Project - SPYKE
In recent years, the usage of Gamma-hydroxybutyrate, commonly known as GHB, for drugging in nightlife contexts has increased noticeably in Western Europe, namely in the United Kingdom, Belgium, the Netherlands, and France, where GHB is the most commonly used ‘rape drug’. It has a fast onset of action, and in excessive doses or when mixed with alcohol, it can cause permanent damage. This drug is mainly used to facilitate sexual assault, due to the fact that the victim rapidly loses conscience, and has no recollection of the night the following day.
Until now, GHB detection technologies have been slow, inconvenient, and expensive. In addition, due to the rapid breakdown of GHB molecules in the body, it is unlikely to identify this drug in the body after six hours from consumption. As a result, hospitals can’t confirm most cases of drugging, leading to a lack of data, and victims are left with no evidence, which prevents them from getting justice.
This year our team SPYKE will strive to contribute to a solution by developing a real-time and reliable detection method for GHB. Our approach is based on biological components as a biosensor inserted in an electrical circuit. Our human practice will contact and discuss with the relevant stakeholders, and implement their feedback into our design. We aim to decrease the number of drug-facilitated sexual assault incidents and gather data on a phenomenon that lacks it.
Although a lot of experiments are being done in the lab, there is still a lot of science we can do or need to do outside of the lab. This year the iGEM TU Delft dry lab team will use computational and mathematical methods to simulate and understand natural phenomena studied in the wet lab.
The dry lab team’s first goal is to model the binding and release process to determine the optimal concentration of our protein. The data obtained from this computational model will be helpful for the experimental design of the wetlab and to check the results obtained.
The second objective of the dry lab is to model the electric circuit that constitutes our biosensor. The goal is to understand how the various electrical components function together and how we can obtain the best readout from it when integrated with the biological components as well.