Assessment of individual bioequivalence using sufficient bootstrap procedure

2019 ◽  
Vol 18 (3) ◽  
pp. 388-398
Author(s):  
Ufuk Beyaztas
Keyword(s):  
Bootstrap Procedure ◽  
Individual Bioequivalence

The bootstrap procedure in individual bioequivalence

2000 ◽  
Vol 19 (20) ◽  
pp. 2741-2754 ◽  
Author(s):  
Jun Shao ◽  
Shein-Chung Chow ◽  
Bill Wang
Keyword(s):  
Bootstrap Procedure ◽  
Individual Bioequivalence

Comparison of Principal Component Solutions in Two Populations

Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan
Keyword(s):  
Simulation Study ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Component Model ◽  
Bootstrap Procedure ◽  
Factor Loadings ◽  
Component Loadings ◽  
Principal Component Model ◽  
Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

Current Regulatory Standpoint on Evaluating the Bioequivalence of Different Classes of Generic Drugs - Is the Evaluation in the Right Direction?

2019 ◽  
Vol 20 (10) ◽  
pp. 835-844 ◽  
Author(s):  
Francis Micheal ◽  
Mohanlal Sayana ◽  
Balamurali Musuvathi Motial
Keyword(s):  
Generic Drugs ◽  
Bibliographic Databases ◽  
Eligibility Criteria ◽  
Individual Bioequivalence ◽  
Population Bioequivalence ◽  
Standard Tool ◽  
Review Question ◽  
Guidance Documents ◽  
The Right

Background: The concept of evaluating bioequivalence has changed over a period of time. Currently, the Average Bioequivalence approach (ABE) is the gold standard tool for the evaluation of generics. Of late, many debates had arisen about employing ABE approach for the appraisal of all drug categories. This review aims to examine the limitations of ABE approach and the significances of Population Bioequivalence (PBE) and Individual Bioequivalence (IBE) approach, current regulatory thinking for assessing different categories of the drug, whether they are adequately assessed, and the evaluation is in the right direction. Methods: We carried out an organized search of bibliographic databases for peer-reviewed research literatures, regulatory recommendations, guidance documents using a focused review question and eligibility criteria. The standard tools were used to appraise the quality of retrieved documents and to make sure the authenticity of the data. Results: In total 73 references were used in the review, the majority of the references (guidance documents) were from the different regulatory agencies and product-specific guidance. There were 29 product-specific guidance from USFDA and EMA. The limitations of the ABE approach were discussed in detail along with the significances of Population Bioequivalence (PBE) approach and Individual Bioequivalence (IBE) approaches. Conclusion: It is apparent from the review that IBE approach is a precise method for evaluating the drugs as it answers drug interchangeability (prescribability and switchability). IBE approach is followed by PBE approach and ABE approach for the evaluation of different categories of drugs in terms of precision.

Has the Time Come to Employ Population and Individual Bioequivalence for the Evaluation of Generics?

2020 ◽  
Vol 21 (2) ◽  
pp. 112-125
Author(s):  
Francis Micheal ◽  
Mohanlal Sayana ◽  
Rajendra Prasad ◽  
Balamurali Musuvathi Motilal
Keyword(s):  
Therapeutic Index ◽  
Bioequivalence Study ◽  
Open Label ◽  
Statistical Parameters ◽  
Population Mean ◽  
Average Bioequivalence ◽  
Individual Bioequivalence ◽  
Population Bioequivalence ◽  
Enteric Coated ◽  
Bioequivalence Assessment

Background: Bioequivalence studies are a vital part of drug development. The average bioequivalence approach is the standard method of assessment to conclude whether the generic product is bioequivalent to the innovator product. Of late, debates are on whether the average bioequivalence approach adequately addresses drug interchangeability as it considers only population mean for the evaluation especially when highly variable drug products and narrow therapeutic index drugs are dealt with. Hence, the alternative approaches like population bioequivalence and individual bioequivalence assessment approaches emerge as they consider inter/intra-subject variance and subject- by-formulation variance along with population mean. Objectives: The objective of the study was to apply different bioequivalence assessment approaches in a replicate bioequivalence study to evaluate the drug interchangeability. Methods: This was an open-label, single-dose, randomized, balanced, two-treatment, three-period, three-sequence, partial replicate crossover bioequivalence study of omeprazole enteric-coated tablet 20 mg conducted on 48 normal healthy subjects under fed conditions. The plasma concentration of omeprazole was analyzed by a validated bioanalytical method to determine the pharmacokinetic and statistical parameters to assess average bioequivalence, population bioequivalence, and individual bioequivalence. Results: In this study, test formulation was shown to be bio-inequivalent to the reference formulation by average bioequivalence, population bioequivalence, and individual bioequivalence approaches. Conclusion: The outcome of the evaluation clearly states that the bioequivalence outcome of all these approaches are the same. Obviously, it does not mean that these three approaches provide the same outcome though the consideration of variances varies. Certainly, population bioequivalence and individual bioequivalence approach will be more accurate for the assessment of drug interchangeability.

data a; * significance level; a=0.05; * variance of difference of two observations on the log scale; * sigmaW = within-subjects standard deviation; sigmaW=0.355; s=sqrt(2)*sigmaW; * total number of subjects (needs to be a multiple of 2); n=58; * error degrees of freedom for AB/BA cross-over with n subjects in total; n2=n-2; * ratio = mu_T/mu_R; ratio=1.00; run; data b; set a; * calculate power; t1=tinv(1-a,n-2); t2=-t1; nc1=(sqrt(n))*((log(ratio)-log(0.8))/s); nc2=(sqrt(n))*((log(ratio)-log(1.25))/s); df=(sqrt(n-2))*((nc1-nc2)/(2*t1)); prob1=probt(t1,df,nc1); prob2=probt(t2,df,nc2); answer=prob2-prob1; power=answer*100; run; proc print data=b; run; As an example of using this SAS code, suppose µ = 1, σ = 0.355, α = 0.05 and n = 58. The power (as a percentage) is calculated as 90.4. The required number of subjects to achieve a given power can easily be obtained by trial and error using a selection of values of n. An alternative approach is to use trial and error directly on the sample size n for a given power. For more on this see Phillips (1990) and Diletti et al. (1991), for example. 7.4 Individual bioequivalence As noted in Section 7.1, individual bioequivalence (IBE) is a criterion for deciding if a patient who is currently being treated with R can be

2003 ◽  
pp. 362-362
Keyword(s):  
Standard Deviation ◽  
Sample Size ◽  
Degrees Of Freedom ◽  
Trial And Error ◽  
Significance Level ◽  
Individual Bioequivalence ◽  
Alternative Approach ◽  
Within Subjects ◽  
Log Ratio ◽  
Selection Of
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