business opportunity.
Click to view the Supertrends anti-aging company database
References
27. MedicineNet. Drug approvals – from intention to market. Accessed on April 30, 2021, https://www.medicinenet.com/script/main/art.asp?articlekey=9877
28. Takebe T, Imai R, Ono S. The Current Status of Drug Discovery and Development as Originated in United States Academia: The Influence of Industrial and Academic Collaboration on Drug Discovery and Development. Clin Transl Sci. 2018;11(6):597-606. doi:10.1111/cts.12577
29. Chi H. W., Kien W. S., Andrew W Lo, Estimation of clinical trial success rates and related parameters, Biostatistics, Volume 20, Issue 2, April 2019, Pages 273–286, doi: 10.1093/biostatistics/kxx069