Latest App Notes & Case Studies

Data-independent acquisition (DIA) has been shown to increase the quantitative reproducibility and accuracy of MS-based phosphoproteomics. This app note explores the impact of dia-PASEF on the speed and sensitivity of phosphoproteomics.

RNA-based therapies can modulate cells in a controlled and targeted manner, effectively acting as gene therapies. But, as with any therapeutic, RNA therapeutics must undergo strict quality control (QC) to ensure the product is exactly as specified, with no errors or alternate products.

The multi-attribute method (MAM) is a powerful LC-MS method that overcomes this challenge by simultaneously monitoring and quantifying multiple PQAs in a single injection.

Antibody drug conjugates (ADCs) are biotherapeutics, composed of small molecule drugs conjugated to an antibody scaffold, that have very complex molecular structures.

Elemental impurities contained in pharmaceutical products are getting more and more attention due to their harmful potential on patient health and impact on drug shelf life and efficacy. ICP-MS is an elemental analysis technology capable of detecting most of these threats at as little as a nanogram level per liter.

Traditional methods are often low throughput, time-consuming and lack linearity. However, advanced flow cytometry has emerged as a more efficient alternative for biologics development.

Routine, robust methods for long-read sequencing have the potential to allow researchers to analyze long stretches of DNA without the requirement of preamplification and can also enable analysis of complex regions that are otherwise difficult to map.

As oligonucleotides (oligos) are synthesized, small amounts of impurities can be introduced at each step, and different synthesis methods and purification efficiencies can impact the quality of the sample.

Inherited metabolic disorders (IMDs) are a vast and complex group of rare genetic diseases presenting throughout a patient’s life span.

Extracting biological insights from spatial data is vital to advancing science, however, the analysis of spatial multiomics data is only possible with a robust and scalable informatics solution.