Machine Learning (ML) in The Pharmaceutical Industry Market Growth Forecast: Exploring Trends and Opportunities for the Next Decade
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What Growth Opportunities are Expected to Drive the Machine Learning (ML) in The Pharmaceutical Industry Market’s CAGR Through 2034?
The market size for machine learning (ML) within the pharmaceutical industry has seen tremendous growth recently. The projection is that it will escalate from $3.02 billion in 2024 to $4.11 billion in 2025, exhibiting a compound annual growth rate (CAGR) of 35.9%. The historical growth trajectory is mainly due to the rising adoption of federated learning, speedier drug discovery timelines, improved drug safety and pharmacovigilance, and the broadening scope of precision medicine applications.
The market size of machine learning (ML) in the pharmaceutical industry is anticipated to witness tremendous growth in the forthcoming years. The market is predicted to rise to $13.99 billion in 2029, demonstrating a compound annual growth rate (CAGR) of 35.8%. The predicted growth in the forecast timeline is linked to the escalating intricacy of biological data, enhanced computational capacities, increasing industry cognizance and education, and patient-oriented healthcare solutions. The forecast period is expected to observe major trends such as AI-pharma alliances and collaborations, drug-agnostic treatments, ML system interoperability, decentralized clinical trials, and biomarker discovery driven by AI.
What Key Drivers Are Accelerating the Growth of the machine learning (ml) in the pharmaceutical industry Market During the Forecast Period?
The escalating acceptance of artificial intelligence (AI) is propelling the use of machine learning (ML) in the pharmaceutical sector. AI essentially functions as computer software that simulates human thought processes to carry out intricate tasks, such as data analysis, reasoning, and learning. ML, an offshoot of AI, employs algorithms that are trained on data to create models capable of performing intricate functions. The application of AI and ML in the fields of pharmaceutical technology and drug delivery design has resulted in quicker solutions for complex issues. There is potential for these technologies to revolutionize drug delivery processes, improve decision-making tools and manage high volumes of data for more effective decision-making. For instance, Forbes, an American business magazine, reported in June 2023, that about 432,000 UK entities, or one-sixth of all organizations, have integrated at least one form of AI technology. Furthermore, at least one AI technology has been integrated by 68% of large businesses, one-third of medium-sized businesses, and 15% of small businesses. Thus, the ongoing surge in artificial intelligence (AI) adoption will continue to stimulate machine learning (ML) within the pharmaceutical industry.
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What Are the Leading Industry Players Dominating 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._x000D_
• Alphabet Inc._x000D_
• Microsoft Corporation_x000D_
• Dell Technologies Inc._x000D_
• Hitachi Ltd._x000D_
What Are the Latest Trends Leading to Disruption in the Machine Learning (ML) in The Pharmaceutical Industry Market?
Leading firms in the machine learning sector within the pharmaceutical industry are concentrating their efforts on creating user-oriented software platforms, such as drug discovery software, to enhance their drug discovery potential. Drug discovery software signifies a wide range of tools and platforms that are utilised across the board in the process of finding and developing new pharmaceutical drugs. For example, in December 2023, Merck & Co. Inc., a pharmaceutical company based in the United States, rolled out the AIDDISON drug discovery software. This platform, the first software-as-a-service delivering drug discovery and synthesis integration through generative AI, machine learning, and computer-aided drug design, empowers labs to pinpoint appropriate drug candidates within an expansive chemical universe, virtually screening compounds from over 60 billion chemical targets, and contemplating synthesis routes for safer, more economical, and higher-yield drug production.
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Which Key Segments Stand Out in Understanding the Composition of the 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
Which Regions Are Significant to the Growth of 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.
What Are the Core Features That Define the Machine Learning (ML) in The Pharmaceutical Industry Market?
Machine learning (ML) in the pharmaceutical industry market refers to the use of artificial intelligence (AI) algorithms and techniques. They are used to improve various aspects of drug discovery, development, and manufacturing processes. The implementation of ML solutions in the pharmaceutical industry requires careful regulatory compliance and addressing potential challenges related to data quality, research gaps, and regulatory uncertainty.
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