Biomarkers – Multimedia

Although there are initiatives to de-risk the drug development process, continually applying the same tools and approaches is unlikely to lead to innovative, first- or best-in-class targets and transformative progress.

According to the World Health Organization (WHO), cancer is a leading cause of death worldwide. Furthermore, recent estimates predict that as many as one in two people could develop a form of cancer in their lifetime.

Bile acids are well known for their roles in cholesterol homeostasis, lipid absorption and as metabolic signaling molecules. They are implicated in a variety of disease states and therefore serve as an exciting focus on research in novel biomarker discovery.

With unparalleled speed, sensitivity and spatial resolution, Shimadzu’s iMScope QT imaging mass microscope clears the way to next-generation mass spectrometry imaging in areas such as biomarker tracking, pharmacokinetics, and ADME studies.

Get to market faster with LuminexPLORE Lab custom assay development and multiplex testing services. Our team of scientists combine technical precision with industry-leading xMAP® and xTAG® technologies to produce highly specific proteomic and genomic multiplex assays.

Download this listicle to discover recent examples of how single-cell analysis methods are driving forward research into cancer, aging, and drug discovery and development.

Identifying novel biomarkers with bottom-up proteomics remains a substantial challenge due to the wide concentration ranges and potentially low abundance of important analytes.

This poster discusses ChipCytometry, a modified approach to slide-based cytometry, a novel, highly multiplexed technology that preserves both plex and spatial context to deeply profile immune cell diversity at single-cell resolution

The metabolites produced by a cell, tissue or organism represent the endpoint of the omics process. Download this infographic to learn more about metabolomics and how it is studied.

Formalin-fixed, paraffin-embedded (FFPE) tissue is a valuable resource in the retrospective proteomic analysis of clinical and non-clinical samples.