Abstract
Radioligand binding assay (RLA) and radioimmunoassay (RIA) development involves consideration of a large number variables which influence signal readout or system errors, with contrary effects on assay performance. We have developed an optimization strategy according to statistical criteria which incorporates these variables and which specifies a minimum data set for a systematic analysis. Increased background and error fractions are seen to reduce assay power, whereas increased specific activity, affinity, and counting time increase power. The optimal concentration of radiolabeled developer in the test is dependent upon a balance of these factors, but in general yields a broad optimum. These analyses suggest several strategies available to the investigator for improving assay performance. The optimization method is adapted to standard microcomputer spreadsheet formats which allow ready application of these procedures in any research laboratory.
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