Background: Identification of laboratory parameter clinical safety signals depends on the terminology and scoring criteria. Grade 1 scoring criteria in the Common Terminology Criteria for Adverse Events (CTCAE) is typically based on the healthy volunteer reference range (HVRR). The objectives of this study were to determine 1) what laboratory parameters in individuals with diabetes are potentially different from the HVRR and 2) what fold change from baseline should be expected in this population.
View Article and Find Full Text PDF: Drug-induced myocardial dysfunction is an important safety concern during drug development. Oncology compounds can cause myocardial dysfunction, leading to decreased left ventricular ejection fraction and heart failure via several mechanisms. Cardiovascular imaging has a major role in the early detection and monitoring of cardiotoxicity.
View Article and Find Full Text PDFThe diagnosis and management of drug-induced liver injury (DILI) remains a challenge in clinical trials in drug development. The qualification of emerging biomarkers capable of predicting DILI soon after the initiation of treatment, differentiating DILI from underlying liver disease, identifying the causal entity, and assigning appropriate treatment options after DILI is diagnosed are needed. Qualification efforts have been hindered by lack of properly stored and consented biospecimens that are linked to clinical data relevant to a specific context of use.
View Article and Find Full Text PDFBackground: Liver biomarkers alanine aminotransferase (ALT) and bilirubin in patients with hepatitis are above the healthy volunteer reference range (HVRR) at baseline (prior to receiving the clinical trial medication). Discussions continue as how to best distinguish drug-induced liver injury in patients with abnormal baseline values participating in clinical trials. This study investigated if other baseline routine clinical safety biomarkers (lab parameters) are different from the HVRR.
View Article and Find Full Text PDFInt J Data Min Bioinform
September 2015
Systems toxicology, a branch of toxicology that studies drug effects at the level of biological systems, offers exciting opportunities to discover toxicity-related sub-networks using high-throughput technologies. This paper takes a computational approach to systems toxicology and investigates the use of automated signalling path detection for discovery of potential biomarkers of drug-induced non-immune neutropenia. The algorithm utilises a gene expression change measure to mine a large protein interaction network and identify chemical-toxicity signalling paths.
View Article and Find Full Text PDF