For much of human history, the discovery and development of new health drugs has been a long and frustrating process, involving years, if not decades, of complex research and countless cycles of trial and error. Today paints a very different picture, with artificial intelligence (AI) - that all encompassing buzzword - completely transforming the industry and taking humanity to the brink of eradicating diseases that have existed for millenia.
Until recently, AI’s potential to cure seemingly incurable diseases was a distant goal. But, in 2016, when Google’s DeepMind unveiled its AlphaFold program to understand how proteins function and interact with other molecules, the dream to develop new drugs faster and more efficiently than ever before was brought into the present.
Inspired by the above, a new generation of companies are developing similar solutions; trained to find patterns that can discover relationships within data that have implications for human health. A surge of investment and hundreds of global partnerships have arisen to explore this field with the aim to unlock billions of dollars in value and advance the bounds of human health.
Written by: Marcus McGrigor
Market Dynamics in AI-Driven Drug Discovery
The global market for AI in drug discovery was $1.5Bn in 2023 and is predicted to hit $9.1Bn by 2030, showcasing a significant upward trajectory. Officially, CAGR stands at 29.7% from 2024 to 2030, according to recent research. The broader drug discovery market is much larger, standing at $65.8Bn in 2024, anticipated to reach $158.7Bn by 2034, with a CAGR of 9.20% over the same time period.
Source: Grand View Research - Artificial Intelligence In Drug Discovery
This growth stems from rising demand for AI-driven solutions in drug discovery, fueled by the need for novel therapies, expanded manufacturing capacities in life sciences, and rapid technological advancements. In order to match demand, start-ups need funding, and with the opportunity as large as it is, investors and pharmaceutical powerhouses have lept at the chance to be involved.
Big Pharma incumbents, biotech companies and VC’s are driving growth in the sector, betting big on start-ups building new technologies in AI-powered drug discovery. The likes of Bayer and Roche have ramped up their deal-making activities in 2024 and the investors behind Moderna have raised $3.6Bn to launch an array of ventures using AI to innovate the pharmaceutical industry. Deloitte estimated that the top 20 pharma companies had increased their total R&D spending by 4.5% in 2023, reaching $145.5Bn.
The COVID-19 pandemic significantly accelerated the adoption of and investment in AI for drug discovery. AI technologies were crucial in expediting the development of treatments, notably vaccines, highlighting their potential in rapidly identifying therapeutic candidates and optimising clinical trials. As a result, investment into AI for drug discovery has increased a huge deal.
VCs are also drawn to AI-driven drug discovery for its scalability and potential to generate high returns (alongside the major societal impact that faster, more effective drug development engenders). However, with the increased pressure of ‘asset lifecycle compression’ in the industry, companies have less time to capture a new drug’s value in the market—now down to 9.8 years from 11.7 years two decades ago. This shrinking time frame underscores the need for organisations to innovate and act quickly to maintain a competitive edge, intensifying investor interest in AI’s ability to accelerate development and maximise returns within this shorter window.
Funding for drug discovery startups in Europe peaked in 2021 when the sector soaked up $2.7Bn, both during and after the pandemic. However, this was not an isolated incident, with venture funding across the board experiencing a record breaking rise in capital deployment. Biotech startups have raised $0.9Bn in funding this year, putting them on track to exceed last year's $1.3Bn total. Additionally, the average deal size for Series A-C rounds has increased, signalling growing investor confidence in the sector.
In 2024, valuations of biotech startups leveraging AI have begun to stabilise following an initial surge post-pandemic. While AI remains a promising tool for accelerating drug discovery, high-profile challenges and unfulfilled expectations are prompting a realignment of valuations to reflect the complex realities of biotechnology.
Regionally, North America dominates, holding a market share of 57.7% in 2023, driven by significant investment in healthcare technology and strong collaborations between pharmaceutical companies and tech giants. The U.S. market is characterised by a high level of M&A activity, with companies seeking to integrate AI capabilities to gain a competitive edge in drug development.
Source: Grand View Research - Artificial Intelligence In Drug Discovery
Both Asia-Pacific and Europe are expected to see significant market growth, led by larger economies in Germany, the UK and China. The UK specifically, is home to numerous AI-driven initiatives aimed at revolutionising drug discovery. Government support, such as the Industrial Strategy Challenge Fund and the UKRI Challenge Fund, and collaboration between industry and academia are key factors driving the adoption of AI technologies in the UK.
Opportunities in AI-Driven Drug Discovery
To better understand this market, we should attempt to know what the technology actually is and how it is making a difference. The most common and promising applications of AI in drug development are as follows:
Accelerated drug discovery: AI can help identify new drug targets, design novel molecules, and predict their properties, leading to faster and more efficient drug discovery processes.
Enhanced clinical trials: AI can optimise patient recruitment, analyse clinical trial data more effectively, and predict patient outcomes, leading to more efficient and successful clinical trials.
Improved regulatory approvals: AI can help streamline regulatory processes by automating data analysis and generating comprehensive reports, leading to faster regulatory approvals.
Personalised medicine: AI can analyse patient data to identify personalised treatment plans, leading to more effective and targeted therapies.
Drug repurposing: AI can identify new uses for existing drugs, leading to faster and more cost-effective drug development.
Source: McKinsey
AI is enhancing efficiency across almost every stage of new drug development, from preclinical research to clinical trials. It is reducing failure rates and bringing down previously high costs through improved accuracy and faster decision-making. For example, AI could yield time and cost savings of between 25% and 50% in the preclinical stage of drug development. This presents a huge opportunity for investors who back companies building such tools.
Challenges and Risks of AI in Drug Discovery
The path to profitability and success in new drug discovery through AI is anything but straightforward, presenting major challenges at almost every step.
While AI holds immense promise, it is not yet the silver bullet many hope it will be—especially in the complex field of healthcare and drug development. Beyond computational prowess, this arena demands careful moral, legal, and regulatory oversight, given the sensitivity of patient data and the high stakes of medical innovation.
Despite advances, drug development pipelines remain slow and prohibitively costly, with few AI-enhanced candidates making it to market. The journey from identifying meaningful biological mechanisms to selecting druggable targets, developing candidate molecules, and navigating preclinical and clinical trials remains intricate and vulnerable to setbacks.
Data privacy also poses a serious concern as patient data is increasingly essential to AI-driven discoveries, demanding strict safeguards to protect confidentiality. Each hypothesis generated by AI must undergo rigorous validation against real-world data—an often time-consuming and regulated process that requires balancing ethical considerations with the urgency to deliver safe, effective drugs.
As discussed in Mustafa Suleyman’s The Coming Wave, regulations act as a form of “containment,” guiding the development of transformative technologies like AI along a “narrow path” that maximises benefits while minimising risks to society. Though regulatory compliance can be challenging, these standards are essential for gaining approval, safeguarding public trust, and ensuring that AI-driven drug discovery is both effective and responsible.
Startups and Players to Watch in AI-Driven Drug Discovery
Moving on, there are several start-ups leading the way in this new era of drug discovery through AI application:
BenchSci (Toronto, Canada)
Launched in 2017 with its AI-Assisted Antibody Selection application, BenchSci leverages a database of 19m scientific publications to enhance disease biology research. Its ASCEND platform has enabled customers to identify novel drug targets in 22% of projects and cut unnecessary experimentation by 40%. In May 2023, BenchSci secured $70m in Series D funding, bringing total investments to $170m.
Causaly (London, UK)
Their AI platform uses natural language processing to rapidly analyse biomedical literature, providing insights that normally take weeks to generate. Its software aids in discovering biomarkers, such as those for tracking cancer drug responses. In July 2023, they raised $60m in Series B funding, bringing total investment to $93m, as the company tripled revenue and gained 12 of the top 20 pharma companies as customers.
Evozyne (Chicago, US)
Uses AI-driven computational chemistry and evolutionary processes to engineer optimal proteins for healthcare and other applications. The company is developing protein drugs targeting autoimmune diseases. In September 2023, Evozyne raised $81m in a Series B round, led by Fidelity and OrbiMed, to advance its technology and validate a new AI model in collaboration with Nvidia.
Genesis Therapeutics (Burlingame, US)
Genesis raised $200m in August 2023, bringing its total funding to $280m. The company uses AI to design small-molecule drugs for difficult-to-treat targets and is now starting clinical trials for some of these drugs. Genesis is also working with Eli Lilly in a $670m partnership to develop treatments for up to five new disease areas. Major investors include Andreessen Horowitz, Fidelity, BlackRock, and NVentures.
Xaira (San Francisco, US)
A new biotech company from San Francisco, launched in 2023 with over $1Bn in funding from top investors. The company brings together experts and advanced AI technology to design new drugs, using data from lab and clinical tests to make its AI smarter. Xaira’s goal is to transform drug discovery by using AI to find better treatments faster, and it’s backed by the biggest startup investment ever from ARCH Venture Partners.
Investors in this area seek to evaluate key start-ups based on factors that can significantly influence their success. In drug discovery, proprietary algorithms, strategic partnerships, and regulatory compliance are all key benchmarks to look out for. Proprietary algorithms can provide a competitive edge by enhancing efficiency and accuracy in operations, while strategic partnerships often signal credibility and market access, increasing the startup's chances for growth. Additionally, strong regulatory compliance is crucial, especially in heavily regulated industries, as it minimises legal risks and builds trust with stakeholders. Collectively, these traits not only impact investor decisions but also serve as indicators of a startup's long-term potential, shaping their overall viability and attractiveness in a competitive market.
AI-driven drug discovery is poised to redefine healthcare, unlocking treatments for once-untreatable diseases and accelerating the path to market for new drugs. Yet this journey requires more than just investment. Regulation and compliance are key to ensuring AI’s safe application to a highly technical and sensitive domain, but also to not hinder its transformative potential in curing disease and improving health outcomes for billions.
For VCs, the intersection of new drug discovery and AI presents an exciting opportunity—but also unique challenges. Increasing regulatory scrutiny in healthcare means startups offering innovative, compliant solutions are highly attractive acquisition targets, setting the stage for strong potential returns. However, as the landscape evolves, VCs will need to navigate complexities carefully to ensure sustained growth and positive long-term impacts.
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