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’s market research report covers artificial intelligence in drug discovery market size, artificial intelligence in drug discovery market forecasts, major artificial intelligence in drug discovery companies and their market share, key strategies to undertake, and more.

LONDON, Jan. 18, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Company’s research report on the artificial intelligence in drug discovery market, Artificial Intelligence (AI) tools are now widely used for molecular target identification and selection in pharmaceutical industry. Target identification and selection is defined as discovering a possible molecular target with a specific biological action which is anticipated to have a defined therapeutic activity. These molecular targets are either genes proteins or small molecules which further require evaluation of functional genomics, structural genomics, proteomics, and cell-based assays (in-vitro), animal research (in-vivo) assays. AI uses a large drug information bank which includes drug candidates, gene expression protein-protein interactions and clinical data records from publicly available resource for anticipating the therapeutic potential. In addition, AI platforms also demonstrate detailed spatial 3D structure of proteins and molecular complexes with the help of training computer vision and machine learning models on cryo-EM microscope data (2D structure). Quantitative Structure Activity Relationship (QSAR) modeling tools have evolved in AI based QSAR approach to identification of potential drug candidate by leveraging, linear discriminant analysis (LDA), support vector machines (SVMs), random forest (RF) and decision trees analysis.

The global artificial intelligence in drug discovery market size is expected to grow from $791.83 million in 2021 to $1042.30 million in 2022 at a compound annual growth rate (CAGR) of 31.6%. The growth in the market is mainly due to the companies resuming their operations and adapting to the new normal while recovering from the COVID-19 impact. As per TBRC’s forecast in its artificial intelligence in drug discovery market size report, the market is expected to reach $2.99 billion in 2026 at a CAGR of 30.2%.

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TBRC’s global artificial intelligence in drug discovery market analysis report identifies segments by technology as deep learning, machine learning; by drug type as small molecule, large molecules; by disease type as metabolic disease, cardiovascular disease, oncology, neurodegenerative diseases, others; by end-users as pharmaceutical companies, biopharmaceutical companies, academic and research institutes, others.

The global artificial intelligence in drug discovery market is concentrated, characterized by the presence of global artificial intelligence in drug discovery providers. The top ten competitors in the market made up to 50.21% of the total artificial intelligence in drug discovery market share in 2020. Artificial intelligence has the potential to transform the pharmaceutical industry. Each of the major pharma players is investing in the technology at some level, and there are a growing number of applications that address target and drug discovery, preclinical and clinical development, and post approval activities. Major players in the artificial intelligence in drug discovery market are IBM Corporation, Microsoft, Atomwise Inc., Deep Genomics, Cloud Pharmaceuticals, Insilico Medicine, Benevolent AI, Exscientia, Cyclica and BIOAGE.

Pharmaceutical industries are now adopting the novel AI based tools to screen drugs and minimize the cost of drug development. The process of drug screening and development of appropriate molecule traditionally take over a decade and need large amount of investment approximately $2.8 billion and about 90% of molecules fail during phase II and regulatory approval. AI algorithm such as Nearest-Neighbor classifiers, RF, extreme learning machines, SVMs, and deep neural networks (DNNs), are used to check virtual 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 immune-oncology diseases.

As per the artificial intelligence in drug discovery market research report, North America was the largest region, accounting for 44.0% of the total in 2021. It was followed by the Asia Pacific, Western Europe and then the other regions. Going forward, the fastest-growing regions in the artificial intelligence in drug discovery market will be South America and Asia Pacific where growth will be at CAGRs of 40.0% and 37.2% respectively during 2021-2026. These will be followed by Africa and Western Europe.

Artificial Intelligence (AI) In Drug Discovery Market Global Report 2022: Market Size, Trends, And Global Forecast 2022 - 2026 is one of a series of new reports from The Business Research Company that provide artificial intelligence in drug discovery market overviews, artificial intelligence in drug discovery market analyze and forecast market size and growth for the whole market, artificial intelligence in drug discovery market segments and geographies, artificial intelligence in drug discovery market trends, artificial intelligence in drug discovery market drivers, artificial intelligence in drug discovery market restraints, artificial intelligence in drug discovery market leading competitors’ revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

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

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