Biosensing platforms based on extracellular vesicles are currently receiving a lot of attention. The reason is that extracellular vesicles, which are endocytic lipid-membrane bound bodies, have the potential to be used as biomarkers in cancer and neurodegenerative disease and can be easily accessed via non-invasive liquid biopsies.
In my research group we focus on fundamental questions related to how materials form and interact on the nanoscale with the overall ambition to develop novel methodologies supporting healthcare and the environment. Typically, we explore design strategies based on molecular self-assembly of polymers, nanoparticles, and biomolecules. Biosensing platforms, which could be used for sensitive detection of analytes enabling disease diagnosis, are an important area for us. In this context we explore novel biosensor architectures as well as different strategies to increase biosensor sensitivity and specificity.
The QCM-D analysis enabled us to monitor the surface immobilization of the nanoparticles, as well as the subsequent uptake and release of binding partners.[1] Using the QCM-D data, we could also model the binding kinetics of the respective nanoparticle - analyte couples, and determine important binding parameters, such as the association and dissociation rate constants (kon and koff) and apparent binding constant Ka.
Recently, we developed an approach for stepwise surface functionalization of biosensing surfaces with a particular focus on extracellular vesicles. The build-up of the surface architecture and performance was characterized by QCM-D and EQCM-D analysis.[2,3] As an example, with the ambition to enhance the sensitivity of the platform, we investigated a 2D and 3D nanostructuring of the QCM-D electrode.[4,5]
Watch the webinar to learn more about our recent efforts on implementing QCM-D for reliable biosensing.
Discover how QSense QCM-D technology reveals real-time cleaning insights. Join our webinar to enhance your cleaning strategies and efficiency.
Here we explain how Quartz Crystal Microbalance with Dissipation monitoring, QCM-D, works.
QSense QCM-D technology enables analysis of cleaning process dynamics, surface etching, and surface residual
Read about how and the QCM fundamental frequency matters in measurements
QCM-D was used to compare the potency and mechanisms of action of two different detergents in disrupting lipid membranes
Explore a case example of surfactant adsorption with QSense Omni, showcasing its performance and enhanced data quality.
Read about why it is important for the mass distribution on the QCM sensor to be even, and what the consequences are if it is not.
Learn more about the Sauerbrey equation and when it should be used.
Read about how QSense QCM-D was used to study the adsorption kinetics of different cell types
Dr. Stefan Guldin is a full professor in Chemical Engineering, head of the Adaptive and Responsive Nanomaterials group, and deputy head of department (Enterprise) at University College London. His research interests include the study of material formation on the nanoscale by molecular self-assembly, creation of adaptive and responsive materials architectures, and translation into chemo- & biosensing applications.