Pharma Industry Players Leverage AI For Drug Discovery By Using Precise Molecular Target Identification As Per The Business Research Company’s Artificial Intelligence (AI) In Drug Discovery Global Market Report 2022

TBRC market research report covers Artificial Intelligence in Drug Discovery Market Size, Artificial Intelligence in Drug Discovery Market Forecast, Major Artificial Intelligence in Drug Discovery Companies and Market Share, Key Strategies to Do, and more.

LONDON, Jan. 18, 2022 (GLOBE NEWSWIRE) — According to a Business Research Company research report on artificial intelligence in the drug discovery market, artificial intelligence (AI) tools are now widely used for molecular target identification and selection in the pharmaceutical industry. Target identification and selection is defined as the discovery of a potential molecular target with a specific biological action that is expected to have a specific therapeutic activity. These molecular targets are either oncoproteins or small molecules that also require assessment of functional genomics, structural genomics, proteomics, cell-based assays (in vitro), and animal research (in vivo). AI uses a large drug information bank that includes candidate drugs, protein-protein interactions in gene expression, and clinical data records from publicly available resources to anticipate therapeutic potential. In addition, AI platforms also demonstrate a detailed 3D spatial structure of proteins and molecular complexes with the help of computer vision training and machine learning models on cryo-EM (two-dimensional structure) microscopy data. Quantitative Structure Activity Relationship Modeling (QSAR) tools have evolved in the AI-based QSAR approach to identify a potential drug candidate by utilizing linear discriminant analysis (LDA), support vector machines (SVMs), random forests (RF), and decision tree analysis.

The global artificial intelligence is expected to grow in the size of the drug discovery market $791.83 million in 2021 to $1042.30 million in 2022 compound annual growth rate (CAGR) of 31.6%. The growth in the market is mainly due to companies resuming their operations and adapting to the new normal while recovering from the impact of COVID-19. According to TBRC’s Forecast in Artificial Intelligence in Drug Discovery Market Size Report, the market is expected to reach 2 dollars.99 Bmillion in 2026 in a Compound annual growth rate of 30.2%.

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TBRC’s Global Artificial Intelligence Drug Discovery Market Analysis Report identifies segments by technology such as Deep Learning and Machine Learning; By type of drug as small molecule, large molecule; By type of disease such as metabolic diseases, cardiovascular diseases, neoplasms, neurodegenerative diseases, etc.; By end users such as pharmaceutical companies, biopharma companies, academic and research institutes, etc.

Global AI is concentrated in the drug discovery market, and is characterized by the presence of global AI in drug discovery providers. the Top Ten Competitors In the market made up of 50.21% of the total market share of AI in drug discovery in 2020. AI has the potential to transform the pharmaceutical industry. Every major pharmaceutical player is investing in technology at some level, and there is a growing number of applications addressing target and drug discovery, preclinical and clinical development, and post-approval activities. The major players in artificial intelligence in the drug discovery market are IBM Corporation, Microsoft and Atomwise Inc. and Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica, and BIOAGE.

Pharmaceutical industries are now adopting new AI-based tools to screen drugs and reduce the cost of drug development. The process of drug screening and development of the appropriate molecule takes more than a decade and requires a significant investment of about $2.8 billion and about 90% of molecules fail during phase II and regulatory approval. AI algorithms such as nearest-neighborly classifiers, RFs, extreme learning machines, self-management devices and deep neural networks (DNNs), are used to verify virtualization-based synthetic feasibility and predict in vivo activity and toxicity. Biopharmaceutical companies such as Bayer, Roche, and Pfizer have associated with IT companies to develop drug discovery platforms for cardiovascular therapies and immuno-oncology.

According to the Artificial Intelligence Drug Discovery market research report, North America It was largest area, Account for 44.0% of the total in 2021. It was followed by Asia Pacific, Western Europe and other regions. to go forward, The fastest growing regions In artificial intelligence in the drug discovery market will be South America and Asia Pacific Where will the growth be compound annual growth rate of 40.0% and 37.2% respectively during 2021-2026. Africa and Western Europe will follow.

Artificial Intelligence (AI) in Global Drug Discovery Market 2022 Report: Market Size, Trends and Global Forecast 2022 – 2026 is one of a series of new reports from Business Research firm providing Artificial Intelligence in Drug Discovery Market Overviews, and Artificial Intelligence in Drug Discovery Market Analysis Drugs and market forecasting of market size and growth for the entire market, AI in drug discovery market segments and geographies, AI in drug discovery market trends, AI in drug discovery market drivers, AI in drug discovery market constraints, AI in drug discovery market driving Competitors revenue, profiles, and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographical regions.

The report also provides an in-depth analysis of the impact of COVID-19 on the market. The reports are based on 150,000 data sets, extensive secondary research, and exclusive insights from interviews with industry leaders. A team of highly experienced and expert analysts and designers provides market analysis and forecasts. The reports identify top countries and divisions for opportunities and strategies based on market trends and the approaches of leading competitors.

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