SEATTLE, June 10, 2021, (MEDGADGET) — Deep learning is branch of machine learning that investigates large volumes of organized and unorganized data. The approach also analyzes multi-dimensional and complex data with non-trivial patterns and can be an effective alternative to manual feature engineering. Increasing use of big data and internet has led to generation of huge amount of data in various forms. Such scenario has led to high adoption of Artificial Intelligence (AI) for data analysis in the healthcare sector and development of analytical data-driven models that rely on machine learning. These factors are expected to boost growth of the deep learning in drug discovery and diagnostics market over the forecast period.
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The emerging field of deep learning in drug discovery and diagnostics is based on Artificial Neural Networks (ANNs). The approach can find wide number of applications in healthcare information system. Significant advancements in computer-based operations and data storage technologies is expected to increase adoption of deep learning in drug discovery and diagnostics. Moreover, the ability of deep learning to automatically generate ideal high level features with semantic effective input data interpretation is also expected to contribute to growth of the market over the forecast period.
Deep Learning in Drug Discovery and Diagnostics Market Taxonomy:
By Application
- Drug Discovery
- Diagnostics
- Forensic Interventions
- Others
By End-use Industry
- Pharmaceutical Companies
- Biotechnology Companies
- Contract Research Organizations
- Healthcare IT
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Deep Learning in Drug Discovery and Diagnostics Market Drivers:
Conventional methods used in drug discovery and development are complex and time-consuming. Adoption of analytical processes and emerging approaches such as data mining, homology modeling, conventional machine learning, and deep learning have led to decrease in time required for drug discovery. This in turn is expected to propel growth of the global deep learning in drug discovery and diagnostics market.
Key players in the healthcare, life sciences, and the pharmaceutical sectors are focused on adopting AI and deep learning in order to expand their product portfolio. Use of AI and Deep Learning can aid in development of target-specific therapies with low side effects. Use of conventional drug discovery approaches involves high investment of time and resources with no assurance of desired outcome. However, deep learning can be used in drug discovery and diagnostics to enhance the probability of desired results. Such advantages of deep learning over conventional methods are expected to contribute to growth of the deep learning in drug discovery and diagnostics market.
Deep Learning in Drug Discovery and Diagnostics Market Competitive Landscape:
The global deep learning in drug discovery and diagnostics market has high presence of prominent players that have extensive experience in AI and deep learning and that have occupied major market share. Market players are focused on investment in R&D in order to introduce new technologies in the market. Key players operating in the deep learning in drug discovery and diagnostics market include, Insilico Medicine, Inc., Google Inc., IBM Corp., Microsoft Corporation, Qualcomm Technologies, Inc., General Vision Inc., Enlitic, Ginger.io, MedAware, NVIDIA Corporation, Zebra Medical Vision, Inc., and Lumiata.
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Key Developments
Research and development activities related to deep learning in drug discovery and diagnostics is expected to boost the market growth. For instance, on September 2, 2019, Insilico Medicine Hong Kong Ltd. reported development of a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL was used to discover potent inhibitors of discoidin domain receptor 1 (DDR1), a kinase target implicated in fibrosis and other diseases, in 21 days.
Key players in the market are focused on adopting collaboration and partnership strategies to enter in the emerging market. For instance, in February 2019, Juvenescence AI, Ltd., a drug development company focused on combating ageing and age-related diseases, collaborated with NetraMark Corp., a company that uses machine learning algorithms to redesign failing drugs, to form a joint venture, NetraPharma.
Major market players are also focused on raising funding to support their product development. For instance, in August 2019, Verisim Life, Inc., a U.S.-based biotechnology startup that uses AI-powered biosimulations to replace animal drug testing, announced it has raised $5.2 million in a round of funding led by Serra Ventures and OCA Ventures.
Table of Content
Global Deep Learning in Drug Discovery and Diagnostics Market Research Report
Section 1: Global Deep Learning in Drug Discovery and Diagnostics Industry Overview
Section 2: Global Economic Impact on Deep Learning in Drug Discovery and Diagnostics Industry
Section 3: Global Market Competition by Industry Producers
Section 4: Global Productions, Revenue (Value), according to Regions
Section 5: Global Supplies (Production), Consumption, Export, Import, geographically
Section 6: Global Productions, Revenue (Value), Price Trend, Product Type
Section 7: Global Market Analysis, on the basis of Application
Section 8: Deep Learning in Drug Discovery and Diagnostics Market Pricing Analysis
Section 9: Market Chain, Sourcing Strategy and Downstream Buyers
Section 10: Strategies and key policies by Distributors/Suppliers/Traders
Section 11: Key Marketing Strategy Analysis, by Market Vendors
Section 12: Market Effect Factors Analysis
Section 13: Global Deep Learning in Drug Discovery and Diagnostics Market Forecast
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