Deep Pharma Intelligence AI in Pharma Market Webinar Summary

- Kate Batz, Managing Partner, Deep Knowledge Group

On March 2 and 3, 2021, I had the pleasure of hosting one of two virtual events focused on key market trends, events, and investor takeaways in the AI in Pharma sector alongside my co-host, Franco Cortese (Director of Aging Analytics Agency), where we were joined by a number of industry experts to present and discuss the increasing market maturation of the AI in Pharma space, from both a collaboration and partnership perspective, as well as an investment, deal-flow, M&A and IPO point of view.

The events were organized by Deep Pharma Intelligence, a leading provider of open source and proprietary analytics in the Pharmaceutical and AI in Pharma industry, and a new joint venture formed between Deep Knowledge Group’s DeepTech-focused analytical subsidiary, Deep Knowledge Analytics, and Biopharma Trend.

Day 1 (Top AI in Pharma Deals, Trends & Partnerships 2020-Q1 2021) featured presentations and a roundtable discussion on the biggest deals, partnerships, collaborations, and industry events in the AI in Pharma sector from 2020 - 2021.

Day 2 (Investment and M&A Deals: AI in Pharma Market 2021) featured talks and a panel discussion on key players, trends in the private equity and venture capital ecosystem, focusing on the increasing market maturation of AI in Pharma, and key take-aways for investors in 2021.

Key Take-Aways & Conclusions From the Events

While global pandemics appeared to be a hard blow for the majority of economic sectors, the BioTech market saw industry developments and investments actually rise as a result — not only reaching record-breaking values for the BioTech stock index, but also showing extraordinary deal-making activity in the areas of venture capital investment and initial public offerings (IPOs).
The rising trends was also observed for the sector of pharmaceutical artificial intelligence (AI) — a rapidly expanding sector involving large corporations, AI-driven biotechs, and investment bodies specifically focused on data-driven drug discovery startups.
It is very clear that the AI in Pharma sector is heating up, and is approaching a period of market maturation and consolidation, where a number of AI-startups have achieved substantial leadership and grew in resources and technology, while others have lagged behind, being forced to focus on niche service-oriented segments of drug discovery. Several AI startups also went out of business, and others were acquired.
The total amount of VC funding in AI-biotech startups increased in 2020 by around 23%, compared to 2019, approaching a total of $1.9B, which is also more than in 2015, 2016, and 2017 combined.
Meanwhile, we are seeing an increasing number of late-stage mega-rounds (e.g. B, C, Pre-IPO), including hundreds of millions, which reflects the increasing quality of players in this market, with strong business models, outstanding deal-making traction, and cutting-edge research.
The market capitalization growth dynamics in the sector of AI-driven corporations significantly outperforms the global market (represented as S&P 500 index), as well as aggregate biotech industry indices (IBB and NBI). At the same time, the segment of AI-driven pharma companies is more volatile compared to the industry average.
After a paradoxically bullish year for the biotech industry, the market may see possible correction over the first half of 2021. However, the sector of pharmaceutical AI will likely outperform the general market and will continue its growth trajectory.
This is explained by a systemic nature of value AI is bringing to the table — every large pharma organization is now prioritizing this technology as a strategic component in their model of innovation, driving the overall sector growth, further increase in the number of transactions and R&D collaborations, and an approaching wave of merger & acquisitions. This also stimulates investors to continue being bullish about allocating capital for AI-driven biotechs.
However, as the market moves towards consolidation, it is clear that its overall continued positive trajectory and stability require proportionate innovations in terms of AI, data-driven approaches to industry analytics, and InvestTech.