Life Science Analytics Market By Type of Analytics (Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Diagnostic Analytics, Cognitive Analytics), By Application (Clinical Trials, Regulatory Compliance, Pharmacovigilance, Sales and Marketing Analytics, Supply Chain Analytics, Research & Development (R&D), Others), By Deployment Mode (On-premise, Cloud-based), By End User (Pharmaceutical & Biotechnology Companies, Medical Device Companies, Contract Research Organizations (CROs), Academic & Research Institutes, Healthcare Providers, Regulatory Authorities, Others), Global Market Size, Segmental analysis, Regional Overview, Company share analysis, Leading Company Profiles And Market Forecast, 2025 – 2035

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Industry Outlook

The Life Science Analytics market accounted for USD 10.73 Billion in 2024 and USD 11.55 Billion in 2025 is expected to reach USD 24.07 Billion by 2035, growing at a CAGR of around 7.62% between 2025 and 2035. Life Science Analytics Market defines the market involved in using data analytics technologies to analyse huge volumes of biological, clinical and pharmaceutical data. It aids in research and development in various fields such as drug discovery, genomics, and patient outcomes by providing information that guides decision-making. Such tools as big data analytics, AI, and machine learning are used in the market to enhance efficiency in the field of life sciences, develop personalised medicine, and boost innovation. The increasing importance of data-driven healthcare and technological breakthroughs is an important driver of its growth.

Industry Experts Opinion

"Implementing AI‑powered analytics equips pharma teams—from sales to manufacturing—to ask natural‑language questions and receive automated insights, unlocking a truly data‑driven culture."

• Betsy Lillian, Lead Writer at Tellius

Report Scope:

Market Dynamics

Increasing adoption of AI-driven data analytics in pharmaceutical research.

The increasing consumption of AI-supported data analytics in the pharmaceutical sector is primarily fuelling the life science analytics market. Major factors driving it are the growing amount and complexity of biomedical data, the growing need for personalised medicine, and the need for more efficient drug discovery and development processes.

Artificial intelligence helps a researcher to quickly scan over big data sets and identify biomarkers and predict responses to possible treatments, as well as reducing cost and time. Going by the National Institutes of Health (NIH), the amount of data that is already being stored in their biomedical repositories amounts to more than 30 petabytes, which goes to show that sophisticated analytics tools are necessary.

The U.S. Food and Drug Administration (FDA) introduced such initiatives as the AI/ML-based Software as a Medical Device (SaMD) action plan, contributing to the regulatory support of AI use in healthcare. The usage of AI tools to process both genomic and clinical data is another topic mentioned by the National Center for Biotechnology Information (NCBI), which enhances the work on precision medicine. Such a combination of technological capability, regulatory approval, and data is boosting the speed of market growth.

Growing volumes of complex biological data fueling analytics growth globally.

Rapid growth of the life science analytics market can be attributed to an increase in the quantity and complexity of biological data from genomics, proteomics, clinical trials, and electronic health records. With research institutions and healthcare providers developing huge volumes of data, extracting insights from the data through state-of-the-art analytics is essential.

The U.S. National Library of Medicine has found that the volumes of human genomic dataset sequences in its archive, the Sequence Read Archive (SRA), have increased exponentially, and in 2024, it had more than 50 petabytes of data. Equally, the European Bioinformatics Institute (EMBL-EBI) indicates that there is an exponential increase in bioinformatics data submitted to its repositories. Such data sets play pivotal roles in precision medicine, drug development, and inducing stratification of patients, all of which have stimulated the need to have a technology that can accommodate high-volume data.

Moreover, the All of Us Research Program by the NIH will target the inclusion of more than one million individuals in the collection of data, and it is clear how large biological data has become. This is a data-ready world, and it requires effective life-science analytics tools to enable innovation and informed decision-making.

Data privacy concerns hinder sharing of sensitive patient information.

Issues related to data privacy act as a big limiting element to the growth of the life science analytics market, especially in the case of sensitive information of the patient. More than 90% of patients believe that privacy is a basic right, and they do not want their health data to be commercialised, and most of them are concerned about the safety of their health data. Most people lack comfort about the transfer of data between healthcare providers electronically or using fax machines since they feel that their data is at risk of being breached.

Research indicates that certain patients hide their health information from clinicians because they fear information leaks, which has a direct bearing on the quality of analytics of incomplete data sets. Patients are demanding legal responsibility over the maltreatment of their health information and therefore want future online healthcare enterprises to be transparent, like their data-sharing or transfer policy.

The government agencies highlight that data sharing can be made more challenging by the domineeringness of unacceptable de-identification strategies, which bear the grave risk of re-identifying them. The quality of shareable data is constrained by these privacy anxieties, and this hinders thorough analysis and the growth of life science analytics.

Expansion of cloud-based analytics platforms in emerging healthcare markets.

Scaling of cloud-based analytics solutions in new healthcare sectors represents a massive opportunity for the Life Science Analytics Market, since it is possible to introduce new levels of data connectivity, analytics updates, and decision support on the drug development and patient care. Governments and educational facilities consider the importance of cloud technologies in handling huge healthcare data, especially in places that lack decent infrastructure in traditional IT systems.

The National Institutes of Health (NIH) in the United States confirms that staying with the cloud promotes research collaboration among research institutions and improves clinical trials and personalised medication. Equally, the World Health Organisation (WHO) emphasises how digital health innovations such as cloud analytics can help improve disease surveillance and the allocation of resources in low- and middle-income countries. The usage saves on the cost and increases scalability, making sophisticated analytics more available. This means that the new markets will be able to use the cloud-based solutions to achieve better results and smooth operations, leading to the rise of the life science analytics market.

Collaborations between academia and industry to accelerate data innovation.

By fusing cutting-edge research with practical application, academic and industry collaborations offer a fantastic opportunity to boost innovation in the life science analytics market. Industry partners offer practical data, resources, and commercialisation opportunities, while academic partners can offer in-depth expertise in biology, data science, and sophisticated analytics methods. Such synergy makes it possible to develop predictive models, develop personalised medicine, and discover drugs more quickly.

The U.S. National Institutes of Health (NIH) reports that there has been a considerable investment in biomedical data science, with more than 500 million spent in recent years, investing in integrative research. Moreover, one of the National Science Foundation (NSF) reports reveals that the translation of data-driven insights into clinics has grown by 30 per cent in the past decade due to the involvement of public-private partnerships in the area of health analytics. This collaboration can lead to producing a skilled workforce, which will make innovations sustainable in the future. All these initiatives are likely to facilitate more effective healthcare solutions and unleash new market share in the life science analytics market across the world.

Segment Analysis

Based on the Type of Analytics, the Life Science Analytics market has been classified into Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, Diagnostic Analytics, and Cognitive Analytics. Descriptive analytics is the most outstanding solution in the life science analytics market. The differentiated factor underlying this dominance is that the pharmaceutical and biotech firms need to gain insights by using the historical records to track the clinical trials, patient outcomes, and the efficiency of the operation.

The potential benefits of descriptive analytics include making stakeholders aware of the trends, in addition to being able to measure their performance and ascertain compliance with regulatory issues by giving them a clear data-based overview of matters. It is commonly used in all the R&D, marketing, and supply chains due to its administrative basis in the decision-making process. With the industry still getting immense piles of data, descriptive analytics is the initial critical task to make full use of it.

Based on the application, the Life Science Analytics market has been classified into Clinical Trials, Regulatory Compliance, Pharmacovigilance, Sales and Marketing Analytics, Supply Chain Analytics, Research & Development (R&D), and Others. The clinical trials application segment is the most notable in the life science analytics market. The more clinical research became sophisticated, the more companies invested in R&D and necessitated more efficient drug development in a more time-efficient manner; the greater is the necessity of incorporating advanced analytics in clinical research. Analytics assist in bringing trial design, patient recruitment, and real-time monitoring to optimise costs and timelines. As the decentralised trials and personalised medicine become increasingly popular, it is apparent that analytics in clinical trials remains a top priority in life sciences companies and is gaining momentum day by day.

Regional Analysis

The North American life science analytics market has a high growth rate in terms of technology, well-developed healthcare facilities, and the concentration of major pharmaceutical and biotechnology firms. The area is the world centre of the clinical research and drug development industry, which also contributes to the increasing needs of advanced data analytics solutions to improve efficiency and regulatory compliance. The United States is leading in the market because it heavily invests in healthcare IT, has a large number of users of electronic health records (EHRs), and the government supports them.

The market is occupied by key players, and the approach toward personalised medicine is emerging, which also stimulates the market. R&D and decision-making are getting increasingly involved with big data, AI, and predictive analytics. Analytics tool adoption is continuing due to an increasing demand to improve patient outcomes and lower costs. Canada is also experiencing constant growth, confirmed by an increase in healthcare digitisation and scholarly partnerships. In the context of life science analytics, North America continues to be at the forefront when it comes to innovation and adoption

The Asia-Pacific region is becoming a fast-growing market in the life science analytics market practices due to the growing investments in healthcare, expanding pharmaceutical markets, and the growing digital health technologies. Such countries as China, India, Japan, and South Korea are on the front line since they have an immense number of patients, friendly government programmes, and an increasing interest in precision medicine. Advanced analytic tools are becoming increasingly popular because organisations strive to enhance clinical outcomes, simplify research, and control costs.

Further, the integration of AI, big data, and cloud-based applications is changing the landscape of data analysis in clinical trials, research and development, and the care of patients. Availability of expert labour and inter-firm interactions between local companies and multinational corporations also boost the development of the market. The privacy of data and the unequal digital infrastructure in a few countries are issues, though. Nonetheless, there lie plenty of prospects in the innovation and growth of life science analytics in the region.

Competitive Landscape

The life science analytics market is highly competitive due to the extensive development of AI, cloud computing, and integration. Key competitors such as IQVIA, SAS, Oracle, IBM, Accenture, and Cognisant further lead through the provision of end-to-end analytics solutions focused on drug development, clinical trials, and patient outcomes. Firms like EPAM and Certara are growing into acquisition and development in real-world evidence and regulatory analytics.

The recent demonstrations of generative AI integration into healthcare workflows reported in popular media, such as IQVIA working with Salesforce to integrate generative AI into patient engagement and Cognisant collaborating with NVIDIA on using generative AI to build new products in healthcare, indicate that the partners of these companies are aware of the same trend.

The emergence of start-ups is also seen within this industry, and therefore, the market is also seeing a replacement of the conventional BI tools with intelligent, predictive analytics platforms that enhance regulatory compliance and decision-making in the life sciences industry.

Life Science Analytics Market, Company Shares Analysis, 2024

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Recent Developments:

• In May 2025, UK-based life sciences investment firm Syncona announced a strategic wind-down of its portfolio due to pressure in the biotech market. The firm planned to return capital to shareholders. At the same time, it aimed to continue supporting select high-potential assets. This move marked a shift in its investment approach.
• In April 2025, Siemens AG completed the acquisition of Dotmatics, a scientific R&D software company, for $5.1 billion. This deal expanded Siemens’ capabilities in life science analytics. It also strengthened their AI-driven data management solutions. The acquisition became part of Siemens’ Xcelerator platform.

Report Coverage:

By Type of Analytics

• Descriptive Analytics
• Predictive Analytics
• Prescriptive Analytics
• Diagnostic Analytics
• Cognitive Analytics

By Application

• Clinical Trials
• Regulatory Compliance
• Pharmacovigilance
• Sales and Marketing Analytics
• Supply Chain Analytics
• Research & Development (R&D)
• Others

By Deployment Mode

• On-premise
• Cloud-based

By End User

• Pharmaceutical & Biotechnology Companies
• Medical Device Companies
• Contract Research Organizations (CROs)
• Academic & Research Institutes
• Healthcare Providers
• Regulatory Authorities
• Others

By Region

North America

• U.S.
• Canada

Europe

• U.K.
• France
• Germany
• Italy
• Spain
• Rest of Europe

Asia Pacific

• China
• Japan
• India
• Australia
• South Korea
• Singapore
• Rest of Asia Pacific

Latin America

• Brazil
• Argentina
• Mexico
• Rest of Latin America

Middle East & Africa

• GCC Countries
• South Africa
• Rest of Middle East & Africa

List of Companies:

• IQVIA
• Oracle Corporation
• SAS Institute Inc.
• IBM Corporation
• Parexel International Corporation
• Cognizant Technology Solutions
• EPAM Systems
• Dassault Systèmes
• Certara
• Cytel Inc.
• Zifo RnD Solutions
• Syneos Health
• PharmaLex GmbH
• Clinithink Ltd.
• Accenture

Frequently Asked Questions (FAQs)