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The AAPS Journal

, 21:47 | Cite as

Trial Design and Statistical Considerations on the Assessment of Pharmacodynamic Similarity

  • Peijuan ZhuEmail author
  • Chyi-Hung Hsu
  • Jason Liao
  • Steven Xu
  • Liping Zhang
  • Honghui Zhou
Research Article

Abstract

Pharmacodynamics (PD) similarity is an important component to support the claim of similarity between two drugs or devices. This article investigates the trial design and statistical considerations in the equivalence test of PD endpoints. Using bone resorption marker CTX as a case study, the relationship between the PD readouts and drug potency was explored to evaluate the sensitivity of the PD endpoint and guide equivalence margin selection. For PD data that have high baseline variability, one conventional similarity assessment method was to apply baseline-normalization followed by the standard bioequivalence (BE) test (Lancet Haematol. 4:e350–61, 2017, Ann Rheum Dis. 2017). This study showcased the drawbacks of the conventional method for PD data that were close to inhibition saturation, as the baseline-normalization significantly skewed the distribution of the PD data toward non-log-normal. In such cases, the standard BE test can produce an inflated type I error. Alternatively, ANCOVA, when applied to the un-normalized PD data with the baseline as a covariate, produced a satisfactory type I error with sufficient power. Therefore, ANCOVA was recommended for equivalence test of PD markers that has a saturated inhibition profile and high variability at baseline. Moreover, the relationship between PD readouts and drug potency was used to explore the sensitivity of the PD endpoint and it could help justify the equivalence margins, since the standard 80% to 125% BE margin often does not apply to PD. Finally, a decision tree was proposed to help guide the design of the PD equivalence study in the choice of PD endpoints and statistical methods.

Keywords

Analysis of covariance (ANCOVA) Equivalence Baseline normalization Pharmacodynamics (PD) Statistical test Trial simulation 

Notes

Supplementary material

12248_2019_321_MOESM1_ESM.docx (149 kb)
ESM 1 (DOCX 148 kb)

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Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  1. 1.Janssen Research and Development IncRaritanUSA
  2. 2.Merck & Co., IncNorth WalesUSA
  3. 3.Janssen Research & Development IncSpring HouseUSA

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