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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.

The machine learning in the pharmaceutical industry market size is expected to see exponential growth in the next few years. It will grow to $10.2 billion in 2028 at a compound annual growth rate (CAGR) of 35.7%. The growth in the forecast period can be attributed to increasing complexity of biological data, growing computational power, increasing industry awareness and education, patient-centric healthcare solutions. Major trends in the forecast period include AI-pharma partnerships and collaborations, drug-agnostic therapies, interoperability of ML systems, decentralized clinical trials, AI-driven biomarker discovery.

Market Overview -
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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Transformative Role Of Artificial Intelligence (AI) And Machine Learning (ML) In The Pharmaceutical Industry
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.

Competitive Landscape -
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

Cutting-Edge AI-Integrated Platforms Unveiled By Major Players In The Pharmaceutical Industry
Major companies operating in machine learning (ML) in the pharmaceutical industry are focusing on developing user-friendly software platforms, such as drug discovery software, to improve their drug discovery capabilities. Drug discovery software is a broad term encompassing a variety of specialized tools and platforms used throughout the process of identifying and developing new pharmaceutical drugs. For instance, in December 2023, Merck & Co. Inc., a US-based pharmaceutical company, launched the AIDDISON drug discovery software, which is the first software-as-a-service platform that integrates drug discovery and synthesis using generative AI, machine learning, and computer-aided drug design. This platform enables laboratories to identify suitable drug candidates in a vast chemical space, virtually screen compounds from a universe of over 60 billion chemical targets, and evaluate synthesis routes for safer, more cost-effective, and higher-yield drug manufacturing.

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Key Segments -

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

Key highlights covered in the report -

1. Detailed market size forecast and historical data analysis
2. Key drivers influencing market growth
3. Identification of upcoming trends and potential opportunities in the market
4. Analysis of major players strategies, to understand competitive dynamics and market positioning
5. Evaluation of regional dynamics

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