Latest Posters

Many promising drugs which show efficacy in animal models have failed in the clinic due to interspecies variance in nociception mechanisms. Hence, consistent, scalable human in vitro models are required to accelerate potential therapeutics to the clinic.

While animal models and primary cells remain valuable resources, neuronal drug development faces many challenges. Not least, the variability and inaccuracy of traditional model systems can result in the failure to translate data into successful clinical trials.

Microglia play key roles in neurogenesis, synaptic remodeling, and are the first responders to infection in the brain. Hence, disease-relevant cell models are key to the success of neuroimmune and neurodegeneration research.

Formaldehyde fixed & paraffin-embedded (FFPE) tissue blocks are one of the most commonly used and archived sample types. However, some preservation approaches can result in the degradation of RNA and hinder transcriptome profiling .

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

Whether you are working in cell line development, 3D biology, drug screening —or a combination of the three — technologies that maximize throughput and reproducibility can free up your time and give you greater insights.

Patient-derived induced pluripotent stem cells (iPSCs) enable generation of in vitro models that can recapitulate human disease phenotypes. However, conventional human iPSC differentiation protocols are often lengthy, inconsistent and difficult to scale.

To overcome these challenges, researchers have developed a proprietary gene-expression targeting strategy that can rapidly reprogram hiPSCs into pure somatic cell types in a scalable manner. This approach was used to develop a Huntington’s disease (HD) model carrying a 50CAG expansion in the huntingtin (HTT) gene.

Researchers require spatial information and high-plex gene expression data to understand how cells interact with tumors. However, molecular subtyping within a tumor type requires additional stratification at the tissue level to facilitate meaningful subsequent gene expression analysis.

Traditionally, there has been a compromise between performance and sustainability.