Overview and Scope
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.
Sizing and Forecast
The machine learning in the pharmaceutical industry market size has grown exponentially in recent years. It will grow from $2.22 billion in 2023 to $3.02 billion in 2024 at a compound annual growth rate (CAGR) of 36.1%. The growth in the historic period can be attributed to increased adoption of federated learning, accelerated drug discovery timelines, enhanced drug safety and pharmacovigilance, expansion of precision medicine applications.
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Segmentation & Regional Insights
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
North America was the largest region in the machine learning in the pharmaceutical industry market in 2023. 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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Major Driver Impacting Market Growth
The increasing adoption of artificial intelligence (AI) is driving machine learning (ML) in the pharmaceutical industry. AI is computer software that mimics human cognition to perform complex tasks, such as analyzing, reasoning, and learning, while ML is a subset of AI that uses algorithms trained on data to produce models that can perform complex tasks. AI and ML has been utilized in pharmaceutical technology and drug delivery design, offering expedited solutions to complex challenges. It has the potential to transform the drug delivery process, enhance decision-making tools, and handle large quantities of data for a more effective decision. For instance, in June 2023, according to Forbes, a US-based business magazine, approximately 432,000 UK organizations, or one in six, have adopted at least one AI technology. Further, at least one AI technology has been adopted by 68% of large businesses, 33% of medium-sized businesses, and 15% of small businesses. Therefore, the increasing adoption of artificial intelligence (AI) will drive machine learning (ML) in the pharmaceutical industry.
Key Industry Players
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
The machine learning (ml) in the pharmaceutical industry market report table of contents includes:
1. Executive Summary
2. Market Characteristics
3. Market Trends And Strategies
4. Impact Of COVID-19
5. Market Size And Growth
6. Segmentation
7. Regional And Country Analysis
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27. Competitive Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
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