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How Fast Is The Generative Artificial Intelligence (AI) In Drug Discovery Market Expected to Grow Between 2025 And 2029?
The market size for generative artificial intelligence (AI) in drug discovery has seen exceptional growth recently. It is anticipated to expand from $0.19 billion in 2024 to $0.25 billion in 2025, with a compound annual growth rate (CAGR) of 30.6%. The historical growth can be credited to the increasing presence of chronic diseases, new advancements in drug discovery, clinical trials that incorporate AI into healthcare and drug development, the evolution of the biotech industry, and increased support from the government.
Anticipated to observe remarkable expansion in the coming years, the market size for generative artificial intelligence (AI) in the field of drug discovery is set to reach around $0.7 billion in 2029, with a compound annual growth rate (CAGR) of 28.8%. This notable rise during the forecasting time is primarily due to the rising demand for cost-effective drug discovery processes, escalating collaborations between market participants, an increase in computational power, and synergy of generative AI with emerging tech for swift drug development. In addition, the forecast period will witness trends like cutting-edge technology usages, incorporation of generative AI with experimental biology, boosting drug discovery pipelines through high-throughput screening, the emergence of AI-driven platforms for repurposing drugs, and the growing preference for cloud-centric AI solutions in cooperative drug discovery ventures.
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What Are the Primary Drivers Supporting the Market Growth of the Generative Artificial Intelligence (AI) In Drug Discovery Market?
The growth of generative AI in the drug discovery market is expected to be fuelled by an increase in the number of clinical trials. These trials involve human volunteers and are used to evaluate the safety and efficacy of new medical procedures or treatments, with the goal of gathering credible scientific information for their application in humans. Advancements in medical research, an escalated disease burden, regulatory amendments, global clinical research, patient advocacy and awareness, industry competition, technological progress, and availability of funding are all contributing to the increase in clinical trials. The data derived from these trials serves as a crucial input for generative AI models, which accelerates the drug discovery process through predictions of interactions and compound design. This collaboration contributes to personalized medicine, enhances the effectiveness of treatments, betters patient outcomes, and transforms the pharmaceutical field. For example, the US-based clinical trial registry, ClinicalTrials.gov, reported 477,234 registered clinical trials worldwide by the end of 2023, a significant rise from the 437,512 trials registered in 2022. As a result, the expanding number of clinical trials is propelling the growth of generative AI in the drug discovery market.
Which Primary Segments of the Generative Artificial Intelligence (AI) In Drug Discovery Market Are Driving Growth and Industry Transformations?
The generative artificial intelligence (AI) in drug discoverymarket covered in this report is segmented –
1) By Type: Small Molecule; Large Molecule
2) By Technology: Deep Learning; Machine Learning; Reinforcement Learning; Molecular Docking; Quantum Computing
3) By End-User: Pharmaceutical And Biotechnology Companies; Academic And Research Institutions; Contract Research Organizations (CROs); Other End-Users
Subsegments:
1) By Small Molecule: Drug Design And Optimization; Lead Discovery And Identification; Toxicology Prediction; Molecular Property Prediction; ADMET (Absorption, Distribution, Metabolism, Excretion, And Toxicity) Prediction
2) By Large Molecule: Protein Structure Prediction; Antibody Design; Biologics Optimization; Peptide Design; Biopharmaceutical Discovery And Optimization
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Which Regions Are Key Players in the Growth of the #What Are the Primary Drivers Supporting the Market Growth of the Generative Artificial Intelligence (AI) In Drug Discovery Market?# Market?
North America was the largest region in the generative AI in drug discovery market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative artificial intelligence (AI) in drug discovery market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
What Are the Most Significant Market Trends in the Generative Artificial Intelligence (AI) In Drug Discovery Market?
Leading firms in the generative AI sector for drug discovery are designing superior AI-enabled tools to hasten the drug discovery procedures. The process of drug development is streamlined by these AI-enabled tools, which incorporate predictive analytics and machine learning to expedite drug discovery, design, and clinical trials. They also improve efficiency in areas such as target identification, compound screening through AI-assisted virtual screening, preclinical development, compliance with regulations, and manufacturing procedures. An example of this occurred in May 2023, when Google Cloud, a U.S. cloud computing service from Google, unveiled two novel solutions driven by AI to enhance drug discovery and precision medicine across sectors such as biotech, pharmaceuticals, and the public sector. The Target and Lead Identification Suite aids researchers in decoding the functions of amino acids and predicting protein structures, and the Multiomics Suite accelerates the examination and comprehension of genomic data, resulting in the simplified creation of customized treatments.
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What Parameters Are Used to Define the Generative Artificial Intelligence (AI) In Drug Discovery Market?
Generative AI in drug discovery involves using advanced machine learning, especially generative models, to create and identify new pharmaceutical compounds. These AI systems analyze extensive data, including chemical properties, biological activity, and existing drug information to predict and generate novel molecules with potential therapeutic benefits. The primary aim of generative AI in drug discovery is to accelerate the creation and identification of novel pharmaceutical compounds with potential therapeutic effects, optimizing the drug development process by leveraging extensive data to predict and generate new molecules efficiently.
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