At what pace is the generative artificial intelligence (ai) in pharmaceutical market growing, and what is its estimated value?
The generative artificial intelligence (AI) in pharmaceutical market size has grown exponentially in recent years. It will grow from $1.85 $ billion in 2024 to $2.43 $ billion in 2025 at a compound annual growth rate (CAGR) of 31.3%. The growth in the historic period can be attributed to growth in computational power, the rise of big data in healthcare and pharmaceuticals, increased research and development investment, improved data quality and integration, and expansion of cloud computing.
The generative artificial intelligence (AI) in pharmaceutical market size is expected to see exponential growth in the next few years. It will grow to $7.16 $ billion in 2029 at a compound annual growth rate (CAGR) of 31.0%. The growth in the forecast period can be attributed to a focus on early disease detection, regulatory support, and guidelines, improved computational power, growth in drug development costs, increased data availability. Major trends in the forecast period include blockchain and AI integration, advanced data integration, enhanced disease diagnosis, automated drug repurposing, real-time clinical trial optimization.
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What are the top drivers to the rising demand in the generative artificial intelligence (ai) in pharmaceutical market?
The increasing focus on personalized medicine is expected to propel the growth of generative artificial intelligence (AI) in the pharmaceutical market going forward. Personalized medicine tailors medical treatment to the individual characteristics, needs, and preferences of each patient based on genetic, environmental, and lifestyle factors. The focus on personalized medicine is increasing due to advancements in genetic research and technology, enabling more precise and effective treatments tailored to individual patients. Personalized medicine leverages generative AI in pharmaceuticals to develop tailored drug therapies, improving treatment efficacy and patient outcomes. For instance, in February 2024, according to the Personalized Medicine Coalition, a US-based non-profit organization, the FDA approved 16 novel personalized therapies for patients with rare diseases in 2023, compared to six in 2022. Therefore, the increasing focus on personalized medicine is driving the growth of generative artificial intelligence (AI) in the pharmaceutical market.
How is the generative artificial intelligence (ai) in pharmaceutical market segmented?
The generative artificial intelligence (AI) in pharmaceutical market covered in this report is segmented –
1) By Type: Small Molecule, Large Molecule
2) By Technology: Deep Learning, Natural Language Processing, Querying Method, Context-Aware Processing, Other Technologies
3) By Application: Clinical Trial Research, Drug Discovery, Research And Development, Other Applications
Subsegments:
1) By Small Molecule: Drug Discovery And Design, Lead Optimization For Small Molecule Compounds, Predictive Modeling For Pharmacokinetics And Toxicity, Virtual Screening Of Compound Libraries, Personalized Medicine Approaches For Small Molecule Therapies
2) By Large Molecule: Biologics Discovery And Development, Monoclonal Antibody Design, Protein Engineering And Optimization, Vaccine Development And Optimization, Predictive Models For Biopharmaceutical Efficacy And Safety.
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Who are the top competitors in the generative artificial intelligence (ai) in pharmaceutical market?
Major companies operating in the generative artificial intelligence (AI) in pharmaceutical market are Pfizer Inc., Johnson & Johnson, Roche Holding AG, Merck & Co. Inc., AbbVie Inc., Bayer AG, Sanofi S.A., Bristol-Myers Squibb Company, AstraZeneca PLC, Novartis AG, GlaxoSmithKline plc, Fujitsu Limited, Takeda Pharmaceutical Company Limited, Eli Lilly and Company, Amgen Inc., Gilead Sciences Inc., NVIDIA Corporation, Conduent Incorporated, XtalPi Inc., Insilico Medicine Inc., Numerate Inc., Atomwise Inc., BenevolentAI Limited
What significant trends should we anticipate in the generative artificial intelligence (ai) in pharmaceutical market over the forecast period?
Major companies operating in generative artificial intelligence (AI) in pharmaceutical market are developing new products, such as AI healthcare microservices, to streamline drug discovery processes. AI healthcare microservices are modular, cloud-based services that use artificial intelligence to improve healthcare functions such as drug discovery, medical imaging, and diagnostics. For instance, in March 2024, Nvidia Corporation, a US-based technology company, launched generative AI microservices. It features optimized NIM AI models and workflows with APIs for building cloud-native applications. It provides advanced imaging, natural language, and speech recognition, along with digital biology capabilities. The key tools included are Parabricks, MONAI, NeMo, Riva, and Metropolis are accessible as CUDA-X microservices, enhancing workflows in drug discovery and genomics.
Which regional trends are influencing the generative artificial intelligence (ai) in pharmaceutical market, and which area dominates the industry?
North America was the largest region in the generative artificial intelligence (AI) in the pharmaceutical market in 2024. The regions covered in the generative artificial intelligence (AI) in pharmaceutical market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Does The Generative Artificial Intelligence (AI) In Pharmaceutical Market Report 2025 Offer?
The generative artificial intelligence (ai) in pharmaceutical market research report from The Business Research Company offers global market size, growth rate, regional shares, competitor analysis, detailed segments, trends, and opportunities.
Generative artificial intelligence (AI) in pharmaceuticals leverages advanced algorithms and machine learning to design new drug compounds, predict molecular behaviors, and optimize drug discovery processes. It uses techniques such as deep learning and generative adversarial networks (GANs) to create novel molecular structures and simulate their interactions.
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