In 2023, the Global Artificial Intelligence in Drug Discovery Market was valued at USD 1.2 billion. This market is expected to reach USD 13.6 billion by 2033, growing at an impressive compound annual growth rate (CAGR) of 27.5% between 2024 and 2033. The growth of this market is driven by several factors, including the increasing need to reduce the time and cost of drug development and the rising prevalence of chronic diseases. AI technologies, particularly machine learning and deep learning, are being increasingly used to streamline various stages of drug discovery, from target identification and validation to lead optimization and preclinical testing.
One of the key growth factors is the ability of AI to analyze vast amounts of data quickly and accurately, improving the efficiency and success rate of drug discovery processes. For instance, AI can predict drug interactions and optimize drug formulations, significantly shortening the development cycle. Additionally, the growing investment in AI by pharmaceutical companies and the introduction of advanced AI-based solutions are further propelling market growth.
However, the market faces challenges such as the high cost of AI integration and the lack of skilled professionals to manage these technologies. Small and medium-sized enterprises, in particular, find it difficult to adopt AI due to these cost and infrastructure barriers. Despite these challenges, ongoing advancements and the increasing application of AI in various therapeutic areas, including oncology and infectious diseases, present significant growth opportunities.
Recent developments highlight the market’s dynamic nature. For instance, new AI platforms and tools are being launched to enhance different stages of drug discovery. The collaboration between tech companies and pharmaceutical firms is also intensifying, driving innovation and adoption of AI in this sector.
Key Takeaways
- The global Artificial Intelligence in Drug Discovery Market was valued at USD 1.2 billion and is projected to reach USD 13.6 billion by 2033.
- Between 2024 and 2033, the market is expected to register a CAGR of 27.5%.
- Software leads the market, accounting for 65.4% of the AI in drug discovery market share.
- Machine learning technology holds a 52.7% market share due to its numerous benefits.
- Neurodegenerative diseases accounted for 43.8% of the market share in 2023.
- Pharmaceutical and biotechnological companies cover 68.4% of the AI in drug discovery market share.
- North America dominates the market, accounting for 60.1% of the global revenue share.
- AI has enabled the pharmaceutical industry to grow significantly in drug discovery, enhancing tasks like lead compound recognition and target validation.
- Key applications of AI in drug discovery include polypharmacology, chemical synthesis, drug repurposing, and drug screening.
- These applications facilitate the development of drugs for emerging diseases.
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Artificial Intelligence in Drug Discovery Market Key Segments
Component
- Software
- Service
Technology
- Machine Learning
- Deep Learning
- Other Technologies
Application
- Neurodegenerative Diseases
- Cardiovascular Diseases
- Metabolic Diseases
- Immuno-Oncology
- Other Applications
End-User
- Pharmaceutical and Biotechnological Companies
- Academic and Research Institutes
- Other End-Users
Key Regions
- North America (The US, Canada, Mexico)
- Western Europe (Germany, France, The UK, Spain, Italy, Portugal, Ireland, Austria, Switzerland, Benelux, Nordic, Rest of Western Europe)
- Eastern Europe (Russia, Poland, The Czech Republic, Greece, Rest of Eastern Europe)
- APAC (China, Japan, South Korea, India, Australia & New Zealand, Indonesia, Malaysia, Philippines, Singapore, Thailand, Vietnam, Rest of APAC)
- Latin America (Brazil, Colombia, Chile, Argentina, Costa Rica, Rest of Latin America)
- Middle East & Africa (Algeria, Egypt, Israel, Kuwait, Nigeria, Saudi Arabia, South Africa, Turkey, United Arab Emirates, Rest of MEA)
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Key Players Analysis
NVIDIA Corporation significantly advances artificial intelligence (AI) in drug discovery through its BioNeMo platform. BioNeMo offers a suite of generative AI models and tools that enable pharmaceutical companies to accelerate drug research and development. By leveraging pretrained biomolecular AI models, NVIDIA helps in predicting protein structures, generating molecular compounds, and optimizing drug candidates, thus reducing the need for extensive lab experiments. Collaborations with leading biotech firms, such as Genentech and Recursion, highlight NVIDIA’s role in transforming computational drug discovery through AI-powered solutions.
Microsoft Corporation is significantly advancing the field of drug discovery through artificial intelligence. Collaborating with pharmaceutical giants like Novo Nordisk and Novartis, Microsoft integrates its AI technology, computational services, and cloud computing to streamline the drug development process. This partnership aims to leverage AI for data analysis, predictive modeling, and identifying novel drug candidates, thereby accelerating research timelines and enhancing efficiency. By combining Microsoft’s technological expertise with pharmaceutical companies’ scientific knowledge, these collaborations strive to expedite the discovery of new, effective treatments.
Cloud Pharmaceuticals, a leader in AI-driven drug design, utilizes proprietary artificial intelligence to accelerate drug discovery. By partnering with major pharmaceutical companies such as GlaxoSmithKline (GSK), Cloud Pharmaceuticals has demonstrated its ability to significantly shorten the drug development timeline from years to months. The company’s technology focuses on designing novel small-molecule agents tailored to specific drug targets, enhancing the efficiency and quality of drug discovery processes.
TOMWISE INC., a leader in AI-driven drug discovery, uses its AtomNet platform to revolutionize small molecule discovery. By leveraging deep learning and structure-based design, the company aims to make drug development more efficient and effective. A notable collaboration with Sanofi highlights TOMWISE’s innovative approach, targeting up to five drug targets with the potential for significant milestone-based payments. The company’s proprietary library of over 3 trillion synthesizable compounds underpins its success in finding novel therapeutic candidates across a wide array of protein types and challenging targets.
Schrödinger Inc. leverages artificial intelligence in drug discovery through its advanced computational platform, which integrates physics-based simulations and machine learning to identify promising drug candidates efficiently. Their AI-driven platform, supported by partnerships with NVIDIA, enables rapid evaluation of billions of molecules, significantly accelerating the drug discovery process. Schrödinger’s recent developments include the advancement of SGR-1505, a MALT1 inhibitor for B-cell malignancies, currently in Phase 1 clinical trials. This approach underscores the potential for AI to transform therapeutic development by enhancing accuracy and reducing time and cost.
Artificial Intelligence in Drug Discovery Market Key Players:
- NVIDIA CORPORATION
- Microsoft Corporation
- Cloud Pharmaceuticals
- TOMWISE INC.
- AI
- Schrödinger
- BioSymetrics
- Cyclica Inc.
- IBM Watson
- Benevolent AI
- Other Key Players
Artificial Intelligence in Drug Discovery Market Report Scope >> Market Value (2023): USD 1.2 Billion || Forecast Revenue (2033): USD 12.8 Billion || CAGR (2024-2033): 27.5% || Base Year Estimation: 2023 || Historic Period: 2019-2022 || Forecast Period: 2024-2033.
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