<img src="https://ml.globenewswire.com/Resource/Download/908fb457-7f8e-4a08-9081-5565e3dfb3d7?size=2" nborder="0" align="left" hspace="5" vspace="5" title="22157.jpg" alt="Company Logo"/>The pharma predictive analytics market offers opportunities in AI-driven drug discovery, maximizing healthcare and real-world data usage, and leveraging hybrid cloud deployments for improved data compliance. Rising AI and ML adoption expands drug development efficiency, but compliance complexities persist across regions.Dublin, July 03, 2026 (GLOBE NEWSWIRE) -- The <a href="https://www.researchandmarkets.com/reports/6247215/pharma-predictive-analytics-market-share?utm_source=GNE&amp;utm_medium=PressRelease&amp;utm_code=zhs2lg&amp;utm_campaign=2292569+-+Pharma+Predictive+Analytics+Market+Soars+to+%249.37+Billion+by+2031+with+28.42%25+CAGR+Growth&amp;utm_exec=clshmsai" rel="nofollow" target="_blank" title="Pharma Predictive Analytics - Market Share Analysis, Industry Trends &amp; Statistics, Growth Forecasts (2026-2031)">"Pharma Predictive Analytics - Market Share Analysis, Industry Trends &amp; Statistics, Growth Forecasts (2026-2031)"</a> has been added to ResearchAndMarkets.com's offering. The pharma predictive analytics market size is expected to increase from USD 2.09 billion in 2025 to USD 2.68 billion in 2026 and reach USD 9.37 billion by 2031, growing at a CAGR of 28.42% over 2026-2031. This report is segmented by component (software and services), deployment (on-premise and cloud-based), technology (Big Data analytics, and more), data source (clinical-trial data, and more), application (drug discovery &amp; development, and more), therapeutic area (oncology, and more), end user (pharmaceutical companies, and more), and geography. The market and forecasted in terms of value (USD). Global Pharma Predictive Analytics Market Trends and Insights Rising Adoption of AI &amp; ML in Drug Discovery The pharma predictive analytics market is seeing a stronger commitment to AI-led drug discovery from large pharmaceutical and technology companies. In January 2026, NVIDIA and Eli Lilly announced a co-innovation AI lab with planned investment of up to USD 1 billion over 5 years to connect wet-lab and dry-lab learning systems in a continuous loop. Merck states in March 2026 that its KERMT deep-learning model, trained on more than 11 million molecules, is already cutting early development timelines by 30% or more by screening out weak candidates before costly synthesis. Growing Volume of Healthcare &amp; Real-World Data The pharma predictive analytics market is gaining momentum from the simultaneous expansion of data volume and regulatory usability in real-world evidence. In December 2025, the FDA removes a major barrier by allowing sponsors to use de-identified real-world datasets in submissions without requiring individual patient-level data in every case. In March 2026, the agency adopts ICH M14, creating clearer standards for design and reporting of non-interventional pharmacoepidemiological studies used in post-approval safety assessment. Data-Privacy &amp; Multi-Jurisdiction Compliance Complexity The market still faces material friction from privacy rules and model-governance obligations that differ across regions. In the US and Europe, expectations now extend beyond basic data handling into transparency, bias control, documentation, and post-deployment monitoring for high-risk AI systems. The EU AI Act, scheduled for full enforcement for high-risk AI systems in August 2026, increases the compliance load for many pharma analytics applications. Segment Analysis Software held 68.34% share in 2025, while services are forecast to grow at a 28.93% CAGR through 2031. The market still leans toward software as enterprise buyers seek integrated analytics suites that support discovery, clinical, safety, and commercial teams on a common platform. Cloud-native architecture eases large deployments across functions, aiding software expansion. On-premise retained 64.82% share in 2025, while cloud-based deployment is projected to grow at a 29.36% CAGR through 2031. The market maintains a large on-premise base due to major pharmaceutical companies prioritizing IP protection, internal control, and compatibility with legacy data centers. Cloud adoption is rising, but local infrastructure remains crucial. Big data analytics held 36.18% share in 2025, while AI and ML are projected to grow at a 30.42% CAGR through 2031. The market depends on big data infrastructure as model performance falters when data pipelines are fragmented, low volume, or poorly curated. AI and ML's value is visible in candidate optimization and patient stratification. Geography Analysis North America accounted for 36.46% of the market size in 2025, attributed to deep pharmaceutical R&amp;D spending, broad real-world data assets, and regulatory clarity around AI-supported evidence generation. The market benefits from stronger institutional capacity to document and validate AI tools in regulated settings. Europe remains a significant center, combining advanced research clusters with a strict compliance framework. The EU AI Act raises implementation burden but also formalizes governance expectations. Asia-Pacific is projected to grow at a 32.98% CAGR through 2031, driven by digital health mandates and regional deployment models. List of Companies Covered in this Report: <ul><li>Aetion</li><li>Axtria</li><li>Benevolent AI</li><li>BioAge Labs</li><li>Clarivate</li><li>ConcertAI</li><li>Cytel</li><li>Deep 6 AI</li><li>Exscientia</li><li>GNS Healthcare</li><li>IBM Watson Health / Merative</li><li>Indegene</li><li>IQVIA</li><li>Medidata Solutions</li><li>Optum</li><li>Oracle Health Sciences</li><li>Owkin</li><li>Saama Technologies</li><li>SAS Institute</li><li>ZS Associates</li></ul> Key Topics Covered: 1 Introduction 1.1 Study Assumptions &amp; Market Definition 1.2 Scope of the Study 2 Research Methodology 3 Executive Summary 4 Market Landscape 4.1 Market Overview 4.2 Market Drivers 4.2.1 Rising Adoption of AI &amp; ML in Drug Discovery 4.2.2 Growing Volume of Healthcare &amp; Real-World Data 4.2.3 Increasing Focus on Personalized &amp; Precision Medicine 4.2.4 Need to Reduce Clinical-Trial Costs &amp; Improve Success Rates 4.2.5 Emergence of Federated Learning for Cross-Institution Analytics 4.2.6 Accelerating Regulatory Sandboxes for Real-Time Trial Analytics 4.3 Market Restraints 4.3.1 Data-Privacy &amp; Multi-Jurisdiction Compliance Complexity 4.3.2 High Implementation &amp; Integration Costs 4.3.3 Algorithmic Bias Triggering Regulatory Push-Back 4.3.4 Shortage of Curated Domain-Specific Labeled Datasets 4.4 Value / Supply-Chain Analysis 4.5 Regulatory Landscape 4.6 Technological Outlook 4.7 Porter's Five Forces Analysis 4.7.1 Threat of New Entrants 4.7.2 Bargaining Power of Buyers 4.7.3 Bargaining Power of Suppliers 4.7.4 Threat of Substitutes 4.7.5 Competitive Rivalry 5 Market Size &amp; Growth Forecasts (Value, USD) 5.1 By Component 5.1.1 Software 5.1.2 Services 5.2 By Deployment 5.2.1 On-Premise 5.2.2 Cloud-Based 5.3 By Technology 5.3.1 Artificial Intelligence (AI) &amp; Machine Learning (ML) 5.3.2 Natural Language Processing (NLP) 5.3.3 Big Data Analytics 5.3.4 Others 5.4 By Data Source 5.4.1 Electronic Health Records (EHRs) 5.4.2 Clinical-Trial Data 5.4.3 Genomic Data 5.4.4 Claims &amp; Billing Data 5.4.5 Real-World Evidence (RWE) Data 5.4.6 Others 5.5 By Application 5.5.1 Drug Discovery &amp; Development 5.5.2 Clinical-Trial Optimization 5.5.3 Patient Outcome Prediction 5.5.4 Pharmacovigilance &amp; Drug Safety 5.5.5 Precision Medicine 5.5.6 Others 5.6 By Therapeutic Area 5.6.1 Oncology 5.6.2 Cardiovascular Diseases 5.6.3 Neurology 5.6.4 Infectious Diseases 5.6.5 Others 5.7 By End User 5.7.1 Pharmaceutical Companies 5.7.2 Biotechnology Companies 5.7.3 Contract Research Organizations (CROs) 5.7.4 Others 5.8 By Geography 5.8.1 North America 5.8.1.1 United States 5.8.1.2 Canada 5.8.1.3 Mexico 5.8.2 Europe 5.8.2.1 Germany 5.8.2.2 United Kingdom 5.8.2.3 France 5.8.2.4 Italy 5.8.2.5 Spain 5.8.2.6 Rest of Europe 5.8.3 Asia-Pacific 5.8.3.1 China 5.8.3.2 India 5.8.3.3 Japan 5.8.3.4 Australia 5.8.3.5 South Korea 5.8.3.6 Rest of Asia-Pacific 5.8.4 Middle East and Africa 5.8.4.1 GCC 5.8.4.2 South Africa 5.8.4.3 Rest of Middle East and Africa 5.8.5 South America 5.8.5.1 Brazil 5.8.5.2 Argentina 5.8.5.3 Rest of South America 6 Competitive Landscape 6.1 Market Concentration 6.2 Market Share Analysis 6.3 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as Available, Strategic Information, Market Rank/Share for Key Companies, Products &amp; Services, and Recent Developments) 6.3.1 Aetion 6.3.2 Axtria 6.3.3 BenevolentAI 6.3.4 BioAge Labs 6.3.5 Clarivate 6.3.6 ConcertAI 6.3.7 Cytel 6.3.8 Deep 6 AI 6.3.9 Exscientia 6.3.10 GNS Healthcare 6.3.11 IBM Watson Health / Merative 6.3.12 Indegene 6.3.13 IQVIA 6.3.14 Medidata Solutions 6.3.15 Optum 6.3.16 Oracle Health Sciences 6.3.17 Owkin 6.3.18 Saama Technologies 6.3.19 SAS Institute 6.3.20 ZS Associates For more information about this report visit <a href="https://www.researchandmarkets.com/reports/6247215/pharma-predictive-analytics-market-share?utm_source=GNE&amp;utm_medium=PressRelease&amp;utm_code=zhs2lg&amp;utm_campaign=2292569+-+Pharma+Predictive+Analytics+Market+Soars+to+%249.37+Billion+by+2031+with+28.42%25+CAGR+Growth&amp;utm_exec=clshmsai" rel="nofollow" target="_blank" title="">https://www.researchandmarkets.com/r/zhkv63</a> About ResearchAndMarkets.com ResearchAndMarkets.com is the world's leading source for international market research reports and market data. 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Pharma Predictive Analytics Market Soars to $9.37 Billion by 2031 with 28.42% CAGR Growth

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