Machine Learning (ML) in The Pharmaceutical Industry Market Projected at $13.99 Billion by 2029 | Strategic Insights and Forecast Data
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How Has the Machine Learning (ML) in The Pharmaceutical Industry Market Size Changed, over the years?
In recent years, the market size for machine learning (ML) in the pharmaceutical sector has experienced an unprecedented surge. It is projected to escalate from $3.02 billion in 2024 to $4.11 billion in 2025, boasting a compound annual growth rate (CAGR) of 35.9%. The remarkable growth witnessed during the historical period can be credited to the broader acceptance of federated learning, faster drug discovery procedures, improved drug security and pharmacovigilance, and the progression of precision medicine applications.
How Much Will the Machine Learning (ML) in The Pharmaceutical Industry Market Be Worth in 2029?
The market size for machine learning (ML) in the pharmaceutical industry is predicted to experience significant expansion in the coming years. The industry is forecasted to reach a worth of $13.99 billion in 2029, with a compound annual growth rate (CAGR) of 35.8%. This anticipated growth during the projected period could be due to the rising intricacy of biological data, the expansion of computational capacity, increased industry knowledge and education, as well as patient-focused healthcare solutions. Key market trends for the forecasted period encompass alliances and cooperations between AI and pharma, drug-neutral treatments, the compatibility of ML systems, the distribution of clinical trials, and biomarker discovery driven by AI.
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Which is the Largest Company 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
What Are the Main Market Drivers in the Machine Learning (ML) in The Pharmaceutical Industry Industry?
The surge in the utilization of artificial intelligence (AI) is propelling the growth of machine learning (ML) within the pharmaceutical sector. AI, which represents computer software that emulates human cognitive abilities to carry out intricate operations such as analyzing, reasoning, and learning, sees ML as its subdomain. Machine learning employs data trained algorithms to generate models capable of executing comprehensive tasks. The application of AI and ML in the sphere of pharmaceutical technology and drug delivery design has expedited solutions to complex challenges. Their potential to revolutionize the drug delivery process, improve decision-making apparatus, and manage vast amounts of data for efficient decision-making is significant. For example, as per Forbes – a US-based business publication, approximately 432,000 UK organizations, or one in six, have embraced at least a single AI technology as of June 2023. Moreover, at least one AI technology has been integrated by 68% of major businesses, 33% of medium-scale businesses, and 15% of small businesses. Hence, the heightened adoption of artificial intelligence (AI) will further stimulate the progress of machine learning (ML) in the pharmaceutical domain.
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How Is the Machine Learning (ML) in The Pharmaceutical Industry Market Segments Structured?
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
What Strategic Trends Are Transforming the Machine Learning (ML) in The Pharmaceutical Industry Market?
Leading organizations in the pharmaceutical sector utilizing machine learning (ML) are concentrating on the advancement of user-friendly software platforms, like drug discovery software, to enhance their proficiency in drug discovery. This software for drug discovery is a comprehensive term that includes different specialized tools and platforms that are employed in the process of discovering and developing new pharmaceutical drugs. For example, in December 2023, Merck & Co. Inc., a pharmaceutical firm based in the US, debuted the AIDDISON drug discovery software. This was the first platform offering software-as-a-service that combines drug discovery and synthesis utilizing generative AI, machine learning, and computer-aided drug design. This platform facilitates laboratories in identifying appropriate drug candidates among a vast chemical space, virtually screening compounds from over 60 billion chemical targets, and examining synthesis routes for safer, more affordable, and higher-yield drug production.
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Which Global Regions Offer the Highest Growth 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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This Report Delivers Insight On:
1. How big is the machine learning (ml) in the pharmaceutical industry market, and how is it changing globally?
2. Who are the major companies in the machine learning (ml) in the pharmaceutical industry market, and how are they performing?
3. What are the key opportunities and risks in the machine learning (ml) in the pharmaceutical industry market right now?
4. Which products or customer segments are growing the most in the machine learning (ml) in the pharmaceutical industry market?
5. What factors are helping or slowing down the growth of the machine learning (ml) in the pharmaceutical industry market?
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