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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 .

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Supplementary material

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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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%

  8. error probability of 5% (ISPE concept) equivalence test (Figure 2) Acceptance limit error probability of 12% ~1,65

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