Alternative approach for defining the particle population requirements for static image analysis based particle characterization methods

Research output: Contribution to journalArticlepeer-review


  • James Clarke
  • John F. Gamble
  • John W. Jones
  • Mike Tobyn

Colleges, School and Institutes

External organisations

  • Bristol Myers Squibb


For image based particle characterisation approaches one of the most common discussion points is determining the number of particles required to have statistical confidence that the measurement is able to adequately describe the distribution of the sample. This topic becomes significantly more challenging when applied to the extraction of single component size distributions from multi-component samples. The aim of this work was to propose a means to accurately assess the particle number requirements using a method specific approach. The method applies a sub-sampling method to the original imaged dataset in order to provide an understanding of the impact of sub-sampling on the ability to accurately reproduce the original distribution. The method was applied to understand the particle number requirements for two batches of theophylline anhydrous with varied particle size distributions, using the input size distribution to guide the requirements for the subsequent multi-component samples of both materials. The results demonstrate the utility of the method to determine the appropriate number of particles required to recreate the size distributions. Whilst the minimum number of particles required to be sampled can be estimated, how those particles are sampled can also affect the validity of the measurement and must be taken into consideration.


Original languageEnglish
Pages (from-to)920-929
Number of pages10
JournalAdvanced Powder Technology
Issue number5
Early online date15 Feb 2019
Publication statusPublished - 1 May 2019


  • Image analysis, Particle shape, Particle size, Sampling, Spectroscopy