A Simulation Approach to Evaluate the Impact of Patterns of Bioanalytical Bias Difference on the Outcome of Pharmacokinetic Similarity Studies. Issue 1 (3rd February 2020)

• Record Type: Journal Article
• Authors: Obianom, Obinna N.; Okusanya, Olanrewaju O.; Earp, Justin; Thway, Theingi M.
• Is Part Of: Clinical pharmacology & therapeutics. Volume 108:Issue 1(2020)
• Page Start: 107
• Page End: 115
• Publication Date: 2020-02-03
• Subjects: Pharmacology -- Periodicals; Therapeutics -- Periodicals; 615.5
• DOI: 10.1002/cpt.1767
• Languages: English
• ISSNs: 0009-9236

Abstract

Abstract : Pharmacokinetic (PK) similarity studies are vital to assess the biosimilarity of a biosimilar to a reference product. Systematic bias in a bioanalytical method that quantify products could be a potential source of error affecting the variability of the data and influencing the outcome of a PK similarity study. We investigated the impact of six varying patterns of bioanalytical bias difference (biasdiff ) between the similar products on the probability passing the PK similarity test. A population PK model was used to simulate concentration‐time profiles for a biosimilar and a reference product and added biasdiff ranging from 030%. The probability of achieving the PK similarity criteria (90% confidence interval between 0.8 and 1.25) for the maximum serum concentration (Cmax ) and area under the curve (AUC) was assessed. The data indicate that an increase in absolute biasdiff between products of ≥ 10% would decrease the power to assess the similarity criteria for Cmax and AUC.