Device and method for detecting and identifying molecularly imprinted polymers in a liquid dispersion sample

A method for detecting a molecularly imprinted polymer (MIP) from a backscattered or scattered forward light fingerprint, including detecting whether it is bound or not bound to a target analyte, in a liquid dispersion sample, said method using an electronic data processor for classifying the sample as having, or not having, said MIP present, the method comprising the use of the electronic data processor for pre-training a machine learning classifier with a plurality of MIP specimens comprising specimens bound and specimens not bound to the target analyte, comprising the steps of:

• emitting a laser modulated by a modulation frequency onto each specimen;
• capturing a temporal signal from laser light backscattered or scattered forward by each specimen for a plurality of temporal periods of a predetermined duration for each specimen;
• calculating specimen coefficients from the captured signal for each of the temporal periods;
• using the calculated coefficients to pre-train the machine learning classifier;
• wherein the method further comprises the steps of:
• using a laser emitter having a focusing optical system coupled to the emitter to emit a laser modulated by a modulation frequency onto the sample;
• using a light receiver to capture a signal from laser light backscattered or scattered forward by the sample for a plurality of temporal periods of a predetermined duration;
• calculating sample coefficients from the captured signal for each of the temporal periods;
• using the pre-trained machine learning classifier to classify the calculated sample coefficients as having, or not having, the MIP present and whether it is bound or not bound to a target analyte.