Machine Learning (ML) in The Pharmaceutical Industry: Core Growth Enabler in the Transformative Role Of Artificial Intelligence (AI) And Machine Learning (ML) In The Pharmaceutical Industry Market, 2025

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What Will the Machine Learning (ML) in The Pharmaceutical Industry Industry Market Size Be by 2025?
The pharmaceutical industry's market size for machine learning (ML) has notably increased in the last few years. It is expected to reach a size of $4.08 billion in 2025, up from $3.02 billion in 2024 - an impressive compound annual growth rate (CAGR) of 34.9%. Elements contributing to this growth in the past include a higher acceptance of federated learning, faster timelines for drug discovery, improved drug safety and pharmacovigilance, along with the widening range of applications for precision medicine.

What's the Long-Term Growth Forecast for the Machine Learning (ML) in The Pharmaceutical Industry Market Size Through 2029?
In the coming years, an explosive growth is predicted for the machine learning (ML) market in the pharmaceutical industry. It is estimated to expand to a staggering "$13.76 billion by 2029 with a compound annual growth rate (CAGR) of 35.5%. This projected growth in the forecast period can be attributed to the ever-increasing complexity of biological data, advancements in computational power, heightened industry awareness and education, and a focus on patient-centric healare solutions. Major upcoming trends during this forecast period include AI-pharma partnerships, collaborations, drug-agnostic therapies, the interoperability of ML systems, decentralized clinical trials, and the discovery of biomarkers driven by AI.

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What Are the Key Growth Drivers Fueling the Machine Learning (ML) in The Pharmaceutical Industry Market Expansion?
The upsurge in the acceptance and use of artificial intelligence (AI) is propelling machine learning (ML) forward in the pharmaceutical sector. AI is essentially software that emulates human thought processes to carry out intricate tasks like analysis, logical reasoning, and learning. ML, on the other hand, is a component of AI that deploys data-trained algorithms to create models capable of executing complex tasks. AI and ML have found significant applications in pharmaceutical technology and drug delivery design, offering quick solutions to intricate problems. These technologies can revolutionize the drug delivery process, bolster decision-making tools, and manage vast data quantities for better decision-making efficacy. Citing an example, Forbes, a US business magazine, reported that about 432,000 UK firms, or one in six, had integrated at least one AI technology by June 2023. Moreover, 68% of large businesses, 33% of medium businesses, and 15% of small businesses have adopted at least one AI technology. Consequently, the escalating integration of artificial intelligence (AI) will fuel the growth of machine learning (ML) in the pharmaceutical sector.

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What Trends Will Shape the Machine Learning (ML) in The Pharmaceutical Industry Market Through 2029 and Beyond?
Leading businesses in the pharmaceutical sector who specialize in machine learning (ML) are concentrating their efforts on crafting user-friendly software systems like drug discovery software, to bolster their drug discovery operations. The term drug discovery software is an umbrella term for various dedicated tools and platforms utilized in identifying and formulating new pharmaceutical drugs. To illustrate, in December 2023, the US pharmaceutical company, Merck & Co. Inc., introduced the AIDDISON drug discovery software, considered the inaugural software-as-a-service platform that combines drug discovery and synthesis by applying generative AI, machine learning, and computer-aided drug design. Through this platform, labs can pick out suitable drug candidates from a massive chemical space, virtually screen substances from a potential 60 billion chemical targets and assess synthesis pathways for safer, more economically-efficient, and higher-yield drug production.

How Is the Machine Learning (ML) in The Pharmaceutical Industry Market Segmented?
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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Which Companies Are Leading the Charge in Machine Learning (ML) in The Pharmaceutical Industry Market Innovation?
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

Which Regions Are Leading the Global Machine Learning (ML) in The Pharmaceutical Industry Market in Revenue?
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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