The AI in drug discovery market size is expected to reach USD 35.42 billion by 2034, exhibiting a CAGR of 29.6% during 2025–2034.
The AI in drug discovery market has emerged as a transformative force in the pharmaceutical and biotechnology industries. By leveraging artificial intelligence (AI) technologies, such as machine learning (ML), deep learning, and natural language processing (NLP), drug discovery processes are being revolutionized, making them faster, more efficient, and cost-effective. AI enables researchers to better understand complex biological systems, identify new drug candidates, predict potential side effects, and optimize clinical trial designs.
Research Scope
The research scope in the AI in drug discovery market is broad, covering various aspects such as:
- Improvement of Machine Learning Models
- Researchers are focused on refining ML algorithms to improve the accuracy of drug efficacy and safety predictions.
- AI in Biomarker Discovery
- AI is being used to discover new biomarkers that can predict disease progression, drug response, and patient outcomes.
- AI-Driven Simulation and Modeling
- In silico models powered by AI simulate drug interactions and predict biological responses, helping to reduce the need for animal testing and optimizing early-phase development.
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List of Key Companies in AI in Drug Discovery Market
- Atomwise Inc.
- BenevolentAI
- Berg Health (In January 2023, Berg Health acquired by BPGbio Inc.)
- BioSymetrics, Inc.
- CYCLICA (Acquired by Recursion Pharmaceuticals)
- Exscientia
- GNS Healthcare (In January 2023, the company Rebranded as Aitia)
- Google (DeepMind)
Challenges in the Market
- Data Privacy and Security Concerns
- As AI relies heavily on big data, concerns about the security and privacy of patient data remain a challenge.
- Integration with Existing Systems
- Integrating AI with traditional drug discovery processes and legacy systems in pharmaceutical companies can be difficult and costly.
- Regulatory Hurdles
- Regulatory agencies are still developing frameworks to assess the safety and efficacy of AI-powered drug discovery tools, creating uncertainty for market players.
𝐒𝐞𝐠𝐦𝐞𝐧𝐭𝐚𝐥 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰:
The research report categorizes the market into various segments and sub-segments. The primary segments covered in the study include type, application, end use and region. The splitting of the market into various groups enables businesses to understand market preferences and trends better. Also, stakeholders can develop products/services that align with the diverse needs of consumers in the industry. Besides, the research study includes a thorough examination of all the major sub-segments in the market.
By Offering Outlook
- Software
- Services
By Technology Outlook
- Machine Learning
- Deep Learning
- Supervised Learning
- Reinforcement Learning
- Unsupervised Learning
- Other Machine Learning Technologies
- Other Technologies
By Therapeutic Area Outlook
- Oncology
- Neurodegenerative Diseases
- Cardiovascular Disease
- Metabolic Diseases
- Infectious Disease
- Others
By Application Outlook
- Drug optimization & repurposing
- Preclinical testing
- Others
By End User Outlook
- Pharmaceutical & Biotechnology Companies
- Contract Research Organizations
- Research Centers
- Academic & Government Institutes
AI in Drug Discovery Industry Developments
In July 2024, Exscientia plc collaborated with Amazon Web Services (AWS) to leverage the cloud provider’s artificial intelligence (AI) and machine learning (ML) services to strengthen its platform for comprehensive drug discovery and automation.
In May 2024, Google launched AlphaFold 3, a new AI model developed by Google DeepMind and Isomorphic Labs. The company claims that the model accurately predicts the structure of RNA, DNA, proteins, and ligands and how they interact with the potential to transform the understanding of the biological world and drug discovery.
In December 2023, MilliporeSigma launched AIDDISON, the first software-as-a-service platform bridging virtual molecule design with real-world manufacturability via Synthia retrosynthesis software API integration.
The AI in drug discovery market is poised for rapid growth, driven by advances in machine learning, deep learning, and natural language processing, alongside increasing investments in biotechnology and personalized medicine. AI is revolutionizing the way pharmaceutical companies discover and develop new drugs, offering substantial reductions in time and cost.