Smart Labs, Automation & Technology Virtual Summit on Wednesday, May 19th, 2021.
The life sciences industry faces many complex challenges in its shift towards “Laboratory 4.0,” due to the steep learning curve of technologies and methodology, as well as the adoption of data-centric approaches necessary to drive the change. The Smart Labs, Automation and Technology Virtual Summit brought together pharmaceutical and biotechnology professionals to facilitate discussions and learnings to identify, select, and implement appropriate technologies and strategies to embrace digitization.
The presentations and interactive discussions focused on:
- Identifying emerging technologies that accelerate early discovery and R&D
- Assessing the value proposition for lab automation and develop a roadmap for successful implementation
- Digitally optimizing laboratory workflows to drive efficiency, productivity, and quality gains
- Creating and implementing effective data strategies to facilitate improved decision-making and connectivity
- Managing the mindset and culture shift required for digital empowerment to successfully transition towards end-to-end laboratory automation
- Aligning internal strategies with the evolving vendor landscape and create strong partnership-driven relationships with solutions providers
TetraScience at Smart Labs, Automation and Technology Virtual Summit
Examining the Critical Role of Automation, Technology, and Innovation for Accelerate Scientific Discovery and R&D
Focusing on innovation, technology and optimization, this discussion will explore best practice methods for ensuring the successful adoption and implementation of technology at scale, as well as how this will enhance drug development.
Moderator: Mike Tarselli, Ph.D., MBA, Chief Scientific Officer
Unlocking Data: Using the R&D Data Cloud to Enable Next-Gen Lab Tech
- Digital transformation speeds time-to-insight, reduces complexity, and future-proofs discovery in life sciences R&D
- Vendor-agnostic integrations and connectivity allow data to be unified across the life sciences R&D ecosystem
- Data-centric approaches that automate the full R&D data lifecycle (acquisition, centralization, harmonization) allow for advanced analysis and AI/ML
- Imaging, ‘omics, sequencing, and advanced chromatography workflows yield insights when given harmonized data
- Data interoperability and reproducibility (FAIR data principles) play critical roles in ensuring data integrity of heterogeneous, distributed, and dark data
- How replatforming to the Cloud allows for more flexibility, elasticity, and scalability to accelerate scientific collaboration and discovery
Speaker: Siping "Spin" Wang, President and Chief Technology Officer
For more information on the event, visit the Smart Labs, Automation & Technology event page.