Detailed case studies about microfluidic new product development will be given on the applications for disease diagnosis, prognosis and precision therapy, as well as the soft microfluidic wearable sensors for healthcare. Examples of emerging commercial microfluidic products (diagnostics cartridge, wearable systems, DNA amplification platforms) will be analysed during the sessions. The course also highlights on the applications of microfluidics and LOC, introduce the microfluidic components for life sciences, chemistry, point-of-care diagnostics, Organ on a Chip, etc. The MasterClass will discuss the fundamentals of microfluidics and Lab-on-a-Chip technology, including the fluid mechanics theory, microfabrication for microfluidics, characterization techniques, and the micro flow control. No prior microfluidics knowledge is required. The MasterClass is conducted by international leaders in microfluidics research, innovation and commercialization. SIMTech’s Microfluidics and LOC MasterClass aims at providing participants from industry, government laboratories, and academia, with state-of-the-art overview and analysis of current and emerging microfluidic and lab-on-a-chip technologies. Microfluidics technology is characterized by the manipulation of small volumes of fluids (10-9 to 10-18 liters) in channels with dimensions of tens of micrometers. Microfluidics offers high return on investment and helps in cost control by minimizing errors. The market is also driven by demand for high-throughput screening methodologies, low-volume sample analysis, demand for in Vitro Diagnostics (IVD), and development of advanced lab-on-a-chip technologies. The application of microfluidics has enabled conventional laboratory procedures to be shifted to Lab-on-a-Chip (LOC). Microfluidics-based devices need a fraction of the sample for data interpretation. ![]() Rise in demand for Point-of-Care (POC) devices is expected to significantly drive the market. The global microfluidics market is projected to reach USD 58.8 billion by 2026 from USD 20.7 billion in 2021, growing at a CAGR of 23.2%. This interdisciplinary field has a wide range of application areas including environmental sensing, medical diagnostics, drug discovery, drug delivery, microscale chemical production, combinatorial synthesis and assays, artificial organs, and micropropulsion, microscale energy systems. ![]() Microfluidics consists of components such as valves, pumps and mixers for manipulating and transporting the fluid at micrometer to nanometer scale. Register of Interest for SIMTech Course.Multi-site Orders Allocation & Tracking.Life Cycle Assessment (LCA) and Life Cycle Costing (LCC).Sustainability & Emerging Applications Centre.Precision Engineering Centre of Innovation.Manufacturing Productivity Technology Centre.Sustainability & Lifecycle Engineering Division. ![]() FlexTech & MedTech Manufacturing Division.We identify challenges and propose research strategies in the context of the prediction and optimization of chemical reactions and materials syntheses and the development of the next generation of more robust and functional organs-on-chips and emerging organoids-on-chips. Of course, when choosing a fitting, it is necessary to ensure that the fitting has the same threading as the receiving port. We believe this approach will provide a robust framework for fundamental explorations in materials science and biomedicine, with implications in fields such as drug discovery, nanomaterials, in vitro organ modeling, and developmental biology. For example, consider two of the most widely used microfluidic connectors: a 10-32 fitting indicates a gauge 10 thread diameter with 32 threads per inch, and ’’-28 means a ’’ inch thread diameter with 28 threads per inch. Here, we elaborate on the potential of operating microfluidic platforms via closed-loop data-driven models by leveraging multimodal monitoring and data-acquisition instrumentation. This method streamlines rapid prototyping of microfluidic devices using plastics, paper, and adhesive substrates, and can be appropriately edited to incorporate different materials and technologies 47. The analysis of microfluidics-generated data via machine learning has been applied in a variety of contexts, achieving impressive results. A simple and enabling methodology for maker microfluidics is designcutassemble, shown schematically in Figure 2. Machine intelligence provides powerful predictive tools with the ability to learn from data. Microfluidics permit the automated manipulation of fluids at the microscale with high throughput and spatiotemporal precision, enabling the generation of large, multidimensional datasets.
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