Product lifecycle approach to cascade impaction measurements.

Over the lifecycle of an orally inhaled product (OIP), multi-stage cascade impactor (CI) measurements are used for different purposes and to address different questions. Full-resolution CIs can provide important information during product development and are widely used but are time- and resource-intensive, highly variable, and suboptimal for OIP quality control (QC) testing. By contrast, Efficient Data Analysis (EDA) combined with Abbreviated Impactor Measurement (AIM) systems pertinent either for QC and-possibly-for adult Human Respiratory Tract (pHRT) has been introduced for OIP performance assessment during and post-development. This article summarizes available evidence and discusses a strategy for using either abbreviated or full-resolution CI systems depending on the purpose of the measurement, such that adequate, accurate, and efficient testing of aerodynamic particle size distribution (APSD) of OIPs can be achieved throughout the lifecycle of a product. Under these proposals, a comprehensive testing program should initially be conducted by full-resolution CI in OIP development to ascertain the product's APSD. Subsequently, correlations should be established from the selected AIM CIs to the corresponding full-resolution system, ideally developing specifications common to both techniques. In the commercial phase, it should be possible to release product using AIM/EDA, keeping the full-resolution CI for investigations, change control, and trouble-shooting, thus optimizing resources for APSD characterization throughout the product lifecycle. If an in vitro-in vivo relationship is established and clinically relevant sizes are known, an AIM-pHRT could serve as a quick indicator that clinically relevant fractions have not changed and also, in the management of post-approval changes.

The effectiveness of quality control samples in pharmaceutical bioanalysis.

The use of quality control (QC) samples in bioanalysis is well established and consistent with regulatory guidance. However, a systematic evaluation of whether QC samples serve the intended purpose of improving data quality has not been undertaken. The Translational and ADME Sciences Leadership Group (TALG) of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) conducted an evaluation to assess whether closer agreement is observed when comparing pharmacokinetic data from two passed runs, than when comparing data from failed and passed (retest) runs. Analysis of data collected across organizations, molecular types and analytical platforms, revealed that bioanalytical methods are very reproducible; and that QC samples improve the overall quality of pharmacokinetic concentration data and justifies their continued use.