Deep Learning in Drug Discovery and Diagnostics Market Report 2025

This Deep Learning in Drug Discovery and Diagnostics market report provides a comprehensive analysis of the market’s characteristics, size, and growth, including segmentation, regional and country-level breakdowns, competitive landscape, market shares, trends, and strategies. It also tracks historical and forecasted market growth across various geographies.

The deep learning in drug discovery and diagnostics market size has grown exponentially in recent years. It will grow from $8.21 billion in 2024 to $10.58 billion in 2025 at a compound annual growth rate (CAGR) of 28.8%. The growth in the historic period can be attributed to increased investment in AI research, growing demand for personalized medicine, increased funding from public and private sectors, rise in chronic diseases and complex conditions, and growing adoption of electronic health records.

The deep learning in drug discovery and diagnostics market size is expected to see exponential growth in the next few years. It will grow to $28.82 billion in 2029 at a compound annual growth rate (CAGR) of 28.5%. The growth in the forecast period can be attributed to improved diagnostic accuracy, growing collaboration between tech companies and pharmaceutical firms, progress in explainable AI (xai) for better model transparency, increased emphasis on real-world evidence (RWE), and expansion into emerging markets. Major trends in the forecast period include the adoption of AI technologies, advancements in computational power, integration of big data, development of novel deep learning architectures, and expansion of cloud-based platforms for AI.

The increasing demand for personalized medicine is expected to drive the growth of the deep learning market in drug discovery and diagnostics. Personalized medicine customizes treatment and interventions based on an individual's genetic, environmental, and lifestyle factors to improve effectiveness and reduce side effects. This demand is fueled by advancements in genomics and data analytics, which allow for more precise treatments tailored to individual patient profiles. Deep learning enhances personalized medicine by analyzing complex biological data to discover unique biomarkers and predict patient responses more accurately. For example, in February 2024, the Personalized Medicine Coalition reported that the FDA approved 16 new personalized therapies for rare diseases in 2023, up from six in 2022. This growing interest in personalized medicine is driving the expansion of deep learning in drug discovery and diagnostics.

Key players in the deep learning drug discovery and diagnostics market are focusing on advancing high-performance computing technologies, such as supercomputers, to boost innovation through enhanced performance and efficiency in complex tasks and AI applications. Improvements in supercomputers facilitate deep learning by accelerating complex data analysis and simulations, which helps in identifying drug candidates more quickly and improving diagnostic accuracy. For instance, in November 2022, Hewlett-Packard Enterprise, a US-based IT company, launched the HPE Cray EX and HPE Cray XD supercomputers. These systems offer powerful performance and scalable AI capabilities in a more compact and cost-effective design, aimed at expediting drug discovery and disease treatment. They enable researchers and pharmaceutical labs to gain deeper insights into chemical interactions, which promotes the development of new therapies for both challenging and emerging diseases.

In February 2024, Ginkgo Bioworks Holdings Inc., a US-based biotech company specializing in genetic engineering, acquired key assets from Reverie Labs for an undisclosed sum. This acquisition includes Reverie's infrastructure and software for training large-scale AI foundation models, which Ginkgo intends to leverage to enhance its AI and machine learning (ML)-driven discovery services and accelerate the development of next-generation biological foundation models. Reverie Labs Inc. is a US-based company that has developed and utilized AI and ML tools to expedite drug discovery.

Major companies operating in the deep learning in drug discovery and diagnostics market are Google Inc., Microsoft Corporation, International Business Machines Corporation, NVIDIA Corporation, Zebra Medical Vision Ltd, Tempus Labs Inc., Nanostring Technologies Inc., Owkin Inc., Insilico Medicine Inc., SOPHiA GENETICS SA, Qureai Technologies Pvt Ltd, H2Oai Inc., Arterys Inc., Deep Genomics Inc., GNS Healthcare Inc., MedAware Systems Inc., PathAI Inc., Kheiron Medical Technologies Ltd, CureMetrix Inc., OncoImmunity AS, Proscia Inc., BenevolentAI Ltd, BioXcel Therapeutics Inc.

North America was the largest region in the deep learning in drug discovery and diagnostics market in 2023. The regions covered in the deep learning in drug discovery and diagnostics market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the deep learning in drug discovery and diagnostics market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Deep learning in drug discovery and diagnostics involves utilizing advanced neural networks and artificial intelligence (AI) to interpret complex biological and chemical data, allowing for the prediction of drug interactions, identification of disease patterns, and advancement of personalized medicine. This approach enhances drug discovery and diagnostics by increasing prediction accuracy, automating data processing, and facilitating personalized treatments through sophisticated data analysis.

Key applications of deep learning in this field include drug discovery, diagnostics, forensic interventions, and more. In drug discovery, deep learning algorithms analyze biological data to predict the effectiveness of drug compounds, accelerating the identification of potential candidates and side effects earlier in the research process. These drugs include small molecules and biologics, with end-use industries ranging from pharmaceutical and biotechnology companies to contract research organizations (CROs) and healthcare information technology (IT).

The deep learning in drug discovery and diagnostics market research report is one of a series of new reports that provides deep learning in drug discovery and diagnostics market statistics, including deep learning in drug discovery and diagnostics industry global market size, regional shares, competitors with a deep learning in drug discovery and diagnostics market share, detailed deep learning in drug discovery and diagnostics market segments, market trends and opportunities, and any further data you may need to thrive in the deep learning in drug discovery and diagnostics industry. This deep learning in drug discovery and diagnostics 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 deep learning in drug discovery and diagnostics market consists of revenues earned by entities by providing services such as developing and integrating deep learning algorithms, analyzing large-scale biological and chemical data, offering software solutions and platforms, and consulting on AI-driven drug discovery and diagnostic strategies. The market value includes the value of related goods sold by the service provider or included within the service offering. The deep learning in drug discovery and diagnostics market also includes sales of software platforms and tools, machine learning frameworks, data analytics solutions, cloud-based computing services, hardware accelerators, and AI-driven diagnostic devices. 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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