DELRAY BEACH, Fla., July 22, 2026 /PRNewswire/ — According to MarketsandMarkets™, the AI in Drug Discovery Market is projected to reach USD 17.56 billion by 2031 from USD 5.09 billion in 2026, at a CAGR of 28.1% during the forecast period.
Browse 350 market data Tables and 65 Figures spread through 450 Pages and in-depth TOC on “AI in Drug Discovery Market – Global Forecast to 2031”
AI in Drug Discovery Market Size & Forecast:
- Market Size Available for Years: 2026–2031
- 2026 Market Size: USD 5.09 billion
- 2031 Projected Market Size: USD 17.56 billion
- CAGR (2026–2031): 28.1%
AI in Drug Discovery Market Trends & Insights:
- The AI in drug discovery market is evolving from fragmented, stage-specific applications toward integrated discovery ecosystems that connect biological data, computational chemistry, and experimental validation within a unified workflow. Pharmaceutical companies are increasingly adopting AI platforms to improve decision-making across the discovery pipeline, enabling faster prioritization of drug candidates and more informed portfolio management. This transition from isolated AI tools to enterprise-scale discovery platforms is reshaping technology investments and positioning AI as a strategic capability for next-generation pharmaceutical innovation.
- North America accounted for a 44.9% share of the AI in drug discovery market in 2025.
- By therapeutic area, the oncology segment held the largest share of 38.6% in 2025.
- By deployment model, the cloud-based model is projected to exhibit a CAGR of 28.7% during the forecast period.
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The market is entering a new phase of commercialization as pharmaceutical and biotechnology companies increasingly integrate AI across the entire drug discovery continuum rather than deploying it for isolated research tasks. Growing adoption of multimodal AI, foundation models, and advanced computational biology platforms is enabling researchers to accelerate target identification, optimize molecular design, and improve candidate selection with greater precision. The increasing availability of multi-omics datasets, expanding investments in precision medicine, and rising demand to improve R&D productivity are creating new revenue opportunities for AI platform providers, software developers, and life sciences technology companies. As pharmaceutical organizations continue to prioritize faster and more cost-effective drug development, the demand for scalable AI-enabled discovery platforms is expected to increase substantially during the forecast period.
The competitive landscape is rapidly evolving with the emergence of autonomous scientific workflows, foundation models for biology and chemistry, and AI-powered laboratory automation. Rather than investing in standalone AI applications, pharmaceutical companies are increasingly adopting integrated platforms that combine high-performance computing, generative AI, molecular simulation, and laboratory data management to accelerate drug discovery. This shift is reflected in recent strategic investments across the industry. In January 2026, NVIDIA and Eli Lilly announced the establishment of a co-innovation AI laboratory with planned investments of up to USD 1 billion over five years to develop next-generation foundation models for biology and chemistry using the BioNeMo platform. Such developments demonstrate that AI infrastructure, proprietary foundation models, and integrated discovery platforms are becoming key differentiators as pharmaceutical companies transition toward data-driven and AI-native R&D environments.
De novo drug design segment held the largest share of the AI in drug discovery market in 2025.
By use case, the de novo drug design segment accounted for the largest market share in 2025. The increasing adoption of generative AI, deep learning, and foundation models has significantly improved the ability to design novel molecular structures with desired biological and physicochemical properties. AI-driven de novo design enables researchers to rapidly generate, screen, and optimize candidate molecules while reducing reliance on traditional trial-and-error approaches. Pharmaceutical and biotechnology companies are increasingly integrating generative AI into their drug discovery workflows to accelerate early-stage research, improve candidate quality, and enhance R&D productivity. As AI models continue to evolve with access to larger biological and chemical datasets, de novo drug design is expected to remain one of the most commercially significant applications within the AI in drug discovery market.
Cloud-based segment to witness a significant CAGR in the AI in drug discovery market from 2026 to 2031.
By deployment model, the cloud-based segment is projected to record a commendable CAGR from 2026 to 2031. The widespread adoption of cloud platforms is driven by the growing computational requirements of AI models, the increasing use of large-scale biological and chemical datasets, and the need for scalable infrastructure to support collaborative drug discovery. Cloud deployment enables pharmaceutical companies and biotechnology firms to access high-performance computing resources, accelerate AI model training, facilitate secure data sharing, and integrate multiple research workflows across geographically distributed teams. In addition, growing partnerships between AI platform providers and cloud service providers are enabling organizations to deploy advanced AI capabilities without substantial investments in on-premises infrastructure, further strengthening the market position of cloud-based solutions.
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Asia Pacific to exhibit the highest growth rate in the AI in drug discovery market during the forecast period.
Based on region, Asia Pacific is projected to register the highest CAGR during the forecast period. The region is witnessing rapid growth in pharmaceutical R&D investments, expanding biotechnology ecosystems, and increasing government support for artificial intelligence and life sciences innovation. Countries such as China, Japan, South Korea, Singapore, and India are strengthening AI research capabilities through national AI strategies, investments in high-performance computing, and initiatives supporting biomedical research and precision medicine. Growing collaborations between pharmaceutical companies, AI technology providers, research institutes, and academic organizations are further accelerating the adoption of AI-enabled drug discovery platforms. These developments are expected to position Asia Pacific as the fastest-growing regional market during the forecast period.
Key Players
Leading players in the AI in Drug Discovery companies include NVIDIA Corporation (US), Schrödinger, Inc. (US), Recursion (US), Insilico Medicine (US), Google (US), Microsoft Corporation (US), Tempus AI, Inc. (US), Illumina, Inc. (US), XtalPi Inc. (China), and Iktos (France), among others.
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