Global AI based Clinical Trial Solution Provider Market
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Artificial Intelligence is set of smart technologies that develop and learn from data and perform tasks based on previous experience. The process, clinical trials are a very crucial that enable both innovators and regulators to assess the efficacy of a candidate drug, use of AI in clinical trial save the time and cost efficiencies by providing faster insights to form the decision. AI helps Investigator to answer some questions inlcuding how to consuct study design, site identification & patient recruitment for clinical research and to digitize adverse drug reaction (ADR) documents in pharmacovigilance. The successfully developing a novel therapeutic intervention required around 10 years of time and cost around USD 2.5 billion, However, use of technology like artificial intelligent in clinical trial help to save huge amount of money as well as time.
Increasing number of strategic alliances in deployment of Artificial Intelligence (AI) in clinical trials aims to reduce time as well expenditure during clinical developmental phases is expected to create the lucrative growth in market near the future. Additionally, Regulators around the world have released guideline that encourage biopharma companies to use real world evidence strategies. For instance, US FDA has passed the 21st Century Cures Act, in 2016, that was designed to help bring new innovations and advances to patients more efficiently and faster.
The Global AI-Based Clinical Trial Solution Provider market is segmented on the basis of target therapeutic area, trial phase, end users and region. Based on the therapeutic area, the market is divided into cardiovascular disorders, cns disorders, infectious disorders, metabolic disorders, oncological disorders and other disorders. Based on the trial phase, the market is divided into early phase 1, phase 1, phase 2, phase 3 and phase 4. Based on the end users, the market is divided into pharmaceutical companies, academia and other users. Based on region, the market is studied across North America, Asia-Pacific, Europe, and LAMEA. Among that Europe held the largest share of the market, followed by America and Asia Pacific. On the other hand, North America is expected to dominate the market during the analysis of forecast period.
The key players of this market include Antidote Technologies, Inc., AiCure, LLC, Deep 6 AI, Deep Lens Inc., Innoplexus, Intelligencia.ai, MEDIAN Technologies, Mendel.ai, Phesi, Saama Technologies, Unlearn.AI, Inc. and Trials.ai
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI-based Clinical Trial Solution Providers Market Snapshot
Chapter 4. Global AI-based Clinical Trial Solution Providers Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis of Key AI in Healthcare Companies
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of COVID 19 on CRO Industry
Chapter 5. Market Segmentation 1: Target Therapeutic Area Estimates & Trend Analysis
5.1. Target Therapeutic Area & Market Share, 2020 & 2028
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2028 for the following Target Therapeutic Area:
5.2.1. Cardiovascular Disorders
5.2.2. CNS Disorders
5.2.3. Infectious Disorders
5.2.4. Metabolic Disorders
5.2.5. Oncological Disorders
5.2.6. Other Disorders
Chapter 6. Market Segmentation 2: Trial Phase Estimates & Trend Analysis
6.1. Trial Phase & Market Share, 2020& 2028
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2028 for the following Trial Phase:
6.2.1. Early Phase 1
6.2.2. Phase 1
6.2.3. Phase 2
6.2.4. Phase 3
6.2.5. Phase 4
Chapter 7. Market Segmentation 3: End-Users Estimates & Trend Analysis
7.1. End-Users & Market Share, 2020 & 2028
7.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2028 for the following End-Users:
7.2.1. Pharmaceutical Companies
7.2.2. Academia and Other Users
Chapter 8. AI-based Clinical Trial Solution Providers Market Segmentation 4: Regional Estimates & Trend Analysis
8.1. North America
8.1.1. North America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) estimates and forecasts by Target Therapeutic Area, 2020-2028
8.1.2. North America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) estimates and forecasts by Trial Phase, 2020-2028
8.1.3. North America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) estimates and forecasts by End-Users, 2020-2028
8.1.4. North America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) estimates and forecasts by country, 2020-2028
8.2. Europe
8.2.1. Europe AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Target Therapeutic Area, 2020-2028
8.2.2. Europe AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Trial Phase, 2020-2028
8.2.3. Europe AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by End-Users, 2020-2028
8.2.4. Europe AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by country, 2020-2028
8.3. Asia Pacific
8.3.1. Asia Pacific AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Target Therapeutic Area, 2020-2028
8.3.2. Asia Pacific AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Trial Phase, 2020-2028
8.3.3. Asia Pacific AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by End-Users, 2020-2028
8.3.4. Asia Pacific AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by country, 2020-2028
8.4. Latin America
8.4.1. Latin America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Target Therapeutic Area, (US$ Million)
8.4.2. Latin America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Trial Phase, (US$ Million)
8.4.3. Latin America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by End-Users, 2020-2028
8.4.4. Latin America AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by country, 2020-2028
8.5. Middle East & Africa
8.5.1. Middle East & Africa AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Target Therapeutic Area, (US$ Million)
8.5.2. Middle East & Africa AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by Trial Phase, (US$ Million)
8.5.3. Middle East & Africa AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by End-Users
8.5.4. Middle East & Africa AI-based Clinical Trial Solution Providers Market revenue (US$ Million) by country, 2020-2028
Chapter 9. Competitive Landscape
9.1. Major Mergers and Acquisitions/Strategic Alliances
9.2. Company Profiles
9.2.1. Antidote Technologies, Inc.
9.2.2. AiCure, LLC
9.2.3. Deep 6 AI
9.2.4. Deep Lens Inc.
9.2.5. GNS Healthcare
9.2.6. Innoplexus
9.2.7. Intelligencia.ai
9.2.8. MEDIAN Technologies
9.2.9. Mendel.ai
9.2.10. Phesi
9.2.11. Saama Technologies
9.2.12. Unlearn.AI, Inc.
9.2.13. Trials.ai
9.2.14. Concerto HealthAI
9.2.15. PathAI
9.2.16. OWKIN, INC.
9.2.17. Accutar Biotechnology Inc.
9.2.18. Atomwise, Inc.
9.2.19. BenevolentAI
9.2.20. Berg LLC
9.2.21. Berkeley Lights, Inc.
9.2.22. BioAge Labs, Inc.
9.2.23. Biovista Inc.
9.2.24. C4X Discovery Holdings Plc
9.2.25. Clinithink Ltd
9.2.26. Cloud Pharmaceuticals, Inc.
9.2.27. Cyclica, Inc.
9.2.28. CytoReason
9.2.29. Deep Genomics Inc.
9.2.30. DeepThink Health Inc.
9.2.31. e-therapeutics plc
9.2.32. Envisagenics, Inc.
9.2.33. Exscientia Limited
9.2.34. Insilico Medicine
9.2.35. Lantern Pharma Inc.
9.2.36. Medable, Inc.
9.2.37. Mind the Byte
9.2.38. NuMedii, Inc
9.2.39. Nuritas, Ltd.
9.2.40. Recursion Pharmaceuticals, Inc.
9.2.41. Schrödinger, LLC
9.2.42. Symphony Innovation, LLC
9.2.43. TARA Biosystems, Inc.
9.2.44. twoXAR, Incorporated
9.2.45. Verge Analytics, Inc.
9.2.46. Winterlight Labs Inc.
9.2.47. WuXi Nextcode Genomics
9.2.48. XtalPi Inc.
9.2.49. Other Prominent Player
This study employed a multi-step, mixed-method research approach that integrates:
This approach ensures a balanced and validated understanding of both macro- and micro-level market factors influencing the market.
Secondary research for this study involved the collection, review, and analysis of publicly available and paid data sources to build the initial fact base, understand historical market behaviour, identify data gaps, and refine the hypotheses for primary research.
Secondary data for the market study was gathered from multiple credible sources, including:
These sources were used to compile historical data, market volumes/prices, industry trends, technological developments, and competitive insights.
Primary research was conducted to validate secondary data, understand real-time market dynamics, capture price points and adoption trends, and verify the assumptions used in the market modelling.
Primary interviews for this study involved:
Interviews were conducted via:
Primary insights were incorporated into demand modelling, pricing analysis, technology evaluation, and market share estimation.
All collected data were processed and normalized to ensure consistency and comparability across regions and time frames.
The data validation process included:
This ensured that the dataset used for modelling was clean, robust, and reliable.
The bottom-up approach involved aggregating segment-level data, such as:
This method was primarily used when detailed micro-level market data were available.
The top-down approach used macro-level indicators:
This approach was used for segments where granular data were limited or inconsistent.
To ensure accuracy, a triangulated hybrid model was used. This included:
This multi-angle validation yielded the final market size.
Market forecasts were developed using a combination of time-series modelling, adoption curve analysis, and driver-based forecasting tools.
Given inherent uncertainties, three scenarios were constructed:
Sensitivity testing was conducted on key variables, including pricing, demand elasticity, and regional adoption.