AI is reshaping cloud computing in cell biology, genomics and drug development, extending the existing potential of computational and experimental methods. AI helps address the industry's pain points, including lengthy timelines for discovery, high attrition rates during drug development, and ineffective design and execution of clinical trials. The combination of AI and cloud improves global collaboration by providing a compliant way to directly connect research institutes, biopharma companies and clinical sites.
The report includes:
- Impact analysis of artificial intelligence (AI) on the global cloud computing in cell biology, genomics, and drug development
- Insights of the use cases/case studies for AI implementation related to cloud computing in cell biology, genomics, and drug development
- Understanding of AI adoption trends across the major geographic regions
- Review of AI disruption trends across the key industry verticals
- Impact of AI on various stages of the value chain
- Analysis of the companies’ market spendings and forecasting analysis, and a VC investment outlook
Table of Contents
Chapter 1 Key Use Cases for AI Adoption in Cloud Computing in Cell Biology, Genomics and Drug Development- Overview
- Key Use Cases
- Case 1: AI-Optimized Cloud Infrastructure for Genomic Data Analysis
- Case 2: Cloud-Based Digital Twins for Cell Biology and Process Development
- Case 3: AI-Driven Target Discovery and Validation in the Cloud
- Case 4: Intelligent Clinical Trial Data Management and Analytics
- Adoption Trends at the Geography Level
- Adoption Trends in North America
- Adoption Trends in Europe
- Adoption Trends in Asia-Pacific
- Adoption Trends in the Rest of the World
- Impact of AI on Key Industry Verticals
- Biologics and Cell Therapy Development
- Precision Genomics
- Preclinical Research and Toxicology
- Impact of AI on Various Stages of the Supply Chain
- Preclinical Research and Toxicology
- Clinical Development
- Commercial and Manufacturing
- Key Spending by Companies on AI
- Abbreviations Used in the Report
Table 1: Key Spending by Companies on AI
Table 2: Abbreviations Used in This Report
List of Figures
Figure 1: AI Integration Across the Biopharmaceutical Product Development Lifecycle
