The Bioanalytical Method Workhorses

The most common bioanalytical tools applied for macromolecule drug bioanalysis are IA, HPLC, and LC-MS/MS. 

HPLC-UV is often used for formulation product analysis, but its sensitivity and selectivity is inadequate for bioanalytical application. A gradient elution of 30 to 60 min is often used to provide column separation from the matrix proteins. HPLC-UV methods are not desirable due to low signal-to-noise (S/N) ratios and long chromatographic run times. 

TMB Substrate is added to each well and color develops ( 10 min) in proportion to the amount of drug bound in each well. 

M ore details are given in the example in Section 6.3.1. This format represents a non-competitive assay. Right panel The two formats of noncompetitive and competitive assays. 

The method of choice is dependent upon the analyte, the assay performance required to meet the intended application, the timeline, and cost-effectiveness. The assay requirements include sensitivity, selectivity, linearity, accuracy, precision, and method robustness. Assay sensitivity in general is in the order of IA LC-MS/MS HPLC, while selectivity is IA LC-MS/MS HPLC. However, IA is an indirect method which measures the binding action instead of relying directly on the physico-chemical properties of the analyte. The IA response versus concentration curve follows a curvilinear relationship, and the results are inherently less precise than for the other two methods with linear concentration-response relationships. The method development time for IA is usually longer than that for LC/MS-MS, mainly because of the time required for the production and characterization of unique antibody reagents. Combinatorial tests to optimize multiple factors in several steps of some IA formats are more complicated, and also result in a longer method refinement time. The nature of IAs versus that of LC-MS/MS methods are compared in Table 6.1. However, once established, IA methods are sensitive, consistent, and very cost-effective for the analysis of large volumes of samples. The more expensive FTMS or TOF-MS methods can be used to complement IA on selectivity confirmation. 

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