Statistics

In the field of pharmaceutical manufacturing, the pharmacist is required to validate the quality of prepared products. For this validation, he must use statistical quality control. The collection of analytical data or data with a go no-go format is meaningless without a conclusion on batch rejection or acceptance. In addition, a decision is worthless when not properly based on sound scientific statistical principles and a carefully conceived sampling plan that considers issues such as sample size and variability. The up scaling of production (batch size, numerous products in a single facility) and by consequence the up scaling of complexity within industry as well as within larger production facilities e.g. hospital pharmacies have led to the application of statistical quality control. Such an approach has been in use since the middle of the past century and is nowadays easily accessible by statistical software programs. This chapter discusses several statistical principles that are used in pharmaceutical quality decisions, such as: normal distribution, rounding, confidence interval, standard deviation, outliers, operating characteristic curves, acceptance sampling, control chart. Examples have been embedded in a pharmaceutical context.