Deep Pharma Intelligence AI in Pharma Market Webinar Summary

Franco Cortese gave a talk that summarized key take-aways from Aging Analytics Agency’s recently released Longevity Investment Digest and Longevity Investment Big Data Analytics Dashboard. 

Longevity Investment Digest Key Take-Aways

• In 2020 the total volume of investments into Longevity focused or related companies globally had crossed the $156 billion mark, of which $60B were raised during the last year alone.

• Overall, Longevity-focused and related companies saw 30% growth in investments compared to the previous year, with the total funding for the top-8 most funded such companies exceeding $500 million by the end of 2020. 

• These developments are also crossing over into the public equities and retail investment space as well, with an increasing number of Longevity-related companies going public, with the US still dominating the public markets, but with UK and Asia-based public companies growing quickly.

• And, in addition to an increasing number of Longevity focused or related companies going public, we are also seeing an increasing number of already publicly traded Longevity-related companies seeing their market caps increase year over year as well. 

• Despite the Covid-19 pandemic, all new public companies in this space announced successful closing of the IPO. They show volatile but steady growth, although net income of all corporations remains negative. Most IPOs took place in the USA in the second half. 

• All companies have beta smaller than 1 (although positive) which means that longevity stock prices move in accordance with general market movements, yet the degree of these movements is lower (although volatility as measured by standard deviation can be relatively high).

• Aging Analytics Agency’s Longevity stock index includes more than 300 longevity-related corporations operating in biotech and IT sectors. Longevity corporations market capitalization growth strongly outperforms the market as a whole (represented as S&P500 index), as well as general biotech industry indices (IBB and NBI), although longevity stock market segment is more volatile compared to them (as measured by standard deviation). 

• Interestingly, the distribution of returns of the longevity stock market segment is right-skewed, which differentiates it from the vast majority of stock indices and segments. It means that rare, extraordinary positive events play a large role in the dynamics of the market capitalization of the segment, which can be described as the presence of “anti-black swans”. Many other indices are, on the contrary, characterized by negative skewness, which means that extraordinary negative events are more likely. 

Longevity Investment Dashboard Key Take-Aways

• Aging Analytics Agency’s Longevity Investment Big Data Analytics Dashboard serves as an analogue to Deep Pharma Intelligence’s Big Data Analytical Dashboard, focused on the global Longevity industry, and including 20k companies and 9k investors. 

• These systems were first applied to the AI in Pharma sector, which has a lower number of players and a lower degree of cross-technology and cross-domain intersectionality than Longevity (although still a very high degree of these features compared to most other industries).

• Following its validation there, Deep Knowledge Group retuned and reapplied it to the much larger Global Longevity Industry, with quite positive results. 

• The dashboard itself uses almost 5 million individual data points split across 20,000 companies, 9,000 investors, 14 sectors and 140 subsectors in order to facilitate targeted and tunable comparative analytics, entity and technology benchmarking, competitor prediction and smart-matching, advanced data visualization and other features within the full scope of the Global Longevity Industry. 

• The official roll-out of the dashboard beta is scheduled for Q2 2021, but interested viewers can already view the dashboard alpha now at www.aginganalytics.com/longevity-investment-dashboard, and explore some of its current features, which include an AI-driven company and investor smart-matching and competitor prediction engine, automated and semi-automated company SWOT analysis, machine-learning based database exploration and financial indicator prediction, as well as stock market analytics and forecasting, among others.