Particles, Powders and Pills – Optimized Raman across the Formulation Spectrum

October 22, 2020
Renishaw

Webcast

***Live:Friday, November 13, 2020 at 11am EST| 8am PST| 4pm GMT| 5pm CET *** From contaminants in injectables to the fate of APIs in nasal sprays, Raman reveals the identity and distribution of materials in complex formulations. In this webinar we describe the best approaches to characterizing common pharmaceutical samples; from morphologically targeted analysis of filtered particles to full three-dimensional chemical imaging of whole tablets.*** On demand available after final airing until Nov. 13, 2021.***

Register free: https://www.pharmtech.com/pt_w/optimized_raman

Event Overview: This webcast will present methodologies to characterize a range of pharmaceutical materials from contaminant particles through to powders and pressed tablets. Each method requires an approach to ensure nothing is missed but analysis is rapid and complete. From selective pinpoint analysis based on particle morphology, to complete chemical images, the discussion will demonstrate how to optimize Raman data collection and analysis for the sample of interest.

Four cases will be covered

  • Microparticles on a filter
  • Deposits from nasal sprays
  • Mixed powders
  • Pressed tablets

Key Learning Objectives:

  • How to speed analysis of large complex samples without data loss
  • How to best analyze filtered particles
  • The importance of magnification and focus to the analytical result
  • Obtaining quantitative and qualitative data from images
  • Understand the role of Raman spectroscopy in characterizing pharmaceutical products from dispersed particles through to whole tablets

Speakers: Tim Smith, Head of Applications, Renishaw Spectroscopy

Sarah Shidler, Ph.D, Applications Scientist,, Reinshaw Spectroscopy

Time and Date: Friday, November 13, 2020 at 11am EST| 8am PST| 4pm GMT| 5pm CET

On demand available after final airing until Nov. 13, 2021

Sponsor: Renishaw

Register free:https://www.pharmtech.com/pt_w/optimized_raman

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