Life Science Omni-Experience
Improving Laboratory Workflows
- Current tools supporting researchers are largely discrete, requiring scientists to manually connect the dots.
- Collaborative research creates numerous data silos, which limit productivity and introduce errors.
Goals and Objectives
- With projects growing in size and complexity, using common cloud, process, and analytics infrastructure can empower researchers while addressing both IP and data security requirements.
- Interconnected apps, automated workflows, and intelligent analytics allow researchers to focus on insights and discovery.
- Interconnected lab applications in a common cloud, including experimental design, execution, data sharing, and analysis applications
- Secure collaborative infrastructure
- Machine learning and automated workflows
- Cognitive computing supporting research data and publication mining
Use Case Summary
- Transparent experiment management across the entire laboratory value chain
- Effective research sharing with external partners
- Cognitive support on global research progress and insights