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The U.S. AI in life science analytics market is expanding due to AI-based technologies, increasing demand for advanced data analytics for pharmaceutical and biotechnology research, and further augmenting the market.
The adoption of AI in life science/healthcare is expanding due to an increasing volume of data created from genomics, proteomics, and other technologies that require sophisticated analytical tools to extract actionable plans. Pharmaceutical firms are heavily investing in AI to find out drug development timelines and minimize costs related to clinical trials. Additionally, AI is being used to customize medicine by detecting patient responses to various treatments, hence improving patient responses. Regulatory bodies like the FDA are also supporting AI integration in the drug development process by offering stringent guidelines, which augment growth in the U.S. AI in life science analytics market.
AI in life science encompasses analyzing complex datasets with the help of machine learning, natural language processing, and AI tools to increase drug discovery. For instance, in 2023, an AI-driven drug discovery company known as Insilico Medicine made an advancement in its AI-discovered drug candidate as a clinical trial, highlighting a milestone in AI’s potential in drug discovery.
AI use cases in life sciences
Let’s now take a look at the impact of AI in life sciences. This list could be a lot longer, but in this article I will only focus on AI use cases in life sciences.
Speeding up drug discovery and development
I think one of the areas where AI in healthcare is making the biggest impact is drug development and discovery. Thanks to the use of data science, deep learning and machine learning, AI is able to quickly analyze massive data sets, and as a result, accelerate the discovery of new molecules.
Since AI algorithms can simultaneously sift through information from multiple sources like published scientific literature, clinical trial data, public databases and conference summaries it can identify therapies that might work for specific health conditions. The speed with which AI in life sciences can examine large data volumes can cut down the drug discovery and development time to months, rather than years, and I think that is truly revolutionary.
AI In Life Science Analytics Market Report Scope
|
Report Attribute |
Details |
|
Market size value in 2025 |
USD 661.12 Million |
|
Revenue forecast in 2034 |
USD 3.6 Million |
|
Growth rate |
CAGR of 1,732.76 % from 2025 to 2034 |
|
Base year for estimation |
2023 |
|
Historical data |
2019 - 2024 |
|
Forecast period |
2025 - 2034 |
|
Quantitative units |
Revenue in USD million/billion & CAGR from 2025 to 2034 |
|
Report coverage |
Revenue forecast, company share, competitive landscape, growth factors and trends |
|
Segments covered |
Delivery, component, application, end-use, |
|
Key companies profiled |
Indegene; Lexalytics; Databricks; SAS Institute, Inc.; IQVIA; IBM; Sorcero; Axtria |
U.S. AI in Life Science Analytics Market trends
• Growing demand for efficient drug discovery- the major driving factor for the expansion of U.S. AI in life science analytics market is the increasing demand for efficient drug discovery processes. These processes, when performed with conventional methods, are time-consuming and expensive too, making them hard to adopt as they may take decades and amount to billions of dollars. Hence, growing incidences of complicated diseases bring light to such healthcare problems that need to be solved efficiently, propelling the market further.
• Use of cutting-edge tools- another factor that drives the market is the usage of cutting-edge tools in life sciences, particularly deep learning and machine learning. Both technologies have emerged as significantly transformative new-age tools because they assist in the rapid assessment of vast datasets like chemical libraries, genomic data, and clinical trial data to detect possible drug candidates more effectively and precisely than conventional analysis methods, which are time-consuming and costly.
• AI’s ability to predict drug-target interaction- AI holds the potential to analyze complex data that predict drug-target interactions and simulate clinical results, making it an indispensable tool for modern drug discovery. Thus, leading companies are collaborating and investing hugely to positively affect their drug discovery pipeline. For instance, Pfizer collaborated with IBM Watson to use AI for immuno-oncology research. On the other way, Bayer partnered with Recursion Pharmaceuticals to use AI to find innovative technologies and treatments for fibrosis.
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U.S. AI in Life Science Analytics Market Segment insights
By Deployment
By Deployment, the cloud segment accounted for the largest market share and thus dominated the U.S. AI in life science analytics market. The same segment is expected to witness the fastest growth rate as well, owing to its flexibility, highly scalable nature, and cost-effectiveness. Cloud providers give the best solutions for AI-powered services and specific tools that streamline the development and deployment of machine learning models in life sciences. To simplify the AI lifecycle management process, these platforms offer access to AI algorithms that are prebuilt, model development frameworks, and automation in workflows.
On the other hand, the on-premises segment is expected to witness a significant growth rate during the foreseeable period. The growth of this segment can be attributed to factors like fully controlling security measures and customizing IT configurations to meet specific demands of cybersecurity.
By component
By component, the service segment accounted for the largest market share, thus dominating the market. The same segment is expected to grow the fastest during the foreseeable period. The growth of this segment is due to the increasing demand for AI implementation and integration services widely, the complex nature of AI solutions and technologies, and the increasing demand for personalization.
Enterprises across various sectors are intensively acknowledging the importance of AI in increasing operational efficiency, consumer engagement, and decision-making processes. For instance, IBM is the leading AI service provider that offers AI-as-a-service platforms, which allows enterprises to access pre-built AI models and tools for diverse applications like virtual assistants and predictive analytics. The specialty of this platform is to simplify AI adoption and to make it ready-to-use for consumers.
By application
By applications, the sales and marketing segment accounts for the largest market share, thus dominating the U.S. AI in life science analytics market. The segment is expanding due to the growing demand for AI-powered solutions to increase sales effectiveness and consumer engagement and derive market insight within the sector. AI offers life science enterprises the ability to personalize consumer interactions and engagement strategies for personal choices, historical data, and behaviors. AI algorithms can analyze data sets accurately even though it is in a huge format to analyze.
Again, by applications, the research and development segment accounted for the fastest growth rate during the forecast years. The growth of this segment is due to the increasing adoption of analytical solutions across various industries like clinical trials and drug development. Major companies are investing substantial amounts in the development of innovative drugs specifically for life-threatening diseases like cancer, diabetes, and infectious diseases that require extensive research and development. For instance, in Dec 2023, the U.S. Pharmacopeia introduced the USP advanced manufacturing technology lab in the U.S., aiming to provide services for drug manufacturers to increase pharmaceutical production widely and strengthen the supply chain domain.
By end-use
By end use, the pharmaceutical segment accounted for the largest market share, thus dominating the U.S. AI in life science analytics market. AI aids pharmaceutical companies in acquiring precision medicine by analyzing patients' data, medical history, genetic data, and biomarkers to customize strategies for treatments based on individuals' preferences and health conditions. For instance, in March 2024, the WHO developed a well-guided paper that analyses the increasing applications of AI for every stage of vaccine and medicine development and its production.
By end use, the biotechnology segment is anticipated to grow exponentially during the foreseeable period. The growth of this segment is related to the extensive advantages provided by the incorporation of AI technology for efficient strategies and cost-effective decision-making, along with the acceleration of research and development analysis of databases. For instance, in November 2023, Evommune, Inc. and Accutar Biotechnology Inc. made a strategic partnership to find new small molecule therapeutic candidates to treat chronic inflammatory conditions.
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U.S. AI in Life Science Analytics Market Top Key Companies:
• Indegene
• Lexalytics
• Databricks
• SAS Institute, Inc.
• IQVIA
• IBM
• Sorcero
• Axtria
Recent Developments
• In June 2024, Medidata launched Clinical Data Studio, a unified platform that integrates data from both Medidata and non-Medidata sources. This technology allows stakeholders to control data quality and deliver safer trials faster, accelerating decision-making and enabling holistic data and risk strategies. AI helps identify potential issues and safety signals.
• In April 2024, IQVIA and Salesforce announced broadening their global partnership to hasten the development of the Life Sciences Cloud. This collaboration integrates IQVIA OCE innovations with Salesforce's platform, offering customers a comprehensive engagement solution. Leveraging IQVIA's data, domain expertise, and advanced analytics, Salesforce's CRM software aims to revolutionize healthcare professional (HCP) and patient engagement, providing a seamless and effective experience.
• In January 2024, Cleveland Clinic and IBM researchers released a strategy using AI to identify new immunotherapy targets. This marks the initial peer-reviewed publication stemming from their Discovery Accelerator partnership, which aims to progress healthcare and life sciences research.
• In September 2023, SAS introduced SAS Health, a new AI and analytics solution catering to health insurers, providers, and public health agencies. This solution empowers them with flexibility and agility to drive health innovation, ultimately improving health outcomes and patient experiences.
• In August 2023, Indegene launched Invisage, an AI-enabled platform designed for life sciences companies to enhance their go-to-market strategies. Utilizing data from a vast network of healthcare professionals (HCPs) and interactions, InvisageTM facilitates personalized outcomes for HCPs, optimizing engagement and effectiveness in the industry.
• In March 2022, IQVIA introduced OCE+, the latest advancement in its prominent life science customer engagement platform. OCE+ integrates IQVIA’s Next Best recommendation engine into the Orchestrated Customer Engagement (OCE) platform, offering AI-driven suggestions for engaging healthcare professionals (HCPs). This addition enhances HCP experiences, boosts productivity, and increases user ROI.
U.S. AI in Life Science Analytics Market Report Segmentation
This report forecasts revenue growth at country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2019 to 2034. For this study, Statifacts has segmented the U.S. AI in Life Science Analytics Market
By Component
• Software
• Hardware
• Services
By End-user
• Medical Devices
• Pharmaceutical
• Biotechnology
• Others
By Application
• Research and Development
• Sales and Marketing support
• Supply chain analytics
• Others
By Deployment
• On-premise
• Cloud
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