Artificial Intelligence (AI) in Drug Discovery Market Innovation Landscape to 2030
Artificial Intelligence (AI) in Drug Discovery Market Innovation Landscape to 2030
The artificial intelligence (AI) in drug discovery market focuses on the use of advanced technologies like machine learning and data analytics to accelerate and enhance the drug development process. AI helps researchers identify potential drug candidates, predict outcomes, and streamline clinical trials, significantly reducing time and cost compared to traditional methods. This market is growing rapidly due to increasing R&D investments, rising demand for faster drug approvals, and technological advancements in healthcare. North America leads the market due to strong infrastructure and early adoption, while regions like Asia-Pacific are emerging as key growth areas.
According to Fortune Business Insights, the global artificial intelligence (AI) in drug discovery market was valued at USD 3.00 billion in 2022 and is projected to grow from USD 3.54 billion in 2023 to USD 7.94 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 12.2% during the forecast period (2023–2030). In 2022, North America led the market with a dominant share of 69.33%.
Microsoft (U.S.)
Schrödinger, Inc. (U.S.)
Cresset (U.K.)
IBM (U.S.)
Atomwise Inc. (U.S.)
Insilico Medicine (U.S.)
Exscientia (U.K.)
BenevolentAI (U.K.)
Aria Pharmaceuticals, Inc. (U.S.)
Integral BioSciences (U.S.)
Alphabet Inc. (U.S.)
In November 2022, Cyclica secured a USD 1.8 million grant from the Bill & Melinda Gates Foundation to apply its AI‑enabled drug discovery platform toward novel, non‑hormonal compounds targeting multiple low‑data biological targets using its signature approach.
Rising chronic diseases and pandemics: The growing prevalence of illnesses like COVID‑19, cancer, cardiovascular and metabolic disorders fuels the urgent need for new drug candidates, driving demand for AI in drug discovery.
Time and cost pressure on drug development: Since bringing a molecule to market can take over a decade and cost billions, AI adoption is a strategic necessity to compress timelines and reduce financial burden.
Cross‑industry collaborations: Strategic partnerships—like BioNTech’s acquisition of InstaDeep and Sanofi’s deal with Atomwise—are accelerating platform adoption and driving innovation across sectors.
Data quality and standardization issues: Many pharmaceutical datasets are small, fragmented, multi-format or poorly labeled, hampering AI model training and deployment.
High R&D costs and regulatory hurdles: Developing AI‑based drug candidates still requires extensive validation, increasing upfront costs and delaying adoption.
The Fortune Business Insights report offers an in‑depth review of:
Market size (historical and projected 2023–2030
Segments by drug type, offering, technology, application, end‑user and region
COVID‑19’s impact, key trends, and unmet needs
Competitive benchmarking and strategic alliances
The AI drug discovery market is highly competitive and populated by leading technology and biotech innovators. Major players like Microsoft, IBM, Exscientia, Insilico Medicine, Atomwise, BenevolentAI and Alphabet are forging strategic alliances with pharmaceutical companies to bring AI‑designed drug candidates into clinical pipelines.
Small molecules: Dominated the market in 2022 due to vast availability of clinical data making AI integration efficient and cost‑effective.
Large molecules: Held a smaller share due to complex structures and limited data, though growing investments may drive future expansion.
Software: Led the market in 2022 owing to rapid adoption of AI tools for molecular screening, target identification, and compound optimization.
Services: Grew more slowly due to need for trained professionals and customization at each client site.
Machine Learning (ML): The dominant technology, used to build predictive models, design molecules, and prioritize compounds.
Natural Language Processing (NLP): Gaining traction for mining biomedical literature and clinical trial reports, though smaller in market share.
Others (e.g., computer vision, automation): Emerging but early-stage.
Oncology: Led the sector in 2022 due to high cancer prevalence and urgent need for innovative therapies.
Neurology: Growing adoption in neurological disorders and neurodegenerative diseases.
Other therapeutic areas such as endocrinology and cardiovascular disorders follow.
Pharmaceutical & biotechnology companies: The primary adopters of AI drug discovery tools and key investors in platform development.
Academic & research institutes continue to adopt AI for early-stage exploratory studies.
Other end‑users include CROs and clinical research organizations integrating AI into discovery pipelines.
Explore the full research report with detailed insights and TOC:https://www.fortunebusinessinsights.com/artificial-intelligence-in-drug-discovery-market-105354
In 2022, North America dominated the AI in drug discovery market with a 69.33% share, reflecting strong pharma‑tech alliances, robust R&D spending, and favorable regulatory frameworks.
Other regions such as Europe and Asia-Pacific show rising interest. Europe benefits from active biotech ecosystems and cross‑border collaborations, while Asia-Pacific—particularly China and India—is poised for the fastest growth due to increasing AI investments and rising chronic disease burden.
The future of AI in drug discovery appears promising:
Accelerated adoption of AI to alleviate time and cost pressures in drug development.
Expansion of AI platforms into new therapeutic domains, including rare diseases and precision medicine.
Emerging collaborations between biotech and tech firms, fueling pipeline innovation.
Efforts to improve data standardization and quality to unlock AI’s full potential.
As Fortune Business Insights forecasts, the market is set to reach nearly USD 7.94 billion by 2030, signaling a new era for drug discovery powered by AI.
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