New York, NY, March 17, 2021 (GLOBE NEWSWIRE) -- Facts and Factors have published a new research report titled “AI in Drug Discovery Market By Drug Type (Small Molecule and Large Molecule), By Technology (Deep Learning, Machine Learning, Others), By End User (Pharmaceutical Companies, Biopharmaceutical Companies, Academic & Research Institutes, and Others), By Therapeutic Area (Metabolic Diseases, Cardiovascular Diseases, Immuno-Oncology, Oncology, Neurodegenerative Diseases, Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2020–2026”.
“According to the research report, the global AI in Drug Discovery Market was estimated at USD 830 Million in 2019 and is expected to reach USD 12,000 Million by 2026. The global AI in Drug Discovery Market is expected to grow at a compound annual growth rate (CAGR) of 39% from 2020 to 2026”.
Artificial Intelligence is a machine, device, or company method for learning about how smart human thought is and that research eventually develops intelligent software systems. Modularizing artificial intelligence with health-care tools in pharmaceutical, biopharmaceutical companies, and drug discovery research organizations is called drug discovery AI. Machine learning and other innovations will allow pursuing new pharmaceuticals quicker, cheaper, and more successful. Drug companies rapidly understand the importance of introducing systems focused on Artificial Intelligence (AI) that can exploit data on gene variants, receptor targets, metabolic enzymes, disease events, and clinical studies to find hidden associations in drug-disease. One of the drivers for the market could be the growing demand for genetic data analysis and customized medication. Machine learning could help enhance treatment by incorporating biomedical and scientific statistics with computational models and can be used to build software to check drugs and other therapies. Some computational replicas and tactics that sustenance the accumulation of clinical statistics are under progress and are moreover a few very good examples of successful data integration in biology and medicine. One of the possible alternatives is to interpret the genetic makeup as a one-dimensional model and then to implement a regular algorithm for machine learning.
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Our Free Sample Report Includes:
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(Note: The sample of this report is updated with COVID-19 impact analysis before delivery)
Key Questions Answered in this Report
1) What were the pre and post-business impacts of COVID-19 on the AI in Drug Discovery Market?
2) What is the market size, share of AI in Drug Discovery Market?
3) Who are the top market players in AI in Drug Discovery Market?
4) What will be the future market of AI in Drug Discovery Market?
Key Offerings:
- Market Size & Forecast by Revenue | 2020−2026
- Market Dynamics – Leading trends, growth drivers, restraints, and investment opportunities
- Market Segmentation – A detailed analysis by product, by types, end-user, applications, segments, and geography
- Competitive Landscape – Top key vendors and other prominent vendors
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Impact Analysis of COVID-19 Pandemic on Businesses: Know Short Term and Long Term Impact
Most of the businesses are facing a growing litany of business-critical concerns related to the coronavirus outbreak, including supply chain disruptions, a risk of a recession, and a potential drop in consumer spending. All these scenarios will play out differently across various regions and industries, making accurate and timely market research more essential than ever.
We at Facts and Factors (http://www.fnfresearch.com) understand how difficult it is for you to plan, strategize, or make business decisions, and as such, we have your back to support you in these uncertain times with our research insights. Our team of consultants, analysts, and experts has developed an analytical model tool for markets that helps us to assess the impact of the virus more effectively on the industrial markets. We are further implementing these insights into our reports for a better understanding of our clients.
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Another driver for the market is Quantum machine learning research indicating this method should be useful for finding complex patterns in results. Given the complexity of biological and clinical details, deterministic quantic machine learning algorithms represent a real chance to better know them. The introduction of a novel machine-learning algorithm for drug discovery in the near future is expected to generate an immense opportunity for the growth of the market in the near future. In the near future, the increasing relationship between pharmaceutical companies and AI-based companies to automate the drug discovery approach is expected to generate huge opportunities for company growth.
Industry Major Market Players
- Atomwise Inc
- BenevolentAI
- Bio age
- Cloud Pharmaceuticals Inc
- Exscientia Ltd
- Insilico Medicine Inc
- Numerate Inc
- Envisagenics Inc
- Two XAR Inc
- Accutar Biotechnology Inc
- Recursion Pharmaceuticals Inc
- Silicon Therapeutics LLC
- AstraZeneca PLC.
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One of the major challenges in the drug discovery phase is patient health. Dynamic activities are to interpret information about the documented effects of drugs and anticipate their side effects which will be a restraint for the market.
One of the major challenges in the drug discovery phase is patient health. Dynamic activities are to interpret information about the documented effects of drugs and anticipate their side effects which will be a restraint for the market.
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The study provides a decisive view of the AI in the Drug Discovery market by segmenting the AI in the Drug Discovery market based on drug type, technology, end-user, therapeutic area, and regions. All the segments and sub-segments have been examined based on historic, current, and future trends in the global market and the market size is estimated from 2020 to 2026 in terms of value. The regional segmentation includes the current and forecast demand for North America, Europe, Asia Pacific, Latin America, and the Middle East and Africa.
An AI in Drug Discovery is used to identify targets, in silico drug design, drug development, predictive analytics, research risk assessment, clinical tracking, and even more.
Machine learning may help maximize treatment by combining biological and clinical evidence with mathematical models and can be used to develop drug testing and probabilistic treatment applications. Computational deep learning research indicates this methodology should be helpful in finding complex models in results. Since biological and clinical data are diverse, deterministic quantic machine learning algorithms offer a reasonable opportunity to advance interpret them. However, one of the major challenges in the drug discovery phase is patient health.
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The global AI in the Drug Discovery market is segmented into drug type, technology, end-user, therapeutic area, and region. On the basis of drug type, the global AI in the Drug Discovery market is classified as a small molecule and large molecule. The small molecule segment is expected to record the fastest growth over the predictable period, due to its advantages over the large molecule. On the basis of technology, the global AI in the Drug Discovery market is bifurcated into deep learning, machine learning, and others where machine learning is more dominating over the predictable period. On the basis of end-user, the global AI in the Drug Discovery market is divided into pharmaceutical companies, biopharmaceutical companies, academic, and research institutes, and others where pharmaceutical companies are leading. The global AI in the Drug Discovery industry is categorized into metabolic diseases, cardiovascular diseases, immuno-oncology, neurodegenerative diseases, and others where oncology is at the front, depending on therapeutic areas.
By Drug Type, the segmentation includes small molecule and large molecule. Here small molecule type is accounted for the market share of around 60% and is likely to dominate in the target market. Further, based on the technology it can be segmented into deep learning, machine learning, and other segments in which machine learning accounts for the market share of around 50% and is probable to dominate in the target market. Based on the end-user it can be segmented into pharmaceutical companies, biopharmaceutical companies, academic and research institutions where pharmaceutical companies dominate with around 40% market share in the target market. Depending on the therapeutic area, it can be segmented into metabolic disease, cardiovascular disease, immuno-oncology, oncology, neurodegenerative diseases, and others where oncology controls the target market at about 40% share of the market. It can be segmented into North America, Europe, Asia Pacific, the middle east & Africa, and Latin America, based on the geographic field, where North America dominates the target market at around 50% market share.
Browse the full “AI in Drug Discovery Market By Drug Type (Small Molecule and Large Molecule), By Technology (Deep Learning, Machine Learning, Others), By End User (Pharmaceutical Companies, Biopharmaceutical Companies, Academic & Research Institutes, and Others), By Therapeutic Area (Metabolic Diseases, Cardiovascular Diseases, Immuno-Oncology, Oncology, Neurodegenerative Diseases, Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2020–2026” report at https://www.fnfresearch.com/ai-in-drug-discovery-market
This report segments the AI in Drug Discovery market as follows:
Global AI in Drug Discovery Market: By Drug Type Segment Analysis
- small molecule
- large molecule
Global AI in Drug Discovery Market: By Technology Segment Analysis
- deep learning
- machine learning
- other segments
Global AI in Drug Discovery Market: By End-user Segment Analysis
- pharmaceutical companies
- biopharmaceutical companies
- academic and research institutions
Global AI in Drug Discovery Market: By Therapeutic Area Segment Analysis
- metabolic disease
- cardiovascular disease
- immuno-oncology
- oncology
- neurodegenerative diseases
Key Insights from Primary Research
- According to our primary respondents, we have analyzed that the global AI in the Drug Discovery market is anticipated to grow annually with a CAGR of nearly 39% till 2026 end.
- It was established through primary research that the global AI in the Drug Discovery market was valued at around USD 830 million in 2019.
- On the basis of drug type, the small molecule led the market in 2019 accounting for around 60% share, in 2019
- Based on technology, the machine learning segment held the largest share in the global AI in the Drug Discovery market, accounted for approximately 50% share in the global market in 2019.
- By the end-user, the pharmaceutical companies segment held a major share in the global AI in the Drug Discovery market in 2019 and is projected to maintain a similar trend over the forecasted period.
- On the basis of therapeutic area segmentation, the oncology category held the leading share of around 25% in 2019.
- On the basis of region segmentation, the North America region held the leading share of around 50% in 2019.
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