Mark T. Marino

Quantification of human serum insulin concentrations in clinical pharmacokinetic or bioequivalence studies: what defines the “best method”?

Abstract Background: Historically, quantitative clinical diagnostic assays (QCDAs) have not been accepted for use in pharmacokinetic or bioequivalence studies because they do not fully comply with the US Food and Drug Administration (FDA) Guidance for Industry: Bioanalytical Method Validation (e.g., full calibration curve not generated with each analytical run). Samples from a bioequivalence study were analysed for insulin and C-peptide concentrations with QCDAs and guidance-conforming radioimmunoassays (RIAs) and the results compared across and within assays. Methods: Serum samples (n=1913) from study MKC-TI-142 were analysed first using the Roche E170 electrochemiluminescence immunoassay (ECLIA) for insulin concentration and the Immulite 2000 chemiluminescence immunoassay (CLIA) for C-peptide, and then using the corresponding Millipore RIAs. Results: The insulin assays were highly correlated: r2=0.92 excluding samples requiring dilution and R2=0.88 including all samples. There was increasing negative bias of the ECLIA compared with the RIA with increasing insulin, especially with samples that required dilution for the RIA. The ECLIA had significantly fewer below-quantifiable-limit samples, a larger dynamic analysis range without dilution, and tighter agreement within incurred sample reanalysis (ISR) as compared with the RIA. The C-peptide assays showed good agreement but the CLIA method produced ISR results that were in closer agreement with the original values. Conclusions: The science indicates that the QCDAs are appropriate for the quantification of serum insulin (ECLIA) and C-peptide (CLIA) concentrations in human pharmacokinetic and bioequivalence studies even though the calibration curve is not generated in each analytical run.

A new C-peptide correction model used to assess bioavailability of regular human insulin

The clinical assessment of new formulations of human insulin is problematic due to the inability to distinguish between endogenous insulin and exogenously administered insulin. The usual methods to surmount the problem of distinguishing between endogenous and exogenous human insulin include evaluation in subjects with no or little endogenous insulin, hyper‐insulinemic clamp studies or the administration of somatostatin to suppress endogenous insulin secretion. All of these methods have significant drawbacks. This paper describes a method for C‐Peptide correction based upon a mixed effects linear regression of multiple time point sampling of C‐Peptide and insulin. This model was able to describe each individuals insulin to C‐Peptide relationship using the data from four different phase I clinical trials involving both subjects with and without type 2 diabetes in which insulin and C‐Peptide were measured. These studies used hyper‐insulinemic euglycemic clamps or meal challenges and subjects received insulin or Glucagon‐like peptide 1 (GLP‐1). It was possible to determine the exogenously administered insulin concentration from the measured total insulin concentration. A simple statistical technique can be used to determine each individuals insulin to C‐Peptide relationship to estimate exogenous and endogenous insulin following the administration of regular human insulin. This technique will simplify the assessment of new formulations of human insulin. Copyright