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Dissolution Method Development and Validation

Dissolution method development and validation are crucial analytical activities for new product development in pharmaceutical industry. This article provides a comprehensive guide covering items to consider for developing and validating dissolution procedures and the accompanying analytical procedures.


Before method development can begin, it is important to characterize the drug substance so that the filter, dissolution medium, volume of medium, and apparatus can be chosen properly in order to evaluate the performance of the dosage form.

  • Performing Filter Compatibility
  • Determining Solubility and Stability of Drug Substance in Various Media
  • Choosing a Medium and Volume
  • Choosing an Apparatus


A properly designed test should yield data that are not highly variable, and ideally should be free of significant stability problems. High variability in the results can make it difficult to identify trends or effects of formulation changes. The number of dosage units tested can affect the observed variability. One guidance defines dissolution results as highly variable if the relative standard deviation (RSD) is more than 20% at time points of 10 min or less and more than 10% at later time points for 12 dosage units tested.

  • Deaeration
  • Sinkers
  • Agitation
  • Study Design (Time Points, Observations, Sampling, Cleaning)
  • Data Handling
  • Dissolution Procedure Assessment


  • Sample Processing
  • Filters
  • Centrifugation
  • Analytical Procedure
  • Spectrophotometric Analysis/ Chromatography


  • Medium Preparation
  • Sample Introduction and Timing
  • Sampling and Filtration
  • Cleaning
  • Operating Software and Computation of Results
  • Common Deviations from the Compendial Procedures that May Require Validation


Depending on the parameter of interest, validation of the sample handling and analytical procedure can be performed in situ, e.g., within the dissolution vessel. The validation parameters addressed and the extent of the validation may vary, depending on the phase of development or the intended use for the data.

  • Specificity/Placebo Interference
  • Linearity and Range
  • Accuracy/Recovery
  • Precision (Repeatability, Ruggedness, Reproducibility)
  • Robustness
  • Stability of Standard and Sample Solutions
  • Considerations for Automation


  • USP NF 〈1092〉

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