40% of Global AI Companies Focus on Early Drug Development while AI-Powered Startups Reshape the Future of Drug Discovery

August 16, 2023 - London, UK: The largest profiling of the global AI in the Drug Discovery industry made to date has been released in the form of an interactive industry report by Deep Pharma Intelligence, a leading BioTech market research agency.  

The report, presented within a new AI in Drug Discovery platform, provides an in-depth overview of the current industry landscape with interactive profiles of over 800 AI companies, 1900 investors, 90 corporations, and 50 hubs.

Key findings report that out of the 800+ AI-focused companies in the Drug Discovery sector, 91 were established between the years 2022 and 2023. These companies are all startups that leverage AI technology. Moreover, there is an increasing tendency for new collaborations to emerge, both between Big Pharma companies, as well as with new startups with new technologies.

Introducing a new drug has become a marathon, taking over a decade and costing at least $2.6 billion on average and by some recent estimations can reach up to an astounding $6 billion. As the pharmaceutical industry grapples with rising costs and diminishing returns, AI emerges as the potential solution. Between 2014 and 2023, investment in AI-driven pharma skyrocketed, reaching a cumulative $60.3 billion, a testimony to AI's transformative potential.

The dominance of the AI companies that are focused on Early Drug Development has reached almost 40% of all AI companies, making it the dominant field and one of the most trusted from the point of investments. There are several reasons for this, such as a stage with intensive and massive data-dependance, virtual screening implementation, need for iterative learning and dependance on target identification and validation.

Andrey Savitskiy, the Head of Analytics for Deep Pharma Intelligence who led the curation of the report, said:

“AI is no longer a novel, experimental concept. In reality AI-driven approaches are compressing timelines dramatically at a pace which was once inconceivable; companies are rapidly advancing candidates from preclinical stages to human clinical trials, and even to regulatory compliance stages.

We are also seeing a surge of strategic collaborations between Big Pharma and AI-focused companies, nearing 300 significant partnerships today.  These are strategic and diverse alliances ranging from early drug development—where we see AI’s prowess in data-rich target identification and validation—to clinical trial designs and patient monitoring, where AI is enhancing precision and efficiency

This evolves beyond a technological shift, it is conceptual shift, marking the dawn of a smarter, more agile future for pharmaceuticals, underpinned by the power of AI”

The report and platform delve deep into the evolving landscape, highlighting principal players, trends, and technologies, and revealing key insights and major take-aways for industry participants, stakeholders and decision makers.

It also features an interactive database of the Top 100 AI in Drug Discovery Experts, with information-rich profiles on the leading researchers, scientists, entrepreneurs and technologists committed to harnessing the potential of AI to tackle the complex challenges of drug discovery advancement. 

The platform is further complemented by a Big Data Analytics System and Dashboard for professional users seeking deeper, more specific and customized insights. The system itself provides sophisticated analytical and market intelligence capabilities, as well as automated SWOT analysis and AI-driven smart-matching tools.

Alongside major project release, Deep Pharma Intelligence has also launched a region specificreport focused on the AI in Drug Discovery Industry in Asia, with interactive, filterable and searchable industry profiles, mindmaps and databases of 130 companies, 350 investors, 25 hubs and 30 industry experts, professionals and leaders driving AI pharma innovation in Asia.

Further platform iterations and analytical reports launches are expected in the coming weeks, including AI in Cancer Vaccines, AI applications in Diabetes and FemTech, and AI in Oncology, aiming to highlight groundbreaking solutions, therapies, players and major trends in these areas. 

View the platform here: www.deep-pharma.tech/ai-platform 

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Key Messages: 

• New interactive report and platform presents the most comprehensive overview of the current state of AI in Drug Discovery made to date, highlighting principal players, trends, and technologies
• Features an extensive industry database with interactive search and filtering capabilities, including profiles of 800+ AI Drug Discovery companies, 1900 investors, 100 corporations, 50 hubs, and the top 100 industry experts
• Almost 40% of all AI companies are specialised in Early Drug Development, making it the dominant field and one of the trusted from the point of investments
• Out of the 800+ AI-focused companies in the Drug Discovery sector, 91 were established between the years 2022 and 2023

For enquiries and further details (including early access to the aforementioned upcoming reports) please contact: info@deep-pharma.tech ; roxy@dkv.global

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About Deep Pharma Intelligence:

Deep Pharma Intelligence (DPI) is a BioTech market intelligence agency with a core specialization in AI in Pharma. As the flagship analytical subsidiary of Deep Knowledge Group, it is using powerful data mining and advanced visualisation features combined with AI-driven tools, and is focused on sophisticated analytics, benchmarking and forecasting of emerging and frontier domains in the Pharmaceutical, BioTech and Healthcare industries.

About Deep Knowledge Group

Deep Knowledge Group is a data-driven consortium of commercial and non-profit organizations active on many fronts in the realm of DeepTech and Frontier Technologies (AI, Longevity, BioTech, Pharma, FinTech, GovTech, SpaceTech, FemTech, Data Science, InvestTech), ranging from scientific research to investment, entrepreneurship, analytics, consulting, media, philanthropy and more.