Meticulous Research®, a prominent global market research company, recently published a detailed report titled, Artificial Intelligence in Drug Discovery Market by Offering (Software, Service), Application (Target Discovery, Lead Identification, Clinical Testing), Therapy Area (Oncology, Cardiology, Neurodegenerative), Deployment, End User—Global Forecast to 2030. The report reveals that the global market for AI in drug discovery is anticipated to reach $8.95 billion by 2030, growing at a compound annual growth rate (CAGR) of 27.2% during the forecast period from 2024 to 2030.

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Several key factors are driving this impressive growth, including the increasing focus on reducing the turnaround time in drug discovery processes, expanding applications of AI in pharmaceutical research, the rising prevalence of chronic diseases, and the ongoing advancements in AI technologies within the healthcare sector. Additionally, the growing adoption of machine learning (ML) in drug discovery, the emergence of local and regional start-ups focusing on AI-driven drug discovery, and increased investments in research and development (R&D) are creating further opportunities in this dynamic market.

Market Outlook and Segmentation

The global AI in drug discovery market is comprehensively segmented based on various factors such as offering, deployment mode, application, therapeutic area, end user, and geography. These segments allow for a thorough understanding of market dynamics and growth potential.

1. Offerings Segment: In 2024, the software segment is expected to dominate the market. Software solutions in this space are generally available via licensing models, subscription-based services, or as software-as-a-service (SaaS) offerings, which provide recurring revenue streams. The widespread adoption of AI-based software solutions in drug discovery is a key driver for this segment. AI software helps pharmaceutical companies significantly reduce the time and costs associated with the traditionally lengthy drug discovery process, making it an essential tool in modern drug development.
2. Deployment Mode Segment: The cloud and web-based segment is projected to grow at the fastest pace over the forecast period. Cloud and web-based platforms offer significant advantages, such as enhanced accessibility, lower maintenance costs, and expansive storage capacity. Given the enormous volume of pharmaceutical data generated during drug discovery, cloud-based solutions provide an efficient and cost-effective method of storing and accessing these datasets. Consequently, cloud-based platforms are expected to see increased adoption across the industry.

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3. Application Segment: The lead compound identification segment is poised to hold the largest market share in 2024. Identifying a lead compound is one of the initial and most critical steps in the drug discovery process, as it forms the foundation for developing a new therapeutic agent. AI's ability to streamline and enhance this process has led to its growing use in lead compound identification, making this segment a major contributor to market growth.
4. Therapeutic Area Segment: The oncology segment is expected to account for the largest share of the AI in drug discovery market in 2024. This is largely due to the growing global prevalence of cancer, which remains one of the leading causes of mortality worldwide. According to the International Agency for Research on Cancer, approximately 19.3 million new cancer cases were reported globally in 2020. In response to this rising incidence, pharmaceutical companies are increasingly focusing on developing innovative cancer therapies using AI-driven approaches. As a result, AI-based drug discovery is being widely adopted in oncology, contributing to the dominance of this segment.
5. End User Segment: Pharmaceutical and biopharmaceutical companies are expected to represent the largest end-user group in the AI in drug discovery market by 2024. These companies are heavily investing in AI technologies to accelerate drug discovery, particularly for oncology drugs. Their commitment to integrating AI into their R&D processes, alongside significant financial investments, has solidified their leading position in the market.

Geographical Insights

The report also provides an in-depth analysis of the global AI in drug discovery market across several key regions, including North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa. Among these regions, North America is projected to hold the largest market share in 2024, followed closely by Europe and Asia-Pacific.

1. North America: The U.S. is expected to dominate the North American market, primarily due to the increasing public and private investments in drug discovery, coupled with the rapid adoption of AI-driven solutions. The presence of major AI and pharmaceutical companies, such as Abbott Laboratories and Pfizer Inc., also contributes to the region’s substantial market share.
2. Europe: European countries like Germany, France, and the U.K. are also significant contributors to the AI in drug discovery market, driven by strong government support for R&D initiatives and the presence of advanced healthcare infrastructure. The region’s growing emphasis on AI innovation is expected to propel its market growth over the forecast period.
3. Asia-Pacific: Asia-Pacific is another key growth region, with countries like China, Japan, and India at the forefront. These nations are investing heavily in healthcare innovation, including AI technologies for drug discovery. The region’s rapidly expanding pharmaceutical industry and growing healthcare needs are contributing to the increasing adoption of AI-based drug discovery platforms.
4. Latin America & Middle East & Africa: Although smaller in comparison to other regions, Latin America and the Middle East & Africa are gradually emerging as potential markets for AI in drug discovery. Factors such as improving healthcare infrastructure and rising awareness of AI’s benefits in pharmaceutical research are fostering growth in these regions.

Competitive Landscape

The competitive landscape of the AI in drug discovery market is diverse and includes several key players that are shaping the future of this industry. Major companies in the global market include:

• Microsoft Corporation (U.S.): A global technology leader with a strong focus on AI solutions for healthcare, including drug discovery.
• Exscientia plc (U.K.): A pioneer in AI-driven drug discovery, known for leveraging cutting-edge AI algorithms to accelerate the development of new therapies.
• NVIDIA Corporation (U.S.): Renowned for its AI computing platforms, NVIDIA plays a crucial role in powering the AI infrastructure required for drug discovery.
• Schrödinger, LLC (U.S.): A leading provider of advanced computational solutions for drug discovery and development.
• Atomwise, Inc. (U.S.): Specializes in using AI to identify potential drug candidates, revolutionizing early-stage drug discovery.
• BenevolentAI Limited (U.K.): Focuses on applying AI to unlock new insights in drug discovery, particularly in oncology.
• Deep Genomics Incorporated (Canada): Uses AI to discover and develop innovative RNA-based therapies.
• InSilico Medicine (U.S.): A global leader in using AI to accelerate drug discovery and development processes.
• Cloud Pharmaceuticals, Inc. (U.S.): Focuses on cloud-based AI solutions for drug design and development.
• Standigm Inc. (South Korea): A rapidly growing AI biotech company focused on discovering novel drug candidates.

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Conclusion

The global AI in drug discovery market is poised for remarkable growth over the coming years, driven by the increasing adoption of AI technologies, rising healthcare demands, and the need for faster and more cost-effective drug development processes. With advancements in AI and machine learning, pharmaceutical companies are better equipped to tackle the challenges of drug discovery, ultimately leading to innovative treatments for a wide range of diseases. The future of AI in drug discovery holds immense potential, offering new opportunities for both established industry players and emerging start-ups.

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