AAPS PharmSciTech

, Volume 19, Issue 3, pp 1483–1492 | Cite as

A Science and Risk-Based Pragmatic Methodology for Blend and Content Uniformity Assessment

  • Naheed Sayeed-Desta
  • Ajay Babu Pazhayattil
  • Jordan Collins
  • Chetan Doshi
Brief/Technical Note


This paper describes a pragmatic approach that can be applied in assessing powder blend and unit dosage uniformity of solid dose products at Process Design, Process Performance Qualification, and Continued/Ongoing Process Verification stages of the Process Validation lifecycle. The statistically based sampling, testing, and assessment plan was developed due to the withdrawal of the FDA draft guidance for industry “Powder Blends and Finished Dosage Units—Stratified In-Process Dosage Unit Sampling and Assessment.” This paper compares the proposed Grouped Area Variance Estimate (GAVE) method with an alternate approach outlining the practicality and statistical rationalization using traditional sampling and analytical methods. The approach is designed to fit solid dose processes assuring high statistical confidence in both powder blend uniformity and dosage unit uniformity during all three stages of the lifecycle complying with ASTM standards as recommended by the US FDA.


blend uniformity content uniformity dosage uniformity process validation solid dose lifecycle stages 


Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no competing interests.


  1. 1.
    Guidance for Industry, “Powder Blends and Finished Dosage Units—Stratified In-Process Dosage Unit Sampling and Assessment”. U.S. Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), October 2003, Pharmaceutical CGMPs.Google Scholar
  2. 2.
    Question and Answers on Current Good Manufacturing Practices, good guidance practices, level 2 guidance—Production and Process Controls, CDER/OC Office of Manufacturing and Product Quality: CGMP Subject Matter Contacts, 6 August 2013.
  3. 3.
    Garcia T, Bergum J, Prescott J, Tejwani R, Parks T, Clark J, et al. Recommendations for the assessment of blend and content uniformity: modifications to withdrawn FDA draft stratified sampling guidance. J Pharm Innov. 2015;10(1):76–83. Scholar
  4. 4.
    Brittain HG. Particle size distribution II: the problem of sampling powdered solids. Pharm Technol. 2002;26(7):67–73.Google Scholar
  5. 5.
    Alexander A, Sudah O, Arratia P, Duong N-H., Reynolds S, Muzzio F. Characterization of the performance of bin blenders part 3 of 3: cohesive powders. Pharm Technol. 2004;28(9):54–74.Google Scholar
  6. 6.
    Alexander A, Arratia P, Goodridge C, Sudah O, Brone D, Muzzio F. Characterization of the performance of bin blenders part 1 of 3: methodology. Pharm Technol. 2004;13(5):70–86.Google Scholar
  7. 7.
    Alexander A, Sudah O, Arratia P, Goodridge C, Alani L, Muzzio F. Characterization of the performance of bin blenders part 2 of 3: free flowing mixtures. Pharm Technol. 2004;28(7):56–7.Google Scholar
  8. 8.
    Sayeed-Desta N, Pazhayattil A, Chowdari S. “Determining minimum batch size,” APIs, excipients, and manufacturing supplement to. Pharm Technol. 2016;40:s16–9.Google Scholar
  9. 9.
    Collins J, Sayeed-Desta N, Pazhayattil AB, Doshi C. A novel metric for continuous improvement during stage three. BioPharm Int. 2017;30(6):32–5.Google Scholar
  10. 10.
    Bergum J, Parks T, Prescott J, Tejwani R, Clark J, Brown W, et al. Assessment of blend and content uniformity. Technical discussion of sampling plans and application of ASTM E2709/E2810. J Pharm Innov. 2015;10(1):84–97. Scholar
  11. 11.
    Sayeed-Desta N, Pazhayattil AB, Collins J, Chen S, Ingram M, Spes J. Assessment methodology for process validation lifecycle stage 3A. AAPS PharmSciTech. 2017;18(5):1881–6. Scholar
  12. 12.
    Lewis RA, Fan A. Improved acceptance limits for ASTM standard E2810. Stat Biopharm Res. 2016;8(1):40–8. Scholar
  13. 13.
    Nunnally B. Variance component analysis to determine sources of variation for vaccine drug product assays. J Validation Technol. 2009;15(3):78–88.Google Scholar
  14. 14.
    Gelman A. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 2006;1(3):515–33. Scholar
  15. 15.
    Madsen C. Statistical Methods for Assessment of Blend Homogeneity. PhD Thesis for the department of Informatics and Mathematical Modelling, Technical University of Denmark;2002.Google Scholar
  16. 16.
    Snijders TAB. Power and sample size in multilevel linear models. In: Everitt BS, Howell DC, editors. Encyclopedia of statistics in behavioral science, vol. 3. Chicester: Wiley; 2005. p. 1570–3. Scholar
  17. 17.
    Maas CJM, Hox JJ. Sufficient sample sizes for multilevel modeling. Methodology. 2005;1(3):86–92.CrossRefGoogle Scholar
  18. 18.
    Bell BA, Ferron JM, Kromrey J.‘Cluster size in multilevel models: the impact of sparse data structures on point and interval estimates in two-level models’ Joint Statistical Meetings—Section on Survey Research Methods;2008. Google Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2017

Authors and Affiliations

  • Naheed Sayeed-Desta
    • 1
  • Ajay Babu Pazhayattil
    • 1
  • Jordan Collins
    • 1
  • Chetan Doshi
    • 1
  1. 1.Apotex Inc.TorontoCanada

Personalised recommendations