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Mordor Intelligence has published a new report on\u00a0the AI in life sciences market, offering a comprehensive analysis of trends, growth drivers, and future projections.<\/span>\u00a0<\/span><\/p>\n According to Mordor Intelligence,<\/span>\u00a0the<\/span>\u00a0AI in life sciences market size was valued at USD 3.61 billion in 2025 and is estimated to grow from USD 4.51 billion in 2026 to reach USD 13.64 billion by 2031, registering a CAGR of 24.78% during the forecast period (2026\u20132031). This strong AI in life sciences market growth<\/a> reflects increasing use of intelligent software tools across pharmaceutical research, diagnostics, clinical development, and healthcare analytics.\u00a0<\/span>\u00a0<\/span><\/p>\n The\u00a0artificial\u00a0intelligence\u00a0in life sciences industry\u00a0is\u00a0benefiting\u00a0from improved regulatory clarity and wider availability of clinical and genomic datasets. Regulators are increasingly accepting AI-based biomarkers and analytics outputs as valid evidence, helping accelerate approval pathways. At the same time, federated learning and secure data sharing are enabling researchers to train models on diverse datasets without compromising privacy<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n Regulatory Support Improving Adoption Across Clinical Applications\u00a0<\/strong><\/p>\n One of the major\u00a0AI in life sciences market trends\u00a0is growing regulatory acceptance of AI-generated biomarkers and analytics tools. Regulatory programs have reduced approval timelines for AI-supported oncology and rare disease applications, allowing developers to reach patients faster. These regulatory initiatives also enable validated AI biomarkers to be reused across multiple research pipelines, improving efficiency and increasing the\u00a0AI in life sciences market share\u00a0of AI-enabled clinical programs.<\/span>\u00a0<\/span><\/p>\n Federated Data Networks Strengthening AI Training and Collaboration\u00a0<\/strong><\/p>\n The expansion of federated data platforms is another key factor influencing\u00a0the\u00a0artificial\u00a0intelligence\u00a0in life sciences market\u00a0growth. These systems allow organizations to train AI models across multiple datasets without transferring sensitive patient information. This approach ensures data privacy while enabling broader and more\u00a0accurate\u00a0training.\u00a0Federated\u00a0learning is particularly useful in genomics, imaging, and clinical trial optimization. By connecting hospitals, research institutions, and pharmaceutical companies, these networks improve data accessibility and increase collaboration.\u00a0<\/span>\u00a0<\/span><\/p>\n Hyperscaler\u00a0Partnerships Improving Computational Efficiency\u00a0<\/strong><\/p>\n Partnerships between cloud providers and pharmaceutical companies are reducing computational costs and increasing scalability. These collaborations enable faster molecular simulations and improve the efficiency of drug discovery pipelines. Reduced computational barriers allow smaller research organizations to participate in advanced AI-driven discovery, expanding the reach of the AI in life sciences industry. Cloud infrastructure also supports large-scale analytics, helping researchers analyze genomic data and clinical records more efficiently.<\/span>\u00a0<\/span><\/p>\n Generative AI Enhancing Drug Discovery and Research Capabilities\u00a0<\/strong><\/p>\n Generative AI is becoming a major contributor to AI in life sciences market trends, especially in early-stage drug discovery. These tools can generate new molecular structures and predict biological interactions, reducing the time needed for candidate\u00a0selection. This improves research productivity and increases the success rate of drug\u00a0development.Generative\u00a0models also support personalized medicine and biomarker identification. By analyzing large biological datasets,<\/span>\u00a0<\/span><\/p>\n Check out more details and stay updated with the latest industry trends, including the Japanese version for localized insights:<\/span><\/b>\u00a0<\/span>https:\/\/www.mordorintelligence.com\/ja\/industry-reports\/artificial-intelligence-in-life-sciences-market?utm_source=emailwire<\/span><\/a>\u00a0<\/span>\u00a0<\/span><\/p>\n By Offering\u00a0<\/strong><\/p>\n By Deployment Model\u00a0<\/strong><\/p>\n By Analytics Type\u00a0<\/strong><\/p>\n By Application\u00a0<\/strong><\/p>\n By End User\u00a0<\/strong><\/p>\n By Technology\u00a0<\/strong><\/p>\n By Geography\u00a0<\/strong><\/p>\n North America\u00a0<\/strong><\/p>\n Europe\u00a0<\/strong><\/p>\n Asia Pacific\u00a0<\/strong><\/p>\n South America\u00a0<\/strong><\/p>\n Middle East and Africa\u00a0<\/strong><\/p>\n Explore Our Full Library of Technology,\u00a0Media\u00a0and Telecom Research:\u00a0<\/span><\/b>\u00a0<\/span>https:\/\/www.mordorintelligence.com\/market-analysis\/technology-media-and-telecom?utm_source=emailwire<\/span><\/a>\u00a0<\/span><\/p>\nAI in Life Sciences Market Outlook<\/span>\u00a0<\/span><\/h2>\n
Growth Drivers\u00a0the AI in Life Sciences Market Growth<\/span>\u00a0<\/span><\/h2>\n
AI in Life Sciences Market Segmentation\u00a0<\/span>\u00a0<\/span><\/h2>\n
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