SC5: Bioassay Quality by Design
THURSDAY, OCTOBER 17 | DINNER 6:15 – 9:15 PM
INSTRUCTOR:
NEW: Daniel Harding, Principal Consultant, Bioassay Sciences
ABOUT THIS COURSE
This short course provides an essential primer for bioassay design, characterization, validation and control. The course covers the biostatistical QbD principles (USP) that will make the assay more robust, reduce variation, control for high invalid or OOS rates. Bioassay methods of calculation, control of outliers, dose exclusion, weighting and replicate strategy are discussed. Selection of validity and systems suitability criteria will be discussed as well as standard selection, qualification and control.
TOPICS TO BE COVERED INCLUDE:
- Range Finder Study Design for Dose Selection
- Number of Doses in the dose response
- Number of Plates
- Plate Layout
- PLA versus 4PL fitting methods
- Outlier ID and Removal
- Dose Masking for PLA
- Robust Design and Optimization for a Bioassay
- Standard Selection and Qualification
- Validity and Systems Suitability criteria selection
- Validity and Systems Suitability setting limits
INSTRUCTOR BIOGRAPHY
NEW: Daniel Harding, Principal Consultant, Bioassay Sciences
Dan Harding is a principal consultant at BioAssay Sciences (BAS), a globally recognized bioassay consulting company for biologicals and vaccines. BAS specializes in the design, calculation and control of potency and relative potency for bioassays. BAS works with international companies and health authorities globally to achieve product development goals aligned to ICH and USP guidance. BAS is a strategic partner of SAS/JMP and a division of Thomas A. Little Consulting. Dan has trained a variety of scientist and engineers using courses in statistical methods and data analysis, Bioassay Design and Validation, design of experiments (DOE), Assay Development and Method Validation, and statistical process control. Dan is passionate about helping CMC teams and others improve the results of bioassays by establishing robust acceptance criteria, improving outlier identification and removal, choosing the right statistical model, and other tools key to understanding bioassays.