Top Growth Trends in the Machine Learning (ML) in The Pharmaceutical Industry Market: Key Insights and Opportunities for 2025-2034
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What fueled the previous growth in the Machine Learning (ML) in The Pharmaceutical Industry market?
The market size for machine learning (ML) applications in the pharmaceutical industry has experienced remarkable growth lately. The anticipated expansion from $3.02 billion in 2024 to $4.11 billion in 2025, with a compound annual growth rate (CAGR) of 35.9%, demonstrates this trend. Factors contributing to this surge during the historic period include a higher level of federated learning usage, hastened timelines for drug discovery, improved drug safety and pharmacovigilance, and the broadening scope of precision medicine applications.
What will be the machine learning (ml) intelligent process automation market size in the future?
In the coming years, it is anticipated that the market size of machine learning (ML) in the pharmaceutical industry will undergo significant expansion. It’s expected to reach $13.99 billion by 2029, with a compound annual growth rate (CAGR) of 35.8%. This projected growth in the forecast period can be credited to factors such as the rising complexity of biological data, increased computational capabilities, heightened industry awareness and education, as well as patient-oriented healthcare solutions. Notable trends that will be seen in the forecast period consist of collaborations and partnerships between AI and pharma, therapies that are drug-neutral, interoperable ML systems, decentralized clinical tests, and the discovery of biomarkers that are driven by AI.
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What main drivers are fueling expansion in the machine learning (ml) in the pharmaceutical industry market?
The pharmaceutical industry is experiencing a surge in the utilization of machine learning (ML), driven by the growing acceptance of artificial intelligence (AI). AI, a type of computer software that emulates human cognitive processes to carry out complex actions such as analysis, reasoning, and learning. On the other hand, ML is part of AI that employs data-trained algorithms to create models capable of performing complex functions. AI and ML have found their applications in pharmaceutical tech and drug delivery designs, providing speedy resolutions to intricate problems. They have the ability to revolutionize the drug delivery mechanism, strengthen decision-making systems, and manage vast amounts of data for improved decision-making efficiency. For example, in June 2023, Forbes, a US-based business periodical, reported that approximately 432,000 UK firms, or one in six, have implemented at least one AI technology. Additionally, at least one AI technology has been implemented by 68% of large enterprises, 33% of medium-sized enterprises, and 15% of small enterprises. As a result, the growing acceptance of artificial intelligence (AI) is set to spur machine learning (ML) in the pharmaceutical sector.
What key areas define the segmentation of the global machine learning (ml) in the pharmaceutical industry market?
The machine learning (ML) in the pharmaceutical industry market covered in this report is segmented –
1) By Component: Solution, Services
2) By Component: Cloud, On-premise
3) By Enterprise Size: Small and Medium Enterprises (SMEs), Large Enterprises
Subsegments:
1) By Solution: Drug Discovery Platforms, Predictive Analytics Tools, Clinical Trial Optimization Solutions, Patient Data Management Systems, Personalized Medicine Applications
2) By Services: Consulting Services, Implementation And Integration Services, Data Analysis And Modeling Services, Training And Support Services, Managed Services
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Who are the dominant players expanding their reach in the machine learning (ml) in the pharmaceutical industry market?
Major companies operating in the machine learning (ML) in the pharmaceutical industry market report are Amazon.com Inc., Alphabet Inc., Microsoft Corporation, Dell Technologies Inc., Hitachi Ltd., International Business Machines Corporation, Cisco Systems Inc., Oracle Corporation, Honeywell International Inc., Hewlett Packard Enterprise, NVIDIA Corporation, Thales SA, Atos SE, Hexagon AB, Palantir Technologies Inc., Verient Systems Inc., Alteryx Inc., Comet ML Inc., GAVS Technologies, NEC Corporation, Veritone Inc., H2O.ai Inc., Sparkcognition Inc., Akira AI, Deep Genomics Inc., Cloud Pharmaceuticals Inc., Atomwise Inc., Cyclica Inc., BioSymetrics Inc., Neptune Labs
How are evolving market trends shaping machine learning (ml) in the pharmaceutical industry Strategies?
Leading organizations involved in machine learning (ML) within the pharmaceutical sector are prioritizing the development of user-friendly software solutions like drug discovery software to enhance their drug discovery potential. The term drug discovery software incorporates a range of unique tools and platforms utilized in the identification and formulation of new pharmaceutical drugs. For example, in December 2023, Merck & Co. Inc., a pharmaceutical firm based in the US, introduced the AIDDISON drug discovery software. This innovative software-as-a-service platform is the first to merge drug discovery and synthesis using generative AI, machine learning, and computer-aided drug design. This platform empowers labs to pinpoint promising drug candidates in an expansive chemical environment, virtually analyze compounds from more than 60 billion potential chemical targets, and determine synthesis paths for safer, more economical, and higher producing drug manufacturing.
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Which regions are emerging as leaders in the machine learning (ml) in the pharmaceutical industry market?
North America was the largest region in the machine learning in the pharmaceutical industry market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning (ML) in the pharmaceutical industry market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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