Global AI based Clinical Trial Solution Provider Market

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

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

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

• Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
• External and internal proprietary databases, regulatory databases, and relevant patent analysis
• Statistical databases, National government documents, and market reports
• Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

• Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
• Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
• Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
• End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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