Wearable Sensor Patch with Hydrogel Microneedles for In Situ Analysis of Interstitial Fluid.

Continuous real-time monitoring of biomarkers in interstitial fluid is essential for tracking metabolic changes and facilitating the early detection and management of chronic diseases such as diabetes. However, developing minimally invasive sensors for the in situ analysis of interstitial fluid and addressing signal delays remain a challenge. Here, we introduce a wearable sensor patch incorporating hydrogel microneedles for rapid, minimally invasive collection of interstitial fluid from the skin while simultaneously measuring biomarker levels in situ. The sensor patch is stretchable to accommodate the swelling of the hydrogel microneedles upon extracting interstitial fluid and adapts to skin deformation during measurements, ensuring consistent sensing performance in detecting model biomarker concentrations, such as glucose and lactate, in a mouse model. The sensor patch exhibits in vitro sensitivities of 0.024 ± 0.002 µA mM-1 for glucose and 0.0030 ± 0.0004 µA mM-1 for lactate, with corresponding linear ranges of 0.1-3 and 0.1-12 mM, respectively. For in vivo glucose sensing, the sensor patch demonstrates a sensitivity of 0.020 ± 0.001 µA mM-1 and a detection range of 1-8 mM. By integrating a predictive model, the sensor patch can analyze and compensate for signal delays, improving calibration reliability and providing guidance for potential optimization in sensing performance. The sensor patch is expected to serve as a minimally invasive platform for the in situ analysis of multiple biomarkers in interstitial fluid, offering a promising solution for continuous health monitoring and disease management.

Beyond heuristics: CFD-based novel multiparameter scale-up for geometrically disparate bioreactors demonstrated at industrial 2kL-10kL scales.

The timely delivery of the most up-to-date medicines and drug products is essential for patients throughout the world. Successful scaling of the bioreactors used within the biopharmaceutical industry plays a large part in the quality and time to market of these products. Scale and topology differences between vessels add a large degree of complication and uncertainty within the scaling process. Currently, this approach is primarily achieved through extensive experimentation and facile empirical correlations, which can be costly and time consuming while providing limited information. The work undertaken in the current study demonstrates a more robust and complete approach using computational fluid dynamics (CFD) to provide potent multiparameter scalability, which only requires geometric and material properties before a comprehensive and detailed solution can be generated. The CFD model output parameters that can be applied in the scale-up include mass transfer rates, mixing times, shear rates, gas hold-up values, and bubble residence times. The authors examined three bioreactors with variable geometries and were able to validate them based on single-phase and multiphase experiments. Furthermore, leveraging the resulting CFD output information enabled the authors to successfully scale-up from a known 2kL to a novel and disparate 5kL single-use bioreactor in the first attempted cell culture. This multiparameter scaling approach promises to ultimately lead to a reduction in the time to market providing patients with earlier access to the most groundbreaking medicines.