title: Assays for recombinant proteins: a problem in non-linear calibration.
abstract: Quantification of protein levels in biological matrices such as serum or plasma frequently relies on the techniques of immunoassay or bioassay. The relevant statistical problem is that of non-linear calibration, where one estimates analyte concentration in an unknown sample from a calibration curve fit to known standard concentrations. This paper discusses a general framework for calibration curve fit to known standard concentrations. This paper discusses a general framework for calibration inference, that of the non-linear mixed effects model. Within this framework, we consider two issues in depth: accurate characterization of intra-assay variation, and the use of empirical Bayes methods in calibration. We show that proper characterization of intra-assay variability requires pooling of information across several assay runs. Simulation work indicates that use of empirical Bayes methods may afford considerable gain in efficiency; one must weigh this gain against practical considerations in the implementation of Bayesian techniques. We illustrate the methods discussed using a cell-based bioassay for the recombinant hormone relaxin.
authors.affiliation: Biostatistics Department, Genetech, Inc., South San Francisco, CA 94080.
authors.forename: D M
authors.initials: DM
authors.lastname: Giltinan
authors.forename: M
authors.initials: M
authors.lastname: Davidian
mesh_terms: D001499:Bayes Theorem; D001681:Biological Assay / Q000379:methods / Q000592:standards* / Q000706:statistics & numerical data; D002138:Calibration; D006801:Humans; D016013:Likelihood Functions; D008954:Models, Biological; D017711:Nonlinear Dynamics; D011994:Recombinant Proteins / Q000097:blood; D012044:Regression Analysis; D015203:Reproducibility of Results
chemical_list: D011994:Recombinant Proteins