Lowest Price Guaranteed From USD 4,799
Companies Covered
420
Pages
420
View Count
14433
The deep learning market (for healthcare and drug discovery) is estimated to be $34.5 billion in 2023 and is expected to grow at a CAGR of 21.9% during the forecast period.
Since the mid-twentieth century, computing devices have continually been explored for applications beyond mere calculations, to emerge as machines that possess intelligence. These targeted efforts have led to the emergence of artificial intelligence, the next-generation simulator that employs programmed machines possessing the ability to comprehend data and execute the instructed tasks. The progress of artificial intelligence can be attributed to machine learning, a field of study that imparts computers with the ability to think without being explicitly programmed. Deep learning is a complex machine learning algorithm that uses a neural network of interconnected nodes / neurons in a multi-layered structure, thereby enabling the interpretation of large volumes of unstructured data to generate valuable insights, making it a promising approach for big data analysis. Owing to the distinct characteristic of deep learning algorithm to imitate the human brain, it is currently being deployed in the life sciences industry, primarily for the purposes of drug discovery and diagnostics. Within the healthcare market, the primary application of deep learning is in diagnostics. Considering the challenges associated with drug discovery and drug development, such as the high attrition rate and increased financial burden, deep learning has been found to improve the overall drug discovery productivity. Recent advancements in the deep learning market have demonstrated its potential in other healthcare-associated segments, such as medical imaging, molecular profiling, virtual screening and data analysis. Driven by the ongoing pace of innovation and the profound impact of this field of computational medicine, deep learning market in healthcare and drug discovery is anticipated to witness substantial market growth during the forecast period.
![]() |
![]() |
![]() |
The Deep Learning in Drug Discovery Market and Deep Learning in Diagnostics Market (2nd Edition), 2023-2035: Distribution by Therapeutic Area (Oncological Disorders, Infectious Diseases, Neurological Disorders, Immunological Disorders, Endocrine Disorders, Cardiovascular Disorders, Respiratory Disorders, Eye Disorders, Musculoskeletal Disorders, Inflammatory Disorders and Other Disorders) and Key Geographical Regions (North America, Europe, Asia Pacific and Rest of the World): Industry Trends and Global Forecasts, 2023-2035 market report features an extensive study of the current market landscape, market size, and future opportunities for the deep learning market within the healthcare industry. Further, the market report highlights the efforts of several stakeholders engaged in this rapidly emerging segment of the pharmaceutical industry. Key takeaways of the deep learning market report are briefly discussed below.
The use of deep learning in drug discovery has the potential to reduce capital requirements and the failure-to-success ratio, as algorithms are better equipped to analyze large datasets. Similarly, in diagnostics market, deep learning technology can be used to assist medical professionals in medical imaging and interpretation. This enables quick and efficient diagnosis of disease indications at an early stage.
In the last decade, the healthcare industry has witnessed an inclination towards the adoption of information services and digital analytical solutions. This can be attributed to the fact that companies have recently shifted towards high-resolution medical images and electronic health and medical records, generating large and complex data, referred to as big data. In order to analyze such large datasets, efficient tools and technology, such as deep learning, are required. Thus, the emergence of big data is anticipated to be a primary driver of the adoption of deep learning and artificial intelligence in the healthcare industry.
Currently, more than 200 companies are focused on providing deep learning services and deep learning technologies for drug discovery and diagnostic purposes. The primary focus areas of these companies include big data analysis, medical imaging, medical diagnosis and molecular data analysis. The deep learning in diagnostics segment features the presence of 139 companies, which is dominated by the presence of small companies (49%) owing to the technological advances in this field. Further, these companies are engaged in offering services across a wide range of therapeutic areas, with the primary focus on oncological disorders. It is worth highlighting that deep learning-powered diagnostic service providers offer various diagnostic solutions, such as structured analysis reports, image interpretation and biomarker identification solutions, with input data from several compatible devices. In this context, image processing services emerged as the most prominent type of service offered by the companies (83%) engaged in the deep learning in diagnostics domain.
Deep learning market for drug discovery is estimated to be $0.59 billion in 2023. In terms of therapeutic area, oncology is expected to capture the largest market share. This is due to the fact that deep learning allows the optimized categorization of histopathological images by comparing it with a vast dataset of such images, that enables enhanced diagnosis, prognosis and targeted treatment selection for oncological disorders. Lately, the industry has also witnessed the development of advanced deep learning technologies and software. These technologies possess the ability to obviate the concerns associated with the conventional drug discovery process and aid in the reduction of financial burden associated with drug discovery. The global deep learning market focusing on drug discovery is anticipated to grow at a CAGR of 23.1% between 2023 and 2035. In terms of geography, the market is anticipated to grow at a faster pace in North America and Europe by 2035.
Deep learning market for diagnostics in musculoskeletal and eye disorders is estimated to be $3.9 billion in 2035. The adoption of deep learning technologies to assist medical diagnosis, primarily through medical imaging, has increased in the recent past. The global deep learning market focusing on diagnostics is anticipated to grow at a CAGR of 19.8% between 2023 and 2035. By 2035, the deep learning in diagnostics market in North America is expected to capture the majority share. In terms of therapeutic areas, the deep learning in diagnostics market for musculoskeletal and eye disorders is anticipated to grow at a relatively faster pace by 2035, growing at a CAGR of 23% and 21%, respectively.
As of 2023, the deep learning market size for diagnostics applications is estimated to be $3.1 billion. This is because of increased efficiency and precision of applying deep learning-powered diagnostic solutions. Further, the deep learning in drug discovery market is anticipated to grow at a relatively higher CAGR of 23.1% during the forecast period with several pharmaceutical companies actively collaborating with solution providers for drug design and development.
Several industry and academic players are actively conducting clinical studies for the evaluation of applying deep learning algorithms for diagnostic purposes. Over 240 clinical studies are completed / being conducted to evaluate the potential of deep learning in diagnostics, highlighting the continuous pace of innovation in this field. Moreover, the field is evolving continuously, as a number of start-ups have emerged with the aim of developing deep learning technologies / software. In the past seven years, over 60 companies providing deep learning-based solutions have been established. Given the inclination towards advanced deep learning technologies and their vast applications in the healthcare segment, the deep learning market is likely to evolve at a rapid pace over the forecast period.
Examples of top deep learning companies for drug discovery (which have also been captured in this market research report) include Atomwise, Benevolent.ai, Cloud Pharmaceuticals, Deargen, Deep Cure, Exscientia, GNS Healthcare, Insilico Medicine, Isomorphic Labs, Juvena Therapeutics, Merative, Optibrium,x and Valence Discovery. This market report includes and easily searchable excel database for all the deep learning companies offering technologies for drug discovery.
Examples of top deep learning companies for diagnostics (which have also been captured in this report) include Avalon AI, Behold.ai, Blueberry Diagnostics, Deep Longevity, Esaote, Enlitic, Flatiron Health, H2O.ai, Huawei, InMed Prognostics, Kheiron Medical, Mediwhale, Nference, and Visiopharm. This market report includes and easily searchable excel database for all the companies offering deep learning for diagnostics.
![]() |
![]() |
![]() |
Several recent developments have taken place in the field of deep learning in drug discovery. We have outlined some of these recent initiatives below. These developments, even if they took place post the release of our market report, substantiate the overall market trends that have been outlined in our analysis.
The study presents an in-depth analysis of the various firms / organizations that are engaged in the deep learning market for drug discovery and diagnostics, across different segments as defined in the below table:
Report Attributes | Details | |
Base Year |
|
|
Forecast Period |
|
|
Market Size (Drug Discovery, 2023) |
|
|
Market Size (Diagnostics, 2023) |
|
|
CAGR (Drug Discovery) |
|
|
CAGR (Diagnostics) |
|
|
Therapeutic Areas |
|
|
Key Geographical Regions |
|
|
Key Companies Profiled |
|
|
Customization Scope |
|
|
PowerPoint Presentation (Complimentary) |
|
|
Excel Data Packs (Complimentary) |
|
The market report presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in the deep learning market, across different geographies. Amongst other elements, the report includes:
One of the key objectives of this market report was to estimate the current market size, opportunity, and future growth potential of deep learning market for drug discovery and diagnostic purposes over the coming years. We have provided informed estimates on the likely evolution of the market in the mid-to-long term, for the forecast period, 2023-2035. Our year-wise projections of the current and future opportunity have further been segmented based on relevant parameters, such as therapeutic area (oncological disorders, infectious diseases, neurological disorders, immunological disorders, endocrine disorders, cardiovascular disorders, respiratory disorders, ophthalmic disorders, musculoskeletal disorders and other disorders) and key geographical regions (North America, Europe, Asia Pacific and Rest of the World). Further, the chapter includes estimates of the likely cost saving potential of deploying deep learning technologies in the healthcare sector. In order to account for future uncertainties associated with some of the key parameters and to add robustness to our model, we have provided three market forecast scenarios, namely conservative, base and optimistic scenarios, representing different tracks of the industry’s evolution.
The opinions and insights presented in the report were influenced by discussions held with stakeholders in this industry. The report features detailed transcripts of interviews held with the following individuals:
All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions. Financial figures mentioned in this report are in USD, unless otherwise specified.
![]() |
![]() |
![]() |