Artificial Intelligence (AI) in Drug Discovery Global Market Report 2024

The artificial intelligence (AI) in drug discovery market size has grown exponentially in recent years. It will grow from $1.37 billion in 2023 to $1.79 billion in 2024 at a compound annual growth rate (CAGR) of 30.8%. The growth observed in the historic period in the field of artificial intelligence (AI) in drug discovery can be attributed to several key factors. These include the growth in emerging markets, the rising prevalence of chronic diseases, the increased adoption of artificial intelligence for cost-efficient drug discovery, and the implementation of increasingly strict quality regulations for drug manufacturers.

The artificial intelligence (AI) in drug discovery market size is expected to see exponential growth in the next few years. It will grow to $4.71 billion in 2028 at a compound annual growth rate (CAGR) of 27.4%. Anticipated growth in AI for drug discovery is driven by government support, growing healthcare expenditure, and increased adoption of cloud-based applications. Trends include the integration of multi-omics data, AI in target selection and drug screening, establishment of AI innovation labs, heightened investments, and industry partnerships and collaborations.

The escalating demand for personalized medicine stands as a driving force behind the burgeoning growth of the artificial intelligence (AI) in drug discovery market. Personalized medicine, which tailors treatments based on individual genetic or protein knowledge, has surged in importance. AI's pivotal role spans various phases of clinical development and in the creation of new personalized health solutions. It significantly aids in identifying suitable intervention targets and evaluating their effectiveness. Notably, the US FDA's approval of 12 personalized medicines in 2022, representing about 34% of newly endorsed therapeutic molecular entities, attests to this surge. The heightened demand for personalized medicine is thereby fueling the expansion of the AI in drug discovery market.

A substantial catalyst propelling the artificial intelligence (AI) in drug discovery market growth is the mounting demand to streamline the drug discovery process. Conventionally, the identification and optimization of molecules through animal models typically span three to five years before human evaluation. However, AI-based startups have shown the ability to identify and design new drugs within days or months. An illustrative example is the AlphaFold Protein Structure Database's expansion in December 2021. Developed by Google DeepMind in collaboration with EMBL’s European Bioinformatics Institute (EMBL-EBI), this database added 440k meticulously curated protein structures from Swiss-Prot. This significant expansion more than doubled the database's size to over 800k structures, accelerating the drug discovery process remarkably. This substantial reduction in the overall duration of drug discovery procedures is a key driver underpinning the growth of the AI in drug discovery market.

Major players in the AI drug delivery sector are forging strategic collaborations to delve deeper into drug discovery leveraging AI, a move that's elevating their position within the artificial intelligence in drug discovery market. Take Atomwise, a US-based AI systems company, which partnered with Sanofi in August 2022. This collaboration aims to identify and explore up to five pharmacological targets utilizing Atomwise's AI-driven AtomNet technology. To facilitate the discovery of lead compounds for Sanofi's exclusive targets, Atomwise received an initial payment of $20 million from Sanofi, a prominent French pharmaceutical and healthcare company.

Major corporations are making significant investments in entities operating within the artificial intelligence (AI) in drug discovery domain. These investments aim to facilitate the identification and design of novel therapies, ultimately offering these models to other pharmaceutical firms. Given that drug discovery is both capital-intensive and time-consuming, such strategic investments provide vital funding for research and development of new drugs. This funding often serves as a catalyst for these companies to propel their drug discovery initiatives, expediting the introduction of new treatments into the market. For instance, in July 2023, Nvidia, a leading US-based software company, made a $50 million investment in Recursion Pharmaceuticals, a US-based biotech firm harnessing artificial intelligence (AI) for drug discovery. This infusion of capital is poised to empower Recursion in accelerating the development of its AI foundation models for biology and chemistry by leveraging Nvidia's cloud services.

In December 2022, Tecnotree Corporation, a Finnish telecommunications company, successfully acquired CognitiveScale for a total investment of $6 million. This strategic acquisition is expected to significantly boost Tecnotree's AI capabilities, presenting potential opportunities for the pharmaceutical industry. Leveraging these enhanced AI capabilities, Tecnotree aims to explore and develop innovative AI-powered solutions for drug discovery and advancement. CognitiveScale, a reputable AI software company based in the United States, will contribute to Tecnotree's strategic vision in this evolving landscape.

Major companies operating in the artificial intelligence (AI) in drug discovery market report are IBM Corporation, Microsoft Corporation, NVIDIA Corporation, Exscientia, Alphabet, Atomwise Inc., Insilico Medicine, Owkin Inc., Xtalpi Inc., Cloud Pharmaceuticals, Shanghai Pharmaceuticals, Standigm, Indegene, Intuition Systems, Innoplexus, Takeda Pharmaceutical Company Ltd., RxPrism, Otsuka Pharmaceutical Co. Ltd., China National Pharmaceutical Group Co., Ltd., Jiangsu Hengrui Medicine Co., Ltd., Cipla Limited, Aurobindo Pharma Limited, Dr. Reddy’s Laboratories Ltd., Sun Pharma, Tricog Health Services Pvt. Ltd., Alliance Pharm Pte Ltd., GSK Australia , CytoReason, IIPharma, StoneWise, Adagene, GT Apeiron Therapeutics, Xbiome, Accutar Biotech, DeepMind, Renalytix AI, Iktos, Ipsen Pharma, Galderma S.A., BenevolentAI, Deepflare, Novartis, Gero, Ardigen, Botkin, Care Mentor AI , Diagnocat, GNS Healthcare, Merck & Co., Apotex, Pfizer, Gilead Sciences, Roche, Bayer, AbbVie Inc., GlaxoSmithKline, AstraZeneca, Amgen, Sanofi Pasteur, Abbott Laboratories, Janssen Pharmaceutica, Teva Canada, Accord Healthcare Inc., Acerus Pharmaceuticals Corporation, AA Pharma Inc., Sanfer, Siegfried Rhein, Atomwise, Inc., Bioage, NuMedii, Envisagenics, Aria Pharmaceuticals, Verge Genomics, Berg LLC, Deep Genomics, Cyclica , IQVIA, Quris, GE Healthcare, Avanade , Group42 Holding Ltd., Ilara Health, Adcock Ingram , Johnson & Johnson, Eurolab , Ranbaxy (SA) (Pty) Ltd., Aspen, Rology, hearX Group, DilenyTech.

North America was the largest region in the artificial intelligence (AI) in drug discovery market in 2023. Western Europe was the second largest region in the global artificial intelligence (AI) in drug discovery market share. The regions covered in the artificial intelligence (AI) in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (AI) in drug discovery market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Canada, Spain.

The primary technologies employed in AI for drug discovery are deep learning and machine learning. Deep learning is a technique within machine learning and AI that emulates how humans acquire knowledge. Data science, encompassing statistics and predictive modeling, integrates deep learning as a crucial component. Drug discovery involves various types of drugs, including small molecules and large molecules, and encompasses different therapeutic approaches such as c and others. The implementation of AI in drug discovery is seen across various end-users, including pharmaceutical companies, biopharmaceutical companies, academic and research institutes, among others.

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

The artificial intelligence (AI) in drug discovery market includes revenues earned by entities by offering AI for drug discovery. Artificial Intelligence (AI) for drug discovery is a technology that uses a simulation of the human intelligence process by machines to tackle complex problems in the drug discovery process. It helps to find new molecules to identify drug targets and develop personalized medicines in the pharmaceutical industry. 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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