AI In Life science Analytics Market Size, Share & Trends Analysis Report By Delivery (Cloud, On-premise), By Component (Software, Hardware, Services), By Application, By End-use, By Region, And Segment Forecasts, 2024 - 2030

AI In Life science Analytics Market Size, Share & Trends Analysis Report By Delivery (Cloud, On-premise), By Component (Software, Hardware, Services), By Application, By End-use, By Region, And Segment Forecasts, 2024 - 2030


AI in Life Science Analytics Market Growth & Trends

The global AI in life science analytics market size is anticipated to reach USD 3.6 billion by 2030 and is projected to grow at a CAGR of 10.9% from 2024 to 2030. According to a new report by Grand View Research, Inc. Key factors driving market growth include the increase in clinical trials, drug discovery, and a growing focus on rare diseases. In addition, advancements in deep learning and artificial intelligence are significantly contributing to market expansion. Rapid developments in AI within the healthcare sector and the increasing adoption of these tools by healthcare institutions to streamline workflows are anticipated to be major growth drivers. For example, in February 2024, Trinity, a global leader in life sciences commercialization, launched 'Brand Insights AI.' This new tool facilitates the development, sharing, and refinement of insights across biopharmaceutical brand research. Developed by experts with extensive technical and life sciences expertise, it enables insights and analytics teams to efficiently address brand-related questions.

“GenAI is poised to revolutionize how insights leaders harness the collective power of all their research investments to make quick, informed decisions. The deep investments Trinity has made in the latest AI innovations allow us to put the power in the hands of our clients to efficiently unearth insights from trusted past research. Brand Insights AI represents the intersection of AI and our biopharma-specific market research expertise, combined to supercharge a brand’s insights.”

-Senior Partner and Head of Insights at Trinity

Artificial intelligence is used improve supply chain, validate genetic targets and create novel compounds. The tools are used to enhance clinical trials and improve operational efficiencies while controlling the costs of the processes which is expected to positively contribute to the market growth.

Rising demand for correct and accurate diagnosis of diseases among the population is expected to drive the demand for the adoption of these models. Moreover, companies such as IBM, DeepMind and P1vital Products are working towards development of solutions for accurate diagnosis of diseases such as cancer, central nervous system disorders which is projected to boost the market growth. Moreover, with AI models the drug discovery and development process can be fast tracked which is expected to contribute to the market growth.

COVID-19 pandemic has shown positive impact on adoption of technologically advanced tools in life sciences, thereby boosting the growth of the market. The amount of data generated every day by research and development is unfathomable; thus, AI plays an important role in interpreting data, assisting in the analysis and drawing of relevant information more quickly.AI offers reliable and big data in life science, assisting companies in revamping business model and streamlining biopharma manufacturing.

AI In Life Science Analytics Market Report Highlights
  • Based on the component, the services segment led the market with the largest revenue share of 37.7% in 2023. Factors contributing to the growth include increasing adoption of digitalized services for streamlining of processes in life sciences industry
  • Based on deployment, the cloud segment led the market with the largest revenue share of 51.1% in 2023. Development of cloud-based services, improvement in internet connectivity and increasing digital literacy are the important factors that contribute to the growth of cloud segment
  • Based on application, the sales and marketing segment led the market with the largest revenue share of 33% in 2023, owing to increased incorporation of these tools for automation, personalization and reducing errors
  • Based on end use, the pharmaceutical segment led the market with the largest revenue share of 46.3% in 2023, owing to the increased adoption of the artificial intelligence tools in drug discovery and clinical trials
  • North America dominated the market with the largest revenue share of 50.23% in 2023. High digital literacy among the healthcare providers and favourable government initiatives contributed to the market growth
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Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.1.1. Component
1.1.2. Delivery
1.1.3. Application
1.1.4. End use
1.1.5. Regional scope
1.1.6. Estimates and forecast timeline.
1.2. Research Methodology
1.3. Information Procurement
1.3.1. Purchased database.
1.3.2. GVR’s internal database
1.3.3. Secondary sources
1.3.4. Primary research
1.3.5. Details of primary research
1.4. Information or Data Analysis
1.4.1. Data analysis models
1.5. Market Formulation & Validation
1.6. Model Details
1.6.1. Commodity flow analysis (Model 1)
1.6.2. Approach 1: Commodity flow approach
1.6.3. Volume price analysis (Model 2)
1.6.4. Approach 2: Volume price analysis
1.7. List of Secondary Sources
1.8. List of Primary Sources
1.9. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Component outlook
2.2.2. Delivery outlook
2.2.3. Application type outlook
2.2.4. End use outlook
2.2.5. Regional outlook
2.3. Competitive Insights
Chapter 3. AI In Life Science Analytics Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.2. Market restraint analysis
3.3. AI In Life Science Analytics Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Supplier power
3.3.1.2. Buyer power
3.3.1.3. Substitution threat
3.3.1.4. Threat of new entrant
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Economic landscape
3.3.2.3. Social landscape
3.3.2.4. Technological landscape
3.3.2.5. Environmental landscape
3.3.2.6. Legal landscape
Chapter 4. AI In Life Science Analytics Market: Component Estimates & Trend Analysis
4.1. Component Market Share, 2023 & 2030
4.2. Segment Dashboard
4.3. Global AI In Life Science Analytics Market by Component Outlook
4.4. Software
4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.5. Hardware
4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.6. Services
4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 5. AI In Life Science Analytics Market: Delivery Estimates & Trend Analysis
5.1. Delivery Market Share, 2023 & 2030
5.2. Segment Dashboard
5.3. Global AI In Life Science Analytics Market by Delivery Outlook
5.4. Cloud
5.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.5. On Premise
5.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 6. AI In Life Science Analytics Market: Application Estimates & Trend Analysis
6.1. Application Market Share, 2023 & 2030
6.2. Segment Dashboard
6.3. Global AI In Life Science Analytics Market by Application Outlook
6.4. Research and Development
6.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.5. Sales and Marketing Support
6.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.6. Supply Chain Analytics
6.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.7. Others
6.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 7. AI In Life Science Analytics Market: End Use Estimates & Trend Analysis
7.1. End Use Market Share, 2023 & 2030
7.2. Segment Dashboard
7.3. Global AI In Life Science Analytics Market by End Use Outlook
7.4. Medical Devices
7.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.5. Pharmaceutical
7.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.6. Biotechnology
7.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.7. Others
7.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 8. AI In Life Science Analytics Market: Regional Estimates & Trend Analysis, By Component, By Delivery, By Application, By End Use
8.1. Regional Market Share Analysis, 2023 & 2030
8.2. Regional Market Dashboard
8.3. Global Regional Market Snapshot
8.4. Market Size, & Forecasts Trend Analysis, 2018 to 2030:
8.5. North America
8.5.1. U.S.
8.5.1.1. Key country dynamics
8.5.1.2. Regulatory framework/ reimbursement structure
8.5.1.3. Competitive scenario
8.5.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
8.5.2. Canada
8.5.2.1. Key country dynamics
8.5.2.2. Regulatory framework/ reimbursement structure
8.5.2.3. Competitive scenario
8.5.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
8.5.3. Mexico
8.5.3.1. Key country dynamics
8.5.3.2. Regulatory framework/ reimbursement structure
8.5.3.3. Competitive scenario
8.5.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
8.6. Europe
8.6.1. UK
8.6.1.1. Key country dynamics
8.6.1.2. Regulatory framework/ reimbursement structure
8.6.1.3. Competitive scenario
8.6.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
8.6.2. Germany
8.6.2.1. Key country dynamics
8.6.2.2. Regulatory framework/ reimbursement structure
8.6.2.3. Competitive scenario
8.6.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
8.6.3. France
8.6.3.1. Key country dynamics
8.6.3.2. Regulatory framework/ reimbursement structure
8.6.3.3. Competitive scenario
8.6.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
8.6.4. Italy
8.6.4.1. Key country dynamics
8.6.4.2. Regulatory framework/ reimbursement structure
8.6.4.3. Competitive scenario
8.6.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
8.6.5. Spain
8.6.5.1. Key country dynamics
8.6.5.2. Regulatory framework/ reimbursement structure
8.6.5.3. Competitive scenario
8.6.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
8.6.6. Norway
8.6.6.1. Key country dynamics
8.6.6.2. Regulatory framework/ reimbursement structure
8.6.6.3. Competitive scenario
8.6.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
8.6.7. Sweden
8.6.7.1. Key country dynamics
8.6.7.2. Regulatory framework/ reimbursement structure
8.6.7.3. Competitive scenario
8.6.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
8.6.8. Denmark
8.6.8.1. Key country dynamics
8.6.8.2. Regulatory framework/ reimbursement structure
8.6.8.3. Competitive scenario
8.6.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
8.7. Asia Pacific
8.7.1. Japan
8.7.1.1. Key country dynamics
8.7.1.2. Regulatory framework/ reimbursement structure
8.7.1.3. Competitive scenario
8.7.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
8.7.2. China
8.7.2.1. Key country dynamics
8.7.2.2. Regulatory framework/ reimbursement structure
8.7.2.3. Competitive scenario
8.7.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
8.7.3. India
8.7.3.1. Key country dynamics
8.7.3.2. Regulatory framework/ reimbursement structure
8.7.3.3. Competitive scenario
8.7.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
8.7.4. Australia
8.7.4.1. Key country dynamics
8.7.4.2. Regulatory framework/ reimbursement structure
8.7.4.3. Competitive scenario
8.7.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
8.7.5. South Korea
8.7.5.1. Key country dynamics
8.7.5.2. Regulatory framework/ reimbursement structure
8.7.5.3. Competitive scenario
8.7.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
8.7.6. Thailand
8.7.6.1. Key country dynamics
8.7.6.2. Regulatory framework/ reimbursement structure
8.7.6.3. Competitive scenario
8.7.6.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
8.8. Latin America
8.8.1. Brazil
8.8.1.1. Key country dynamics
8.8.1.2. Regulatory framework/ reimbursement structure
8.8.1.3. Competitive scenario
8.8.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
8.8.2. Argentina
8.8.2.1. Key country dynamics
8.8.2.2. Regulatory framework/ reimbursement structure
8.8.2.3. Competitive scenario
8.8.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
8.9. MEA
8.9.1. South Africa
8.9.1.1. Key country dynamics
8.9.1.2. Regulatory framework/ reimbursement structure
8.9.1.3. Competitive scenario
8.9.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
8.9.2. Saudi Arabia
8.9.2.1. Key country dynamics
8.9.2.2. Regulatory framework/ reimbursement structure
8.9.2.3. Competitive scenario
8.9.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
8.9.3. UAE
8.9.3.1. Key country dynamics
8.9.3.2. Regulatory framework/ reimbursement structure
8.9.3.3. Competitive scenario
8.9.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
8.9.4. Kuwait
8.9.4.1. Key country dynamics
8.9.4.2. Regulatory framework/ reimbursement structure
8.9.4.3. Competitive scenario
8.9.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)
Chapter 9. Competitive Landscape
9.1. Recent Developments & Impact Analysis, By Key Market Participants
9.2. Company/Competition Categorization
9.3. Innovators
9.4. Vendor Landscape
9.4.1. List of key distributors and channel partners
9.4.2. Key customers
9.4.3. Key company market share analysis, 2023
9.4.4. Indegene
9.4.4.1. Company overview
9.4.4.2. Financial performance
9.4.4.3. Technology Type benchmarking
9.4.4.4. Strategic initiatives
9.4.5. Lexalytics
9.4.5.1. Company overview
9.4.5.2. Financial performance
9.4.5.3. Technology Type benchmarking
9.4.5.4. Strategic initiatives
9.4.6. Databricks
9.4.6.1. Company overview
9.4.6.2. Financial performance
9.4.6.3. Technology Type benchmarking
9.4.6.4. Strategic initiatives
9.4.7. SAS Institute, Inc.
9.4.7.1. Company overview
9.4.7.2. Financial performance
9.4.7.3. Technology Type benchmarking
9.4.7.4. Strategic initiatives
9.4.8. IQVIA Inc.
9.4.8.1. Company overview
9.4.8.2. Financial performance
9.4.8.3. Technology Type benchmarking
9.4.8.4. Strategic initiatives
9.4.9. IBM
9.4.9.1. Company overview
9.4.9.2. Financial performance
9.4.9.3. Technology Type benchmarking
9.4.9.4. Strategic initiatives
9.4.10. Sorcero, Inc.
9.4.10.1. Company overview
9.4.10.2. Financial performance
9.4.10.3. Technology Type benchmarking
9.4.10.4. Strategic initiatives
9.4.11. Axtria
9.4.11.1. Company overview
9.4.11.2. Financial performance
9.4.11.3. Technology Type benchmarking
9.4.11.4. Strategic initiatives

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