Application of Chemometrics in Biosensing: A Brief Review

Ekaterina Martynko, Dmitry Kirsanov

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations


The field of biosensing is rapidly developing, and the number of novel sensor architectures and different sensing elements is growing fast. One of the most important features of all biosensors is their very high selectivity stemming from the use of bioreceptor recognition elements. The typical calibration of a biosensor requires simple univariate regression to relate a response value with an analyte concentration. Nevertheless, dealing with complex real-world sample matrices may sometimes lead to undesired interference effects from various components. This is where chemometric tools can do a good job in extracting relevant information, improving selectivity, circumventing a non-linearity in a response. This brief review aims to discuss the motivation for the application of chemometric tools in biosensing and provide some examples of such applications from the recent literature.

Original languageEnglish
Article number100
Issue number8
StatePublished - Aug 2020

Scopus subject areas

  • Clinical Biochemistry


  • ANN
  • Biosensor
  • Chemometrics
  • Classification
  • Multivariate regression
  • PCA
  • PLS


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