A curve similarity approach to parallelism testing in bioassay.

Potency determination via bioassay is a relative measure that requires an evaluation of parallelism between the dose-response relationships of a reference standard and a sample material. Typical approaches for assessing parallelism include difference ([Formula: see text]-value) and equivalence tests. These traditional methods rely on a statistical assessment of model parameters as opposed to direct evaluation of the similarity of the dose-response curves. We propose a simple curve similarity approach that tests the hypothesis that the sample material is a dilution or concentration of the reference standard. The test is achieved by quantifying and normalizing the total area between the two curves and provides a single composite measure of parallelism. Both a frequentist and a Bayesian approach to the test are provided. We show through a simulation study that the curve similarity approach overcomes the drawbacks of the traditional methods and is effective at detecting parallelism and non-parallelism for bioassays.

A Bayesian Approach to Determination of F, D, and Z Values Used in Steam Sterilization Validation.

For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the well-known DT , z, and Fo values that are used in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these values to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion.LAY ABSTRACT: For manufacturers of sterile drug products, steam sterilization is a common method used to provide assurance of the sterility of manufacturing equipment and products. The validation of sterilization processes is a regulatory requirement and relies upon the estimation of key resistance parameters of microorganisms. Traditional methods have relied upon point estimates for the resistance parameters. In this paper, we propose a Bayesian method for estimation of the critical process parameters that are evaluated in the development and validation of sterilization processes. A Bayesian approach allows the uncertainty about these parameters to be modeled using probability distributions, thereby providing a fully risk-based approach to measures of sterility assurance. An example is given using the survivor curve and fraction negative methods for estimation of resistance parameters, and we present a means by which a probabilistic conclusion can be made regarding the ability of a process to achieve a specified sterility criterion.