The global intelligent drug discovery market is expected to be valued at USD 3,711.8 Million in 2027 from USD 258.9 Million in 2019, registering a CAGR of 39.4% through the forecast period. Artificial intelligence has proven to be a game-changing technology for the healthcare industry. It helps streamline healthcare research & development activities, enhance drug discovery techniques, and develop personalized medicine.
The global intelligent drug discovery market is predicted to account for a comparatively higher revenue share over the forecast timeframe. The rising focus of pharmaceutical companies on leveraging artificial intelligence for drug development, the growing adoption of AI for cost-effective and more efficient drug discovery for complex diseases are the primary factors propelling the global market growth. The rising prevalence of chronic diseases around the world, increasing investments by pharmaceutical companies in drug development, technological advancements in the design and development of new medicine, and the extensive utilization of cloud and machine learning technologies in drug development processes are the other significant factors spurring the market growth.
Furthermore, the growing emergence of biopharmaceutical companies, increasing partnerships and mergers between public and private healthcare companies for R&D activities, strategic approaches undertaken to lower drug discovery costs, and greater investments by the government in healthcare infrastructure further support the global intelligent drug discovery market growth. However, the dearth of skilled healthcare professionals and the lack of data sets in drug discovery are predicted to limit the market growth to a significant extent.
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Key Highlights of the Report:
- Based on offering, the software sub-segment is expected to hold the largest market share over the forecast period. Advantages of AI-based software, such as lesser time and costs and lower risks of failure, have boosted the adoption of AI for drug discovery. The emergence of avant-garde software for drug discovery and escalating demand among leading pharmaceutical companies have further driven this segment’s growth.
- The machine learning sub-segment dominates the global intelligent drug discovery market in terms of technology, retaining the highest market revenue. Researchers optimize drug discovery and development by combining clinical and biomedical data with various computational models. Hence, this helps them develop software for combinational therapies.
- Among the leading regional markets, the Asia Pacific has emerged as the most dominant market for intelligent drug discovery. The market is poised to maintain its dominating market status over the estimated period due to the growing patient pool in the region, increasing healthcare R&D activities, the thriving biotechnology and pharmaceutical sectors.
- The leading market participants include IBM Corporation, Google, Microsoft Corporation, Insilico Medicine, Cloud Pharmaceuticals, Inc., Nvidia Corporation, Atomwise, Inc., Exscientia, Bioage, and Envisagenics.
- In October 2020, Optibrium launched an intelligence platform for drug discovery, called Cerella. The architecture of the new platform comprises cloud computing with on-premise deployment and offers enhanced data security.
- In December 2020, Capgemini, the leading information technology company based in France, introduced its third set of intelligent offerings for the healthcare industry focused on life sciences research and development. The new offering, dubbed ‘Data Driven R&D for Life Sciences,’ is intended to help biopharmaceutical companies streamline the drug discovery process and leverage specific AI capabilities for research & development.
Intelligent Drug Discovery Market
For the purpose of this report, Emergen Research has segmented the Global Intelligent Drug Discovery Market based on offering, technology, application, end-user, and region:
By Offering (Revenue, USD Billion; 2017-2027)
- Software
- Services
By Technology (Revenue, USD Billion; 2017-2027)
- Machine Learning
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- Deep Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
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- Other Technologies
By Application (Revenue, USD Billion; 2017-2027)
- Cardiovascular Disease
- Neurodegenerative Diseases
- Immuno-oncology
- Metabolic Diseases
- Others
By End-user (Revenue, USD Billion; 2017-2027)
- Pharmaceutical & Biotechnology Companies
- Research Centers
- Contract Research Organizations (CROs)
- Academic & Government Institutes
- Others
By Region (Revenue, USD Billion; 2017-2027)
- North America
- U.S.
- Canada
- Europe
- Germany
- U.K.
- France
- BENELUX
- Rest of Europe
- Asia Pacific
- China
- Japan
- South Korea
- Rest of Asia Pacific
- Latin America
- Brazil
- Rest of Latin America
- Middle East & Africa
- Saudi Arabia
- U.A.E.
- Rest of Middle East & Africa
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