AI in Biopharmaceuticals Market Reshaping Global Pharma Outlook

AI in Biopharmaceuticals Market Size, Key Players with Shares and Growth

The AI in biopharmaceuticals market size is calculated at US$ 1.55 billion in 2024, grew to US$ 2.05 billion in 2025, and is projected to reach around US$ 24.49 billion by 2034. The market is expanding at a CAGR of 32.27% between 2025 and 2034.

The AI in biopharmaceuticals market has transformed drug discovery, precision medicine, and pharmaceutical research by improving biopharmaceutical commercialization. It encompasses market analysis and strategy, regulatory approval, brand development, product launch and post-launch activities, patient support and education, and market access and reimbursement. Biopharmaceutical leaders are prioritizing predictive analytics, digital engagement, and real-time personalization.

Key Takeaways

• AI in biopharmaceuticals sector pushed the market to USD 1.55 billion by 2024.
• Long-term projections show USD 24.49 billion valuation by 2034.
• Growth is expected at a steady CAGR of 32.27% in between 2025 to 2034.
• North America dominated the market in 2024, with a revenue share of approximately 45%.
• Asia Pacific is expected to grow at the fastest CAGR in the market during the forecast period.
• By application/value-chain use, the drug discovery segment dominated the market in 2024, with a revenue share of approximately 45%.
• By application/value-chain use, the clinical development & trials segment in the AI in biopharmaceuticals market is expected to grow at the fastest CAGR during the forecast period.
• By therapeutic focus/use case, the oncology segment dominated the market in 2024, with a revenue share of approximately 28%.
• By therapeutic focus/use case,  the neurology segment is expected to grow at the fastest CAGR in the market during the forecast period.
• By technology/methodology, the deep learning segment dominated the market in 2024, with a revenue share of approximately 28%.
• By technology/methodology, the generative models segment is expected to witness the fastest growth during the forecast period.
• By deployment/delivery model, the cloud-based SaaS & platforms segment dominated the market in 2024, with a revenue share of approximately 62%, the segment is expected to sustain the position during the forecast period.

Executive Summary Table

What is AI in Biopharmaceuticals?

The urgent need to streamline preclinical research, improve success rates of clinical trials, and tailor treatment plans drives the adoption of artificial intelligence in the biopharmaceutical industry. The AI in biopharmaceuticals market covers software, platforms, and services that apply artificial intelligence (machine learning, deep learning, generative models, computer vision, natural language processing, and hybrid approaches) across the biopharma value chain.

This includes AI for drug discovery (target ID, hit generation, lead optimization), preclinical modeling and in-vitro/in-vivo prediction, clinical trial design and patient selection, manufacturing process optimization and quality control, regulatory intelligence & pharmacovigilance, and commercial analytics (market access, RWE, promotional optimization). Solutions range from niche models and point tools to enterprise platforms and CDMO-integrated services.

Growth is driven by pressure to shorten R&D timelines, reduce attrition, lower development costs, increase availability of biological and real-world datasets, and wider acceptance of AI-augmented decision-making in R&D and manufacturing.

Market Outlook

• Industry Growth Overview: The AI in biopharmaceuticals market is primarily driven by regional leadership through robust R&D infrastructure, significant funding, and supportive regulatory frameworks. The automated operations are enabled by AI-powered robotics and predictive maintenance systems.
• Sustainability Trends: The rising trends are seen in the form of reduced timelines for AI-enabled workflows, enhanced supply chain management, and operational continuity. The supply chain resilience, waste reduction, and water conservation accelerate biopharmaceutical operations.
• Major Investors: The major pharmaceutical companies, like Pfizer, Johnson & Johnson, Eli Lilly, Novo Nordisk, Merck, and Sanofi, made investments in AI-enabled drug discovery startups. They have also invested in companies driving precision medicine and clinical trial optimization platforms.

Segmental Insights

How does the Drug Discovery Segment Dominate the AI in Biopharmaceuticals Market in 2024?

The drug discovery segment dominated the market in 2024, with a revenue share of approximately 45%, owing to the wide applications of AI in the analysis of vast datasets, de novo drug design, and prediction of trial outcomes. The drug discovery and development process is accelerated by improved cost efficiency, increased speed, and higher success rates. AI improves trial design and monitoring and streamlines patient recruitment.

The clinical development & trials segment is expected to grow at the fastest CAGR in the market during the forecast period due to enhanced preclinical trials and optimized drug formulations by the insertion of AI into clinical development. AI enables personalized medicine, enhances clinical trial efficiency, and speeds up drug discovery and development. AI allows the identification and optimization of new drug candidates, the monitoring of patient safety, and the refinement of trial design.

What made Oncology the Dominant Segment in the AI in Biopharmaceuticals Market in 2024?

The oncology segment dominated the market in 2024, with a revenue share of approximately 28%, owing to the accelerated drug discovery, biomarker discovery, and precision oncology. AI improves diagnosis and monitoring, and streamlines clinical trials in cancer research. AI assists in patient selection, adaptive trial design, and risk assessment.

The neurology segment is estimated to grow at the fastest rate in the market during the predicted timeframe due to the immense role of AI in diagnosis, early detection, treatment, management, research, and drug development. AI used in neuroimaging can automate the analysis of PET, MRI, and CT scans to detect abnormalities. The wearables and biosensors equipped with AI algorithms help with early detection of severe health conditions like epilepsy and Parkinson's disease.

How did the Deep Learning Segment Dominate the AI in Biopharmaceuticals Market in 2024?

The deep learning segment dominated the market in 2024, with a revenue share of approximately 28%, owing to the use of AI to support clinical decisions in treating neurological conditions. Neurologists understand clinical AI, which helps in diagnosis and patient care. AI assists in procedural tasks and human communication.

The generative models segment is anticipated to grow at a notable rate in the market during the upcoming period due to the critical role of AI in predictive modeling, antibody design and optimization, manufacturing, and supply chain. The generative AI models accelerate drug design, discovery, and optimization of novel drugs. Machine learning algorithms enable virtual screening of potential drug candidates.

Which Segment by Deployment/Delivery Model Dominated the AI in Biopharmaceuticals Market in 2024?

The cloud-based SaaS & platforms segment dominated the market in 2024, with a revenue share of approximately 62%, owing to improved computational power and scalability. The segment is expected to sustain the position during the forecast period due to improved data integration and data management, as well as advanced data analytics. AI-enabled platforms ensure compliance and security through robust security features and regulations.

Regional Insights

How does North America Dominate the AI in Biopharmaceuticals Market in 2024?

North America dominated the market in 2024, with a revenue share of approximately 45%, owing to the largest adoption of AI, pharma HQs, VC funding, and cloud infrastructure. America’s AI action plan drives the establishment of laboratory infrastructure, supports novel scientific organizations, and strengthens the data infrastructure. The American Hospital Association (AHA) announced that many agencies are collaborating on pharmaceutical manufacturing projects using AI. The public-private partnerships are driven by organizations like the Department of Energy (DoE) and the National Science Foundation (NSF) that accelerate drug discovery and validate new therapies.

How is the Notable Growth of the U.S. in the AI in Biopharmaceuticals Market?

The Trump administration launched an AI-driven drug manufacturing initiative, supported by the U.S. Department of Health and Human Services (HHS) and the Defense Advanced Research Projects Agency (DARPA), to advance U.S. pharmaceutical manufacturing through advanced technologies, including machine learning, artificial intelligence, and informatics. The U.S. introduced AI-powered domestic drug manufacturing, driven by public-private partnerships, utilization of cutting-edge technologies, and specific innovative projects. Moreover, the 3D printing revolution, improved manufacturing, automation, and real-time optimization.

What is the Potential of the AI in Biopharmaceuticals Market in the Asia Pacific?

Asia Pacific is expected to grow at the fastest CAGR in the market during the forecast period due to a growing biotech activity, data availability, and AI manufacturing uptake. Asia Pacific governments implement targeted programs to provide capital and infrastructure for early-stage R&D. These efforts attract more private capital investments, and companies embrace new tools to streamline testing, code faster, and improve quality. This region is rapidly inserting AI into its application development and maintenance (ADM) operations. A growing number of enterprises across this region are adopting AI-based ADM services to improve operational efficiency and ensure software reliability.

What are the Trends in India in the AI in Biopharmaceuticals Market?

The Government of India stated that over ₹10,300+ crore were allocated over five years for the IndiaAI mission. Moreover, over 6 million people were employed in the tech and AI ecosystem. India accounts for around 1.8 lakh startups that have used AI in their products and services.

How is the Notable Growth of Europe in the AI in Biopharmaceuticals Market?

Europe is seen to grow at a notable rate in the market in 2024, led by strong translational research and regulatory-driven AI adoption. The European Commission (EC) introduced two strategies that will speed up the adoption of AI, enhance innovations, and maintain the competitiveness of Europe. The European Union (EU) also launched two strategies to advance AI in Science and industry. Europe remains a global leader with innovative AI applications. The EU has expanded access to high-performance computing through AI Gigafactories for researchers and startups.

What is the Major Footprint of Germany in the AI in Biopharmaceuticals Market?

The leading companies that offer AI-driven technologies aim to expand their operations into Germany. These AI applications in Germany encompass drug discovery, orphan drugs, cell and gene therapy, and precision medicine. AI is driving robust healthcare infrastructure, cutting-edge research facilities, and a strong commitment to medical improvements.

Top Vendors in the AI in Biopharmaceuticals Market

• Insilico Medicine: It leads with a strong portfolio of AI-driven platforms, including an end-to-end AI-driven platform like Pharma.AI, an AI engine like PandaOmics, and a generative chemistry engine like Chemistry42. A drug pipeline includes clinical-stage assets, preclinical, and other notable programs.
• Exscientia: This leading company supports generative AI drug design, a robotic laboratory that integrates AI design, and expansion into AI-designed biologics like antibodies.
• Atomwise: The key offerings include the AtomNet platform for small-molecule drug discovery, virtual screening, and drug optimization.
• BenevolentAI: It offers an AI-enabled drug discovery platform, strategic collaborations, and development of in-house drug candidates.
• Recursion Pharmaceuticals: Advanced platforms and technologies are driven by the expansion of AI-driven drug discovery platforms like Recursion OS, supercomputing power, datasets, and models.

Top Companies in the AI in Biopharmaceuticals Market

• Insilico Medicine
• Exscientia
• Atomwise
• BenevolentAI
• Recursion Pharmaceuticals
• Schrödinger
• Deep Genomics
• Relay Therapeutics
• Valo Health
• Numerate
• BenchSci
• Owkin
• Causal AI/BioSymetrics
• Cloud Pharmaceuticals
• Arctoris/Benchling-adjacent tool providers
• TwoXAR/Healx
• Boston- and Silicon Valley-based AI drug startups
• Large cloud/tech providers enabling enterprise AI
• Leading CROs & CDMOs integrating AI capabilities
• Academic spinouts and translational AI labs commercializing platforms

Recent Developments in the AI in Biopharmaceuticals Market

• In October 2025, Insilico Medicine reported a transformation in drug target discovery and a new study that introduced AI-empowered target identification Pro (TargetPro) and TargetBench 1.0.
• In July 2024, Exscientia announced the expansion of its collaboration with Amazon Web Services (AWS) with the launch of an AWS AI-powered platform to advance end-to-end drug discovery and automation by using AI and ML services of the cloud provider.

Segments Covered in the Report

By Application/Value-chain Use

• Drug Discovery (target identification, virtual screening, lead optimization)
• Preclinical Development (toxicity prediction, ADME modeling)
• Clinical Development & Trials (trial design, cohort selection, digital biomarkers)
• Manufacturing & Bioprocess Optimization (PAT, yield prediction, predictive maintenance)
• Regulatory Intelligence & Pharmacovigilance (signal detection, dossier automation)
• Commercial & Market Access Analytics (RWE, pricing, HCP/patient engagement models)

By Therapeutic Focus/Use Case

• Oncology
• Rare & Genetic Diseases
• Immunology & Inflammation
• Neurology (incl. CNS disorders)
• Cardiometabolic Diseases
• Infectious Diseases & Vaccinology
• Multi-indication/Platform Agnostic

By Technology/Methodology

• Classical Machine Learning (random forests, gradient boosting)
• Deep Learning (CNNs, RNNs)
• Generative Models (transformers, diffusion models for molecule generation)
• NLP for Literature & Regulatory Mining
• Computer Vision (histopathology, imaging analysis)
• Hybrid & Multi-omics Integration Models

By Deployment/Delivery Model

• Cloud-based SaaS & Platforms
• On-premise/Private Cloud (regulated environments)
• Edge/Embedded (lab instruments, imaging devices)
• Hybrid (cloud + on-prem orchestration)

By Region

• North America
  • U.S.
  • Canada
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Thailand
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Sweden
  • Denmark
  • Norway
• Latin America
  • Brazil
  • Mexico
  • Argentina
• Middle East and Africa (MEA)
  • South Africa
  • UAE
  • Saudi Arabia
  • Kuwait