Pharmaceutical Analysis of Micro Steel Particles
Sponsored by: Novo Nordisk Pharmatech A/S
- Steel Particles
- Multivariate Statistics
- Particle Analysis
Date: 9 May
Days to go: 18
Time: 3PM London/10AM New York
Using Energy Dispersive X-ray Spectroscopy and Multivariate Statistics to Enhance Identification
Regulatory agencies calls for identification and characterization of any intrinsic, inherent or extrinsic particles present in pharmaceuticals. Common methods for particle analysis (optical, vibrational or flow microscopy) may yield some chemical and morphological information; however in the case of extrinsic particles, the identification may stop once a particle has been identified as e.g. metallic.
USP <1787> outlines methods and strategies for particle identification and characterization. Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) are two of the methods discussed in USP <1787>.
This presentation will show how Electron Microscopy, Energy Dispersive X-ray Spectroscopy and Multivariate statistics may be combined to go one step further in identification of different steel particles.
By registering for this presentation you will get an insight into how multivariate statistics may enhance a powerful tool for visible and subvisible particle identification. The presentation will show how this unique combination enables a shift from a subjective to an objective data evaluation; that in spite of the advanced data analysis gives an intuitive answer.
Jonas Hoeg Thygesen, Ph.D.,
Jonas Hoeg Thygesen works at Novo Nordisk Pharmatech as area specialist, where he works with microscopy, microanalyses and develops new analytical methods for material identification. Among his areas of expertise are spectroscopy, microanalysis and advanced data analysis (chemometrics). He holds a Ph.D. from University of Copenhagen within Process Analytical Technology (PAT).
Key Learning Objectives
- Knowledge on how to use SEM/EDS for ID of steel
- How multivariate statistics may help you in obtaining more knowledge from the same data
- Insight into strengths and weaknesses of current analytical tools for particle analysis
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