AI In Pharma Global Market Report 2025

AI in pharmaceuticals involves the application of automated algorithms to perform tasks typically requiring human intelligence. Within this realm, AI solutions effectively analyze extensive datasets, including disease patterns, and aid in determining optimal medication formulations for treating specific ailments.

The market analysis of artificial intelligence (AI) in the pharmaceutical sector, as detailed in the report, is segmented based on technology, encompassing context-aware processing, natural language processing, querying methods, and deep learning. Additionally, it is categorized by drug type, covering small molecules and large molecules. Furthermore, the segmentation includes various applications such as diagnosis, clinical trial research, drug discovery, research and development, and epidemic prediction.

The artificial intelligence (AI) in pharma market research report is one of a series of new reports from The Business Research Company that provides artificial intelligence (AI) in pharma market statistics, including artificial intelligence (AI) in pharma industry global market size, regional shares, competitors with artificial intelligence (AI) in pharma market share, detailed artificial intelligence (AI) in pharma market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in pharma industry. This artificial intelligence (AI) in pharma market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The AI in pharma market size has grown exponentially in recent years. It will grow from $2.92 billion in 2024 to $3.8 billion in 2025 at a compound annual growth rate (CAGR) of 30.1%. The growth in the historic period can be attributed to increased adoption of artificial intelligence (AI) for cost efficient drug discovery and rising implementation of AI in radiology.

The AI in pharma market size is expected to see exponential growth in the next few years. It will grow to $9.64 billion in 2029 at a compound annual growth rate (CAGR) of 26.2%. The growth in the forecast period can be attributed to adoption of cloud-based applications and services by pharma companies, increasing healthcare expenditure and growing government support rising to AI development. Major trends in the forecast period include introduction of generative AI in pharma, use of AI in molecular target identification, integration of AI in drug screening process, advancements in AI tools for the pharmaceutical industry, growing investments to develop new product solutions and strategic partnerships and collaborations among market players.

The anticipated growth of the AI in pharma market is set to be propelled by the increasing government support for AI development. Governments globally acknowledge the transformative potential of AI technologies within the pharmaceutical sector, leading to the implementation of supportive policies and initiatives. Numerous countries have formulated national AI strategies that prioritize healthcare and pharmaceutical applications. These strategies are designed to catalyze the development and integration of AI technology, fostering scientific advancements and addressing real challenges within the country. An illustrative example is the Australian government's announcement in April 2022 of a financing program amounting to AUD44 million ($29.61 million) to bolster AI research among small and medium-sized enterprises (SMEs). This initiative aligns with a broader strategy aimed at enhancing AI applications across Australia's national manufacturing priority sectors, including the pharmaceutical industry. The funds will be utilized to establish digital capability centers, serving as hubs for AI research and development, offering resources, training, and support to SMEs. Consequently, the growing government support is poised to be a driving force behind the growth of the AI in pharma market in the forecast period.

The growing adoption of cloud-based applications and services by pharmaceutical companies is expected to drive the expansion of the AI in pharma market in the future. Cloud-based drug discovery platforms represent an innovative approach to research and development in the pharmaceutical sector. These platforms utilize data analytics and cloud computing technologies to enhance drug discovery processes, offering a variety of tools and functionalities essential for various aspects of drug research and discovery. They contribute to improved efficiency, cost-effectiveness, and collaboration within these processes. Pharmaceutical companies are key market participants and end-users of these platforms, which enable them to manage large volumes of clinical, chemical, and biological data by providing secure data storage solutions. For example, in December 2023, Eurostat Statistics, a Luxembourg-based provider of statistical information and analysis, reported that 45.2% of European Union enterprises used cloud computing in 2023, an increase of 4.2 percentage points from 2021. Most enterprises utilize cloud computing for email hosting, file storage, and office software. Furthermore, 75.3% have adopted advanced cloud services for security applications, database hosting, and application development platforms, indicating a growing dependence on digital solutions for enhanced efficiency and security. Therefore, the increasing adoption of cloud-based applications and services by pharmaceutical companies is poised to propel the growth of the AI in pharma market during the forecast period.

An important trend in the AI for the pharma market is the introduction of new AI tools by companies, aiming to provide significant benefits to pharmaceutical companies. AI technology contributes to various aspects of the pharmaceutical industry, including quality control, predictive maintenance, waste reduction, design optimization, and process automation. In August 2022, Sanford Health and Sharp HealthCare, both US-based non-profit healthcare organizations, collaborated with Dandelion Health, a US-based healthcare AI company, to unveil a comprehensive data platform. Named the Dandelion Platform, this initiative provides health institutions with access to high-quality and representative patient data for the development of clinical AI tools. The platform enables health AI developers to securely access patient datasets, encompassing images, waveforms, and structured health records. This accessibility facilitates the creation of tools and products that can benefit both patients and clinicians.

Companies operating in the AI for pharma market are increasingly directing their focus towards the application of generative AI in improving medical consultations. Generative AI, a subfield of artificial intelligence dedicated to creating new data instances resembling existing data, has found its way into the pharmaceutical industry, offering the potential to revolutionize drug discovery, development, and medical records management. In October 2023, Ubie, a Japan-based medical AI startup, introduced a novel Generative AI feature designed for doctors. This feature, known as the 'Medical Interview Summary Function,' utilizes a Large Language Model (LLM) to generate AI-based summaries from patient visits. Specifically, it summarizes the 20-30 questions related to symptoms and lifestyle habits that patients answer on the 'Ubie Medical Navi' product. The LLM then presents this summary on the doctor's PC screen, enabling quick comprehension of the patient's symptoms and concerns. This innovation serves to enhance the quality of medical consultations by providing efficient and comprehensive summaries for healthcare professionals.

In July 2023, BioNTech SE, a Germany-based biotechnology firm known for developing and manufacturing active immunotherapies, acquired InstaDeep for an undisclosed sum. This acquisition is intended to strengthen BioNTech's AI-driven drug discovery and development capabilities, thereby speeding up the creation of next-generation immunotherapies and vaccines. InstaDeep is a UK-based technology company that specializes in artificial intelligence (AI) and machine learning (ML) solutions.

Major companies operating in the AI in pharma market include Concerto HealthAI, Alphabet Inc., OWKIN, Nvidia Corporation, PathAI, Insilico Medicine, Exscientia, Microsoft Corporation, XtalPi, Intel, Standigm, Takeda Pharmaceutical Company Ltd., Otsuka Pharmaceutical Co. Ltd., China National Pharmaceutical Group Co. Ltd. (Sinopharm), Jiangsu Hengrui Medicine Co. Ltd, Cipla Limited, Aurobindo Pharma Limited, Dr. Reddy's Laboratories Ltd., Sun Pharma, Alliance Pharm Pte Ltd., Shanghai Pharmaceuticals, DeepMind, GlaxoSmithKline, Sanofi, Bayer, Renalytix AI, Merck, AstraZeneca, Iktos, Benevolent AI, Novartis, Ardigen, Botkin, Webiomed, Care Mentor AI, Diagnocat, IBM Corporation, Atomwise Inc., Cloud Pharmaceuticals, Bioage, NuMedii, Envisagenics, Aria Pharmaceuticals, Verge Genomics, Berg LLC, Cyclica, IQVIA, Roche, Pfizer, PRA Health Science, Gesto, Intensicare, Epitrack, Deep Genomics Inc., Welltok Inc., Oncora Medical, Recursion Pharmaceuticals Inc., Nucleai, Pepticom, Rology, hearX Group, DilenyTech, iNNOHEALTH Technology Solutions

North America was the largest region in the AI in pharma market in 2024. The regions covered in the AI in pharma market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the AI in pharma market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Spain, Canada.

The AI in pharma market includes revenues earned by entities by implementing quality control, addressing supply chain problems in the production line, and minimizing material waste. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

AI In Pharma Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on ai in pharma market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for ai in pharma ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The ai in pharma market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

• The market characteristics section of the report defines and explains the market.
• The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
• The forecasts are made after considering the major factors currently impacting the market. These include:

The forecasts are made after considering the major factors currently impacting the market. These include the Russia-Ukraine war, rising inflation, higher interest rates, and the legacy of the COVID-19 pandemic.

• Market segmentations break down the market into sub markets.
• The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth. It covers the growth trajectory of COVID-19 for all regions, key developed countries and major emerging markets.
• The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
• The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

• Markets Covered:1) By Technology: Context-Aware Processing, Natural Language Processing, Querying Method, Deep Learning
• 2) By Drug Type: Small Molecule, Large Molecules
• 3) By Application: Diagnosis, Clinical Trial Research, Drug Discovery, Research and Development, Epidemic Prediction
• Subsegments:
• 1) By Context-Aware Processing: Real-Time Data Processing; Contextual Recommendation Systems; Adaptive Learning Systems
• 2) By Natural Language Processing (NLP): Text Analytics And Sentiment Analysis; Chatbots And Virtual Assistants; Document And Data Mining
• 3) By Querying Method: Structured Querying; Unstructured Querying; Semantic Search Technologies
• 4) By Deep Learning: Neural Networks For Drug Discovery; Image Recognition For Medical Imaging; Predictive Analytics Models
• Companies Mentioned: Concerto HealthAI; Alphabet Inc.; OWKIN; Nvidia Corporation; PathAI
• Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain
• Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
• Time series: Five years historic and ten years forecast.
• Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
• Data segmentations: country and regional historic and forecast data, market share of competitors, market segments.
• Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
• Delivery format: PDF, Word and Excel Data Dashboard.