Facts and Factors Market Research has published a new report titled “AI for Drug Discovery Market By Drug Type ( Small Molecule and Large Molecule), By Technology (Deep Learning, Machine Learning, and Others), By Therapeutic Area (Metabolic Diseases, Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Oncology, and Others), and By End User (Pharmaceutical Companies, Academic & Research Institutes, Biopharmaceutical Companies, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2018 – 2027”. According to the report, the global AI for drug discovery market was valued at approximately USD 591 million in 2018 and is expected to reach a value of around USD 12,135 million by 2027, at a CAGR of around 39.8 % between 2019 and 2027.
AI for drug discovery is a technique that makes use of tools such as deep learning and machine learning that helps in adding value to the decision-making methods of drug discovery. The massive occurrence of rare ailments and escalating need for personalized medicine has prompted the demand for AI for drug discovery market.
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Huge demand for genetic data analysis to spur the market growth
With giant pharma firms focusing on genetic data interpretation of patients, the market for AI for drug discovery is likely to gain traction over the forecast timeline. Understanding of the patient’s genetic profile assists in providing apt medicines as well as medical treatment for the patients. Moreover, the computational approaches of machine learning help in analyzing genetic data of the patient and propose new drug and therapies.
Additionally, clinical practice based on the machine learning tools has generated huge demand for personalized medicines as well as drug discoveries. Furthermore, the healthcare and pharmaceutical sectors have been benefitted significantly from the use of machine learning computational methods in clinical practice. The machine learning tools are used for determining the body resistance to a particular type of drugs as well as resistance to combined drug therapies based on genotype interpretation.
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Small molecule segment dominates the drug type segment
The growth of the small molecule segment can be attributed to its notable contribution towards a large number of new drug application approvals over the past few years. Apart from this, the segment has also contributed significantly towards new molecular entities over the last few years. The small molecule segment is projected to register the highest growth rate of nearly 40.7% during the forecast timeframe.
Machine learning to contribute majorly towards the overall market earnings
Machine learning segment, which contributed nearly 50% towards overall market share in 2018, is expected to make sizable contributions towards the global market revenue even during the forecast timespan. The growth of this segment is due to the ability of the machine learning tools in assisting the researchers in using new computational algorithms for developing or designing novel drugs. Machine learning can also be used to create software for testing medicines as well as combinational therapies.
Browse the full “AI for Drug Discovery Market By Drug Type ( Small Molecule and Large Molecule), By Technology (Deep Learning, Machine Learning, and Others), By Therapeutic Area (Metabolic Diseases, Immuno-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Oncology, and Others), and By End User (Pharmaceutical Companies, Academic & Research Institutes, Biopharmaceutical Companies, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2018 – 2027” Report at https://www.fnfresearch.com/ai-for-drug-discovery-market-by-drug-type
Pharmaceutical companies sector to lead the end user segment
The pharmaceutical companies segment contributed around 40% of the overall market share in 2018 and is likely to register major market revenue share during the forecast period. The growth can be attributed to pharma giants focusing on using the machine learning tools to derive the exact information from the clinical data output obtained after performing clinical drug trials.
North America to lead the overall market growth in terms of value
The growth of the market in North America can be credited to the high acceptance of new technologies, the presence of major industry participants, and large scale investments in drug discovery research activities.
The major participants involved in the AI for drug discovery market include Recursion Pharmaceuticals, AstraZeneca, Astrocyte Pharmaceuticals, Inc., NeuroVive Pharmaceutical AB, twoXAR Incorporated, Biogen, Bionure Farma, S.L., BIOAGE, Genervon Biopharmaceuticals, LLC., Hoffmann-La Roche Ltd., Neuren Pharmaceuticals, Atomwise, Insilico Medicine, Silicon Therapeutics, Cloud Pharmaceuticals, Inc., Novartis Pharmaceuticals Corporation, Teva Pharmaceutical Industries Ltd., BenevolentAI, Exscientia, Numerate, Envisagenics, Inc., and Accutar Biotech.
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This report segments the AI for drug discovery market as follows:
Global AI for Drug Discovery Market: By Drug Type Segment Analysis
- Small Molecule
- Large Molecule
Global AI for Drug Discovery Market: By Technology Segment Analysis
- Deep Learning
- Machine Learning
Global AI for Drug Discovery Market: By Therapeutic Area Segment Analysis
- Metabolic Diseases
- Neurodegenerative Diseases
- Cardiovascular Diseases
Global AI for Drug Discovery Market: By End User Segment Analysis
- Pharmaceutical Companies
- Academic & Research Institutes
- Biopharmaceutical Companies
Global AI for Drug Discovery Market: Regional Segment Analysis
- North America
- Asia Pacific
- Latin America
- Middle East and Africa
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