Artificial Intelligence in Drug Discovery Market Research Report, By Product Type (Software, Services), Molecule Type (Large Molecule, Small Molecule), Technology (Machine Learning, Deep Learning and others), Indication (Immune-Oncology, Neurodegenerative Diseases, Cardiovascular Diseases, Metabolic Diseases and others), Application (Target Identification, Candidate Screening, De novo Drug Designing, Drug Optimization and Repurposing and Preclinical Testing) – Forecast till 2030
Artificial Intelligence in Drug Discovery Market is expected to hold a value of about USD 8.9 Billion by 2030, and it is projected to register a CAGR of 24.9% from 2022 to 2030. Since different enterprises and big research hospitals have been seeking to build these systems for clinical application, artificial intelligence (AI) has drawn the interest of professionals in the medical area. In the medical field, the first practical applications of artificial intelligence (also known as deep learning, machine learning, and artificial neural networks) are beginning to show promise. These innovations have the potential to revolutionise healthcare processes by boosting efficiency and quality of care delivery for patients.
With the unlimited possibilities given by this cutting-edge technology, artificial intelligence in healthcare is flourishing, and major corporate giants are expressing interest and investing considerably in the industry. Several digital behemoths are making investments in AI for the healthcare business, including IBM’s Watson, Alphabet, and Philips. Drug research and discovery might both benefit from the use of artificial intelligence and machine learning, and many different pharmaceutical companies and startups across the world are already actively working on these fronts.
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Artificial Intelligence in Drug Discovery Market Segmentation
By product type
AI platforms developed with machine learning and deep learning technologies are examples of software that are essential to the operation of an AI business.
Implementing AI, incorporating AI, and upgrading AI are all services. Besides providing a platform, startups like BenevolentAI and DeepMatter collaborate closely with pharmaceutical giants like AstraZeneca to improve drug development outcomes.
for Finding New Drugs Making Use Of Devices
It’s all about the machines now: Machine learning (ML) techniques provide a toolkit that, when combined with an abundance of high-quality data, may significantly improve the quality of certain types of decisions. The application of ML in drug research and development offers the ability to speed the process
In Deep Learning (DL), another subfield of AI, models reflect geometric modifications on several levels.
Technology alternatives to artificial intelligence include natural language processing, expert systems, and robots, all of which have the potential to improve the drug development process.
Artificial Intelligence in Drug Discovery Market Regional Insights
The United States and Canada, among others, have long been global leaders in healthcare. One of the key factors of the region’s swift rise in the AI in drug discovery market is the expanding number of large AI platform developers there.
After the Americas, Europe is the area with the second-largest market for AI in drug discovery. The regional AI in the drug discovery market is predicted to expand as a result of factors including rising R&D activities in the pharmaceutical sector and high demand from Big Pharma businesses for AI solutions. Leading pharmaceutical companies have forged partnerships with AI service providers to incorporate AI technology into the drug discovery process.
Grouping Potential Drug Targets Based on Clinical Presentation
Immuno-oncology: Immuno-oncology is expected to be the largest application area for AI in drug development. Thanks to advancements in artificial intelligence, precision medicine can now tell the difference between various genetic variations.
There is a great deal of importance in using AI in medication discovery for neurodegenerative illnesses. ALS is a devastating neurological disorder for which there is presently no treatment (ALS). An AI and machine learning business named BenevolentAI is currently looking at potential therapies for amyotrophic lateral sclerosis (ALS) (ALS).
Cardiovascular diseases: a substantial proportion of the world’s population suffers from cardiovascular disease, making it one of the leading causes of death worldwide.
Many companies are also putting money into discovering new pharmaceuticals to address metabolic illnesses, another critical health issue.
to Find New Medicines Targeting an Application: In drug development, discovering new targets is a time-consuming process that can take months or even years if done the old-fashioned approach.
Examining potential candidates: This subset of the artificial intelligence in drug development industry is expected to generate the most revenue.
Drug repurposing is the process of finding new and beneficial applications for existing drugs, and it is an important part of the use of artificial intelligence to the drug development process.
unique and unheard-of Planning New Meds: Polypharmacology, pharmacokinetics, and structural pharmacogenomics are all significant factors to consider while developing novel drugs.
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Artificial Intelligence in Drug Discovery Market Key vendors
Microsoft Corporation, IBM Corporation, Google (A Subsidiary of Alphabet Inc.), Atomwise, Inc., Deep Genomics, Cloud Pharmaceuticals, Inc., Insilico Medicine, BenevolentAI, Exscientia, Cyclica, Bioage, Numerate, and Insilico Medicine are just some of the major players that have contributed to this article.
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