What are the best methods to reduce matrix effects in bioanalytical sensors?
Bioanalytical sensors are devices that detect and measure biological molecules, such as proteins, hormones, or drugs, in complex biological samples, such as blood, urine, or saliva. They have many applications in clinical diagnostics, drug discovery, environmental monitoring, and biotechnology. However, bioanalytical sensors often face a challenge called matrix effects, which are interferences caused by the components of the biological sample that affect the sensor performance and accuracy. Matrix effects can reduce the sensitivity, specificity, and reproducibility of the sensor signal, leading to false positives or negatives, or inaccurate quantification. Therefore, it is important to find effective methods to reduce matrix effects in bioanalytical sensors. In this article, you will learn about some of the best methods to reduce matrix effects in bioanalytical sensors, such as sample preparation, sensor design, and signal processing.