BioPharm October eBook: Best Practices 2018

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Page 22 of 27 October 2018 BioPharm International eBook 23 All figures courtesy of the author DEVELOPING ANALYTICAL METHODS It is worth noting that, irrespec- tive of the approach taken, ulti- mately an assay (assay and method are terms used interchangeably throughout the text) should be based on severa l f u nda menta l principles, which include the fol- lowing: • Sound scientific strategy as the basis for the method • An assay that is suitable for the intended use • An assay that is accurate, pre- cise, and robust • Ensuring that all data support- ing the assay development are reviewed and verifiable • Ensuring that data reduction is based on transparent and sound calculations • Making sure that documenta- tion suppor ting the method development is captured in real time • Making sure that development details are legible, if captured on paper, complete, and easy to fol- low. If the development of an ana- lytical method is to be pursued based on the QbD concept, as it is strongly recommended, one needs to follow the multiple discrete steps outlined in Figure 1. Unlike the traditional analyti- cal method development approach, where method variables are tested one at a time in a serial fashion, QbD applies a systematic meth- odology resulting in a full under- standing of var ious sources of method variation and control of the method. The development process starts out by defining the analytical tar- get profile (ATP). For most analyti- cal methods, the assay ATP should minimally include a basic state- ment with respect to method accu- racy (bias) and precision (variance). For instance, the procedure must typically be sufficiently accurate to measure concentration of the analyte within 95 –105% of the nominal concentration and pre- cise based on relative standard deviation (RSD) values of 3% or less. Once a target profile has been defined, it is then time to identify an appropriate analytical technol- ogy that will deliver on the tar- get profile requirements. The type of analytical technique selected will be dependent on the product attribute to be measured and the needed level of accuracy and preci- sion. Table I provides some exam- ples of product quality attributes and correspondingly applicable analytical methods. PERFORMING RISK ASSESSMENT Once the appropriate method is selected, it will be necessary to start scouting assay conditions. For chromatography, identifying the correct column is crucial to assay performance. For this reason, sev- eral columns with varying char- acteristics, such as carbon loads for reverse-phase, pore-size and sil- ica modification for size-exclusion chromatography, as well as column manufacturers, should be carefully evaluated. These evaluations cou- pled with historical knowledge and information gleaned from compre- hensive literature searches help to identify critical method parame- ters (CMP). Figure 1. Diagram of method development by quality by design (QbD). DoE is design of experiment. Biopharma Laboratory Best Practices Analytical Methods Table I. Analytical methods and product quality attributes. Product attribute Analytical methods Identit y N-terminal sequencing, peptide mapping, enz yme-linked immunosorbent assay (ELISA), Western blot, high-per formance liquid chromatography (HPLC), electrophoresis Aggregation High per formance/ultra per formance size exclusion chromatography (HP/UP-SEC), analy tical ultracentrifugation (AUC), field-flow fractionation (FFF) Purit y Reverse-phase (RP)-HPLC, hydrophobic interaction chromatography (HIC), capillar y electrophoresis sodium dodecyl sulfate (CE-SDS), Sodium dodecyl sulfate polyacr ylamide gel electrophoresis (SDS- PAGE) Strength Absorbance, colorimetric assay, ELISA Potency Cell-based assay, ELISA, sur face plasmon resonance (SPR) Par ticulates Light obscuration (HIAC), microfluidic imaging (MFI), Coulter counter

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