Adaptive Bayesian approach to clinical trial renal impairment biomarker signal from urea and creatinine.

A major concern with the identification of renal toxicity using the traditional biomarkers, urea and creatinine, is that toxicity signal definitions are not sensitive to medically important changes in these biomarkers. Traditional renal signal definitions for urea and creatinine have not adequately identified drugs that have generated important medical issues later in development. Here, two clinical trial databases with a posteriori known drug induced renal impairment were analyzed for the presence of a renal impairment biomarker signal from urea (590 patients; age 26-92, median 65) and creatinine (532 patients; age 26-97, median 65).

Adaptive Bayesian analysis of serum creatinine as a marker for drug-induced renal impairment in an early-phase clinical trial.

Background: A concern with using creatinine for the identification of drug-induced renal impairment is that small changes in serum creatinine (SCr) that frequently are perceived as measurement bias or imprecision translate into important changes in the glomerular filtration rate. Important drug-generated changes in creatinine are difficult to detect because they are frequently observed within the reference interval. The design of a crossover drug protocol is an opportunity to use study participants as their own control to identify these small but important changes.

Patient-specific measures of a biomarker for the generation of individual reference intervals: hemoglobin as example.

Although hemoglobin concentration measurement is among the most commonly performed blood tests, the description of global population parameters, heterogeneous factors, and within-subject variations in patients with disease remains incomplete. As absolute action values are being published in the medical literature and by government healthcare agencies, these measures are important to define patient-specific ranges of biomarkers. Here, a global clinical trial data set composed of 1,537,932 hemoglobin values from 416,374 patients and 372 clinical indications was generated over 2 years by automated analyzers in a global network of 5 laboratories.

Assay validation for KIM-1: human urinary renal dysfunction biomarker.

Urinary kidney injury molecule (KIM-1) is a sensitive quantitative biomarker for early detection of kidney tubular injury. The objective of the present work was to analytically validate this urinary renal injury biomarker. Duo-set reagents from R&D were used to develop the ELISA and validate the assay's linearity, intra-run precision, inter-run precision, lower limit of quantification, recovery, dilutional verification, reference range, stability, and length of run.