Latest App Notes & Case Studies

There is a growing demand for more rapid methods with maintained robustness and chromatographic performance for the identification and quantitation of chemical residues in food analysis.

The increasing global demand for food has led to a growing use of pesticides, resulting in elevated risks of trace level chemical pollutants in food. Rapid and reliable methods are required to identify and quantify these pollutants with high sensitivity and over a wide dynamic range.

Download this app note to discover a method that can reduce the risk of cross-contamination, easily automate a process that was previously open to human error as well as increase assay confidence by ensuring sample integrity.

One of the major challenges faced by most toxicology laboratories is analyzing hundreds of drugs of abuse in biological samples. This is further complicated by the constantly increasing emergence in the volume of designer and illicit drugs.

RTP004 is a proprietary peptide used by Revance Therapeutics as a novel excipient in DaxibotulinumtoxinA for injection. Due to its high molecular weight, high isoelectric point and strong non-specific binding property, the sample preparation and LC-MS method development for this peptide is very challenging.

In early-stage pharmaceutical research, knowledge of a compound’s metabolism can assist in the identification of structural liabilities that can contribute to non-optimal pharmacokinetics, potentially toxic breakdown products or the potential for drug-drug interactions.

In quantifying therapeutic peptides and proteins in biological matrices, traditional ELISA-only based techniques can suffer from high variability, narrow dynamic range, problems with selectivity and typically cannot use internal standards.

Sample preparation and alternative chromatography techniques are often used to meet the sensitivity needs required in routine bioanalytical assays, but these methods can be time consuming.

In biotherapeutic development, decreased drug doses and limited sample volumes require higher quantification sensitivity, while the complexity of biological matrices calls for the need of assay selectivity improvement.

Demands for improved sensitivity in routine bioanalytical assays continue to increase as drug discovery and development programs focus on more efficacious, lower dosage compounds. Pharma development scientists supporting this work therefore require highly sensitive and selective bioanalytical methods for quantification.