Latest App Notes & Case Studies

Glucuronidation is an essential metabolic pathway for drug clearance and its characterization is crucial for optimizing the efficiency and safety of drug candidates.

Early ADME studies are used to determine if a drug candidate is prone to metabolic breakdown or oxidation/conjugation. Glucuronide conjugation is difficult to characterize using MS/MS alone, therefore fragmentation is also required to obtain structural information.

Developed for performance in human serum and plasma, the SomaScan Assay v4.1 can measure approximately 7,000 unique human protein analytes in small volumes of biological samples.

Download this app note to learn how you can select 20 individual CTCs in 10 minutes, this approach can be used for DNA, RNA or proteome analysis as well as how these target cells are selected and isolated in high purity from heterogenous backgrounds.

Metabolism has emerged as a key driver of T-cell antitumor function. This means that modulating metabolic programs of T cells can be used as a strategy to improve the antitumor efficacy of adoptive T-cell therapies.

The scale of research into potential gene therapies often means that work is distributed across multiple locations. Investigators must have confidence that the results obtained at one site are consistent with results obtained at other sites participating in the study.

This app note presents a robust workflow that combines automated sample preparation, hydrophilic interaction chromatography and triple quadrupole mass spectrometry that can be applied to plasma and mammalian cell samples.

Serological pipettes are commonly used in cell culture applications when pipetting volumes greater than 1,000 µL. However, their plastic (disposable) nature, coupled with the inability to pre-set the volume and propensity to cause shoulder strain, are just some of the limitations faced by researchers in the lab.

The miniaturization of FTIR into a handheld, portable solutions, now offers a more rapid analysis of photovoltaic cells than ever before

Single-cell RNA sequencing produces a substantial amount of complex data that can be a burden if you don’t have time to become an expert in bioinformatics.