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Pharma Tech Outlook | Monday, February 07, 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.
FREMONT, CA: Artificial Intelligence (AI) technologies are now widely employed for molecular target identification and selection in the pharmaceutical sector, according to The Business Study Company's research report on artificial intelligence in the drug development market. Discovering a potential molecular target with a specific biological action that is expected to have a defined therapeutic effect is characterised as target identification and selection.
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These molecular targets are either genes, proteins, or small molecules that require functional genomics, structural genomics, proteomics, cell-based assays (in vitro), and animal research (in vivo) assays to be evaluated. For predicting therapeutic potential, AI leverages a massive drug knowledge library that comprises drug candidates, gene expression, protein-protein interactions, and clinical data records from publically available resources. In addition, AI platforms can provide a comprehensive spatial 3D structure of proteins and chemical complexes by using cryo-EM microscopy data to train computer vision and machine learning models (2D structure). By using linear discriminant analysis (LDA), support vector machines (SVMs), random forest (RF), and decision trees analysis, AI-based quantitative structure-activity relationship (QSAR) modelling tools have evolved in an AI-based QSAR strategy to identify prospective therapeutic candidates.
The global artificial intelligence in drug discovery market is predicted to increase at a 31.6 percent compound annual growth rate (CAGR) from USD791.83 million in 2021 to USD1042.30 million in 2022. The market's increase is primarily due to enterprises resuming operations and adapting to the new normal while recovering from the impact of COVID-19. The market is predicted to reach USD2.99 billion in 2026, according to TBRC's projection in its artificial intelligence in drug discovery market size research, with a CAGR of 30.2 percent.
Pharmaceutical companies are now using innovative AI-based technologies to assess medicines and reduce medication development costs. Traditionally, the process of drug screening and development of a suitable molecule takes over a decade and requires a significant expenditure of $2.8 billion, with around 90% of molecules failing during phase II and regulatory approval. To verify virtual based synthetic feasibility and predict in vivo activity and toxicity, AI algorithms such as Nearest-Neighbor classifiers, RF, extreme learning machines, SVMs, and deep neural networks (DNNs) are utilised. Bayer, Roche, and Pfizer are among the biopharmaceutical corporations that have partnered with IT companies to build drug discovery platforms for cardiovascular medicines and immune-oncology illnesses.
See Also : Drug And Discovery Development Solutions Companies
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