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analytical method transfer using equivalence tests with reasonable acceptance criteria and appropriate effort: extension of the ISPE concept. L. Kaminski § , U. Schepers § , H. Wätzig* §both authors equally contributed to this article. Supplementary material. Introduction .

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supplementary material

analytical method transfer using equivalence tests with reasonable acceptance criteria and appropriate effort: extension of the ISPE concept

L. Kaminski§, U. Schepers§, H. Wätzig*

§both authors equally contributed to this article

Supplementary material

introduction
Introduction

This file shall provide additional information and hence lead to a better understanding of some circumstances presented in the original paper “ANALYTICAL METHOD TRANSFER USING EQUIVALENCE TESTS WITH REASONABLE ACCEPTANCE CRITERIA AND APPROPRIATE EFFORT: EXTENSION OF THE ISPE CONCEPT” by Kaminski, L., Schepers, U. and Wätzig, H.[1] It does not claim to be an exhaustive explanation of equivalence tests. Please refer to the above mentioned work for detailed information about these tests and their use in analytical method transfer.

[1] L. Kaminski , U. Schepers and H. Wätzig, J. Pharm. Biomed. Anal (2010), doi:10.1016/j.jpba.2010.04.034

test principle

Confidence interval

θ0= 0

CL

CU

Test principle
  • Same test principle for classic t-test and for the equivalence test!

standardized normal distribution of the θvalue

Reference value

classic two sided t test

CU

CL

CL

CU

θ0= 0

classic two sided t-test

High precision and/or high number of samples

Statistically significant but practically irrelevant difference!  transfer wrongly rejected

The t-test paradoxically rewards imprecise working and low data numbers

Statistically insignificant but practically relevant difference!  transfer wrongly accepted

Low precision and/or low number of samples

θ0= 0

equivalence test

CU

CL

θ0= 0

-2%

+2%

CL

CU

-2%

+2%

equivalence test

High precision and/or high number of samples

Same starting position, but an interval of relevance (acceptance interval) with e.g. ±2% is introduced in addition here!

Low precision and/or low number of samples

θ0= 0

equivalence test6

CU

CL

θ0= 0

-2%

+2%

CL

CU

-2%

+2%

equivalence test

High precision and/or high number of samples

The whole confidence interval lies within the interval of relevance  equivalence!

The equivalence test rewards precise working and high numbers of samples

The confidence interval lies partially outside the interval of relevance  no equivalence!

Low precision and/or low number of samples

θ0= 0

classic two sided t test figure 3
classic two sided t-test (Figure 3)

When measurement spread gets higher (e.g. ±2%) the error probability increases to almost 40% at the acceptance limit (approx. 60% acceptance probability)!

acceptance probability of 95%

error probability of 12%

error probability of 5% (ISPE concept)

Acceptance tolerance of approx. 2,3%

equivalence test figure 2

error probability of 5% (ISPE concept)

equivalence test (Figure 2)

Acceptance limit

error probability of 12%

~1,65