Machine Learning (ML) in the Pharmaceutical Industry Global Market Report 2024

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 the increased adoption of federated learning, accelerated drug discovery timelines, enhanced drug safety and pharmacovigilance, and the 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 forecasted growth in the upcoming period can be attributed to several factors, including the increasing complexity of biological data, the growing computational power available, a rise in industry awareness and education, and the shift towards patient-centric healthcare solutions. Major trends expected during this period include partnerships and collaborations between AI and pharmaceutical companies, the development of drug-agnostic therapies, efforts to improve the interoperability of machine learning systems, the implementation of decentralized clinical trials, and the use of AI for biomarker discovery.

The growing use of artificial intelligence (AI) is fueling the expansion of machine learning (ML) in the pharmaceutical sector. AI, which mimics human cognition to execute intricate tasks such as analysis, reasoning, and learning, is a key driver behind ML, a subset of AI that employs algorithms trained on data to generate models capable of performing complex tasks. AI and ML have been harnessed in pharmaceutical technology and drug delivery design, providing accelerated solutions to intricate challenges. They hold the potential to revolutionize the drug delivery process, improve decision-making tools, and manage vast amounts of data for more effective decision-making. For example, as reported by Forbes in June 2023, around 432,000 UK organizations, or one in six, have adopted at least one AI technology. Furthermore, 68% of large businesses, 33% of medium-sized businesses, and 15% of small businesses have adopted at least one AI technology. Consequently, the increasing adoption of AI is poised to propel ML in the pharmaceutical industry.

Key players in the machine learning (ML) sector of the pharmaceutical industry are concentrating on creating user-friendly software platforms, including drug discovery software, to enhance their drug discovery capabilities. Drug discovery software encompasses various specialized tools and platforms utilized in identifying and developing new pharmaceutical drugs. For instance, in December 2023, Merck & Co. Inc., a US-based pharmaceutical company, introduced the AIDDISON drug discovery software. This software-as-a-service platform is the first of its kind, integrating drug discovery and synthesis through generative AI, ML, and computer-aided drug design. AIDDISON allows laboratories to pinpoint suitable drug candidates within a vast chemical space, virtually screen compounds from over 60 billion chemical targets, and assess synthesis routes for safer, more cost-effective, and higher-yield drug production.

In July 2023, BioNTech SE, a Germany-based biopharmaceutical company, acquired InstaDeep for $541 million. This acquisition is anticipated to enhance BioNTech's leading position in AI-powered drug discovery, design, and development. InstaDeep, a UK-based technology company, provides a variety of AI solutions and machine learning services tailored for the pharmaceutical sector.

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.

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. The countries covered in the machine learning (ml) in the pharmaceutical industry market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Machine learning (ML) in the pharmaceutical industry market involves the application of artificial intelligence (AI) algorithms and techniques to enhance drug discovery, development, and manufacturing processes. Regulatory compliance and overcoming challenges related to data quality, research gaps, and regulatory uncertainty are essential for implementing ML solutions in this industry.

The primary components of machine learning in the pharmaceutical industry are solutions and services. Solutions are applications or systems that use ML algorithms to tackle specific challenges or tasks in the pharmaceutical sector. These solutions can be deployed on the cloud or on-premise and cater to enterprises of various sizes, including small and medium enterprises (SMEs) and large enterprises.

The machine learning (ML) in the pharmaceutical industry market research report is one of a series of new reports that provides machine learning (ML) in the pharmaceutical industry market statistics, including machine learning (ML) in the pharmaceutical industry global market size, regional shares, competitors with machine learning (ML) in the pharmaceutical industry market share, detailed machine learning (ML) in the pharmaceutical industry market segments, market trends, and opportunities, and any further data you may need to thrive in the machine learning (ML) in the pharmaceutical industry. This machine learning (ML) in the pharmaceutical industry market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The machine learning (ML) in the pharmaceutical industry market consists of revenues earned by entities by providing components of machine learning (ML) in the pharmaceutical industry market such as solutions and services. The market value includes the value of related goods sold by the service provider or included within the service offering. The machine learning (ML) in the pharmaceutical industry market also includes sales of central processing units (CPUs), random access memory, storage systems, and graphics processing units (GPUs). Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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