U.S. Life Science Analytics - Industry Report

The U.S. life science analytics market size was estimated at USD 10.85 billion in 2024 and is expected to be worth around USD 28.66 billion by 2034, growing at a compound annual growth rate (CAGR) of 10.2% over the forecast period 2025 to 2034.

U.S. Life Science Analytics Market Report Highlights

• The services component segment dominated the U.S. life science analytics market in 2024 with the highest revenue share of over 40.1% and is expected to be the fastest growing during the forecast period. 
• The descriptive type segment dominated the market and accounted for the highest revenue share of over 28.3% in 2024 .
• The predictive analysis type segment is anticipated to be the fastest-growing during the forecast period. 
• The sales and marketing application segment dominated the market and accounted for the highest revenue share of over 28.5% in 2024 
• The research and development is anticipated to register the fastest growth rate of 10.2% over the forecast period. 
• The on-demand delivery segment dominated the market for life science analytics and accounted for a revenue share of over 50.6% in 2024 
• The pharmaceutical end-use segment dominated the market and accounted for the highest revenue share of over 40.7% in 2024.
• The biotechnology companies’ end-use segment is anticipated to grow fastest during the forecast period. 

The U.S. life science analytics market refers to the production, distribution, and application of life science analytics which is a process of clinical data analysis that provides predictive tools for better patient care. Life science analytics is used to enhance and protect animal and human life. Life science analytics can be characterized as any analytical application deployed by pharmaceutical firms, and clinical research organizations (CROs), including research, marketing, pharmacovigilance, and supply chain. Data analytics in life sciences benefits include predicting virus evolution, analyzing remote data, assisting with price control, budgeting research, and profit forecasts, optimizing research and development, improving risk assessment, enhancing clinical trials, and allowing personalized medicine. 

Predicting virus evolution and analyzing remote data driving the growth of the U.S. life science analytics market. Traditional methods discover viruses only when exhibit symptoms, a technique that fails to identify potentially deadly viruses that emerge due to transmission from one species to another. DNA sequencing can make easy discovery of new viruses by testing against high databases, a task for which big data is ideally suited. The Internet of Medical Things (IoMT) includes implantable, wearable, and remote health monitoring devices. Big data will be critical in analyzing the information from these devices as this market continues to expand rapidly. 

Improving research and development and enhancing risk assessment driving the growth of the U.S. life science analytics market. Life science industries use big data to improve and justify their research budgets. This data can also help them defend their profit forecasts and margins by clearly demonstrating value. Data analytics can speed up data processing and derive more focused R&D business outcomes. Incorporating analytics into R&D can reduce development costs by at least 15%, accelerate approval times by about 6 months, and significantly enhance patient outcomes. Risk management is a vital and non-negotiable process in the life science industry. 

Improving clinical trials and allowing personalized medicine driving the growth of the U.S. life science analytics market. Life sciences companies use technology to ensure clinical trials generate error-free, high-quality data. The aim is to expedite the drug approval process. Data analytics can help organizations transform risk management into a continuous process, allowing them to predict and mitigate risks before they increase. Personalized medicine groups patients based on genomic data leading to more targeted treatment and superior medical outcomes. To succeed and identify the most effective treatment for patients, high amounts of clinical and user-generated data need to be collected, processed, and integrated. Innovative data analytics is the ideal tool for the task. 

Artificial intelligence (AI) based system digests millions of medical journal articles, clinical trial data, and patient records to suggest personalized treatment options based on the new scientific evidence. This helps doctors make more informed decisions, potentially enhancing patient outcomes and increasing survival rates. AI tools can help with data collection from multiple sources and cleaning and organizing for analysis. Machine learning (ML) models can be trained and applied to prepared data to extract insights and patterns. AI can easily collect some of the most accurate and insightful data. Additionally, AI project management tools can collect and analyze this data at a much faster rate, finally reducing the time and cost associated with data analysis.

These beneficial factors of AI help the growth of the U.S. life science analytics market. Coherent Solutions provides expert data analytics services, empowering enterprises with meaningful business insights. It includes 100+ AI and data analytics experts, 30 years in business, 10 locations globally and 95% customer retention rate.