Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?
Autor: | Piotr J. Rudzki, Przemyslaw Biecek, Michał Kaza |
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Rok vydání: | 2019 |
Předmět: |
Quality Control
Societies Pharmaceutical Computer science bioanalysis Pharmacology toxicology Pharmaceutical Science Sample (statistics) Validation Studies as Topic bioanalytical method validation 030226 pharmacology & pharmacy Clinical study 03 medical and health sciences Current sample 0302 clinical medicine Statistics Humans bridging data incurred sample reanalysis (ISR) Clinical Trials as Topic Models Statistical United States Food and Drug Administration hypergeometric distribution Reproducibility of Results Hypergeometric distribution United States 3. Good health Sample size determination 030220 oncology & carcinogenesis Sample Size Research Article |
Zdroj: | The AAPS Journal PubMed Central |
ISSN: | 1550-7416 |
DOI: | 10.1208/s12248-019-0293-2 |
Popis: | Reliable results of pharmacokinetic and toxicokinetic studies are vital for correct decision making during drug discovery and development. Thus, ensuring high quality of bioanalytical methods is of critical importance. Incurred sample reanalysis (ISR)—one of the tools used to validate a method—is included in the bioanalytical regulatory recommendations. The methodology of this test is well established, but the estimation of the sample size is still commented on and contested. We have applied the hypergeometric distribution to evaluate ISR test passing rates in different clinical study sizes. We have tested both fixed rates of the clinical samples—as currently recommended by FDA and EMA—and a fixed number of ISRs. Our study revealed that the passing rate using the current sample size calculation is related to the clinical study size. However, the passing rate is much less dependent on the clinical study size when a fixed number of ISRs is used. Thus, we suggest using a fixed number of ISRs, e.g., 30 samples, for all studies. We found the hypergeometric distribution to be an adequate model for the assessment of similarities in original and repeated data. This model may be further used to optimize the sample size needed for the ISR test as well as to bridge data from different methods. This paper provides a basis to re-consider current ISR recommendations and implement a more statistically rationalized and risk-controlled approach. |
Databáze: | OpenAIRE |
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