Realise the true power of your online, atline and offline biologics data
ABOUT THIS WEBINAR
Eliminate the data analysis bottleneck: Polar High-Throughput Process Development (HTPD) finally brings high-throughput data management and analysis to biopharma development.
Managing bioprocess data is a complex challenge even if you run just a few experiments per month. With HTPD, this can quickly scale up to hundreds of automated, parallelised experiments.
If your company is struggling to co-ordinate data from different laboratory software and instrument systems, then you may see your high hopes in high-throughput fade away. Watch this on-demand webinar to discover why HTPD can offer a solution to these challenges. Used effectively as part of a BioPharma Lifecycle Management strategy, the data generated from HTPD can accelerate development by supporting better decision making and reducing timelines.
Learning outcomes of this webinar:
- Learn how to harvest the true power of your mini bioreactors
- Discover how to maximise the productivity of your cell cultures
- Hear about faster progression through traceable data
- Enable better trend analysis and insight.
Register
Speaker
Matt Clifford, Senior Product Manager, IDBS
Matthew Clifford is a product manager at IDBS with a particular focus on pre-clinical solutions. With over 19 years’ experience working within and alongside the pharma industry, including eight years in informatics roles in a top 20 pharma business supporting discovery and pre-clinical organisations, he has a proven background in industry trends and solutions. At IDBS, Matt leads the development of solutions to support all aspects of R&D across pharma from bench to clinic. Matthew has a degree in Chemistry from the University of Newcastle upon Tyne.
Related topics
Analysis, Analytical Techniques, Biopharmaceuticals, Cell Cultures, High-Throughput Screening (HTS), Informatics, Lab Automation, Technology
Related organisations
IDBS
Hi,
how would you advise to handle(export/store/analyse) research data so as to exhaustively link clinical indicators to experimental results?
Thank you,
Isatou