Literature DB >> 11033581

Properties of the estimated variance component for subject-by-formulation interaction in studies of individual bioequivalence.

L Endrenyi1, N Taback, L Tothfalusi.   

Abstract

Characteristics of the variance component for the subject-by-formulation interaction (sigma(2)(D)), estimated in simulated studies of individual bioequivalence and in three- and four-period cross-over trials reported by the FDA, were compared. sigma(2)(D) was estimated by (i) restricted maximum likelihood (REML) and (ii) the method of moments (MM). Variation of the variance component, estimated by both procedures (s(2)(D)) and for both the simulated and FDA data, increased with rising intra-individual variation. Consequently, a constant level of s(2)(D) (such as 0.0225 suggested by the FDA) may not be regarded as a basis for demonstrating substantial interactions. Features of the FDA and simulated parameters were similar. The results suggested that the FDA data were compatible with assuming sigma(D)=0.05 or perhaps 0.00. Therefore, there is no foundation for concerns about public health. Both simulations and calculations demonstrated that s(2)(D) estimated by MM was unbiased and its variance was proportional to sigma(4)(WF) when sigma(2)(D)=0.

Mesh:

Year:  2000        PMID: 11033581     DOI: 10.1002/1097-0258(20001030)19:20<2867::aid-sim551>3.0.co;2-j

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

1.  Subject-by-formulation interaction in bioequivalence: conceptual and statistical issues. FDA Population/Individual Bioequivalence Working Group. Food and Drug Administration.

Authors:  W W Hauck; T Hyslop; M L Chen; R Patnaik; R L Williams
Journal:  Pharm Res       Date:  2000-04       Impact factor: 4.200

2.  A comparison of the intrasubject variation in drug exposure between generic and brand-name drugs: a retrospective analysis of replicate design trials.

Authors:  Yang Yu; Steven Teerenstra; Cees Neef; David Burger; Marc Maliepaard
Journal:  Br J Clin Pharmacol       Date:  2016-01-15       Impact factor: 4.335

3.  An Exact Procedure for the Evaluation of Reference-Scaled Average Bioequivalence.

Authors:  Laszlo Tothfalusi; Laszlo Endrenyi
Journal:  AAPS J       Date:  2016-01-29       Impact factor: 4.009

4.  Spline functions in convolutional modeling of verapamil bioavailability and bioequivalence. I: conceptual and numerical issues.

Authors:  J Popović
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2006 Apr-Jun       Impact factor: 2.441

Review 5.  Evaluation of bioequivalence for highly variable drugs with scaled average bioequivalence.

Authors:  Laszlo Tothfalusi; Laszlo Endrenyi; Alfredo Garcia Arieta
Journal:  Clin Pharmacokinet       Date:  2009       Impact factor: 6.447

6.  Comment on "Levothyrox® New and Old Formulations: Are they Switchable for Millions of Patients?"

Authors:  Yang Yu; Marc Maliepaard
Journal:  Clin Pharmacokinet       Date:  2020-02       Impact factor: 6.447

  6 in total

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