2019 Innovations in Biomarker Analytics

DUBLIN, Nov. 4, 2019 /PRNewswire/ -- The "Innovations in Biomarker Analytics" report has been added to ResearchAndMarkets.com's offering.

Biomarker Analytics has always been one of the most in-demand branches of science relevant to the process of drug discovery and development in the Pharmaceutical Industry. Over the years several advances have been made in the area of biomarker analytics with the aim to accelerate the drug development process. The use of AI-based technology can increase the efficiency of biomarker analytics.

With the huge data deluges generated through various platforms such as omics, diagnostics etc., machine learning and deep learning techniques are slowly proving to be highly effective in sifting through data and identifying critical biomarkers through pattern recognition.

Key Topics Covered:

1. Executive Summary
1.1 Research Objectives
1.2 Research Methodology
1.3 Key Predictions: Biomarker Analytics

2. Biomarkers and Analytics - Introduction
2.1 Biomarkers and Their Role in Drug Development Process
2.2 Critical Data Generation Processes Contributing to Biomarker Identification
2.3 Biomarkers Have Multiple Uses in Drug Development Process

3. Biomarkers and Data Deluge
3.1 Data Processing and Pattern Recognition Key to Biomarker Analytics
3.2 Possible Data Sources for Biomarker Analytics
3.3 Factors Affecting Use of AI in Biomarker Analytics
3.4 Key Aspects and Processes for The Use of AI for Biomarker Analytics

4. Drivers and Challenges Affecting the Use of AI for Biomarker Analytics
4.1 Factors Impacting The Use of AI for Biomarker Analytics
4.2 AI Will Have Both Short-Term and Long-Term Effect on Biomarker Analytics

5. Funding and Investments in AI for Biomarker Analytics and Drug Development
5.1 Increasing Global Life Science Investments in AI start-ups Focused on Drug Development
5.2 Recursion Pharmaceuticals Has Pulled in The Highest Individual Series Funding Round for AI-Based Drug Discovery
5.3 Benevolent AI Is Currently The Highest Funded AI-based Drug Discovery Venture

6. Timeline of Various Industrial Collaborations
6.1 Numerate, NuMedii, and ExScientia Were Some of The Early Movers
6.2 Benevolent AI and Insilico Medicine Were The Trailblazers
6.3 Multiple Research Collaborations Were Agreed in 2016/2017
6.4 GNS Healthcare Reported The Highest Number of Industrial Collaborations in 2017
6.5 The year 2018 Marked The Entry of Multiple AI-based start-ups Focused on Biomarker Analytics and Drug Discovery
6.6 Industrial Collaborations Continue to Be A Global Phenomenon Rather Than Regional Ones
6.7 Atomwise Reported The Highest Potential Industrial Collaboration Deal in 2019
6.8 Global Trends Position North America and Europe as Leaders in Applying AI for Biomarkers and Drug Development Process

7. Industry Landscape of selected companies
7.1 Company Profile: NuMedii & Recursion Pharmaceuticals
7.2 Company Profile: GNS Healthcare & Insilico Medicine
7.3 Company Profile: Standigm & twoXAR
7.4 Company Profile: ExScientia & BioXcel Therapeutics
7.5 Company Profile: Benevolent AI & Berg Health

8. Growth Opportunities
8.1 Growth Opportunity 1: Adoption of AI by The Pharmaceutical Industry for Biomarker Analytics
8.2 Industrial Collaborations Can Lead to Increased Access to Proprietary Databases
8.3 Building More Effective Algorithms and Eliminating Data Bias

9. Appendix

Companies Mentioned

• Atomwise
• Benevolent AI
• Berg Health
• BioXcel Therapeutics
• ExScientia
• GNS Healthcare
• Insilico Medicine
• NuMedii
• Numerate
• Recursion Pharmaceuticals
• Standigm
• twoXAR

For more information about this report visit https://www.researchandmarkets.com/r/a2apc0

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