The aim of our kit was to successfully quantify the different concentrations of the biomarker within the detection ranges described in literature.

According to this, decreased Salivary Lactoferrin (around 4.78 ug/ml) is indicative of a high risk of developing Alzheimer’s.

The successful quantification of the biomarkers here would only meet our goal if the method of quantification is cheap, can be miniaturized, and easily used by any one. All these things are true for Electrochemical Analysis. In fact our proposed biosensor design also can easily be adapted to be used for other diseases by identifying different biomarkers and finding the corresponding aptamers for them.

Our Wet Lab results successfully established a strong linear correlation (R-square value= 0.988) between the concentration and current within the required range for diagnosis and risk calculation.

This serves as proof of concept for the successful quantification of biomarker and modeling the behavior of our biosensor within this range.

A proof of concept however, is only a practical validation of our theoretical proposal. To truly develop our kit though, there are several more steps to go through. We must first optimize our biosensor further by experimenting with more spacer molecule options and ratios. We are also considering the use of nanomaterials to increase sensitivity. Along with this, we must achieve reproducibly stable Aptasensor Fabrications and a reliable protocol for this. Apart from optimisation, our proposed kit will also detect Amyloid Beta 42. The next step would be repeating these electrode immobilization and optimization steps with Amyloid Beta 42 specific aptamers.

Our Dry Lab work also establishes the possibility of comprehensively studying the behavior of aptamers and proteins through Simulations and this creates the scope of introducing carefully analyzed mutations, and perhaps also modeling Aptamer Modifications to increase specificity, sensitivity and binding affinity. These new aptamers would then take the place of our current protocols, and could by that point be easily optimized to create an efficient biosensor and diagnostic tool for the early detection of Alzheimer’s.