Numerical techniques for high-throughput reflectance interference biosensing

Abstract

We have developed a robust and rapid computational method for processing the raw spectral data collected from thin film optical interference biosensors. We have applied this method to Interference Reflectance Imaging Sensor (IRIS) measurements and observed a 10,000 fold improvement in processing time, unlocking a variety of clinical and scientific applications. Interference biosensors have advantages over similar technologies in certain applications, for example highly multiplexed measurements of molecular kinetics. However, processing raw IRIS data into useful measurements has been prohibitively time consuming for high-throughput studies. Here we describe the implementation of a lookup table (LUT) technique that provides accurate results in far less time than naive methods. We also discuss an additional benefit that the LUT method can be used with a wider range of interference layer thickness and experimental configurations that are incompatible with methods that require fitting the spectral response.

Keywords:

• Nanobiotechnology
• biosensors
• label free
• high-throughput
• interference reflectance spectroscopy
• thin film interference biosensing

Acknowledgements

We are grateful to David Freedman for helpful discussions and suggestions leading up to and during this work. This work was funded by the Boston University Cross-Disciplinary Training Program in Nanotechnology and Cancer, a program of the NCI Alliance for Nanotechnology in Cancer.

Notes

No potential conflict of interest was reported by the authors.