Progress on the Electrochemical Sensing of Illicit Drugs.

Illicit drugs are harmful substances, threatening both health and safety of societies in all corners of the world. Several policies have been developed over time to deal with this illicit drug problem, including supply reduction and harm reduction policies. Both policies require on-site detection tools to succeed, i.e. sensors that can identify illicit drugs in samples at the point-of-care. Electrochemical sensors are highly suited for this task, due to their short analysis times, low cost, high accuracy, portability and orthogonality with current technologies. In this chapter, we evaluate the latest trend in electrochemical sensing of illicit drugs, with a focus on detection of illicit drugs in seizures and body fluids. Furthermore, we will also provide an outlook on the potential of electrochemistry in wearable sensors for this purpose.

Dual Microfluidic Sensor System for Enriched Electrochemical Profiling and Identification of Illicit Drugs On-Site.

Electrochemical sensors have emerged as a new analytical tool for illicit drug detection to facilitate ultrafast and accurate identification of suspicious compounds on-site. Drugs of abuse can be identified using their unique voltammetric fingerprint at a given pH. Today, the right buffer solution is manually selected based on drug appearance, and in some cases, a consecutive analysis in two different pH solutions is required. In this work, we present a disposable microfluidic multichannel sensor system that automatically records fingerprints in two pH solutions (e.g., pH 5 and pH 12). This system has two advantages. It will overcome the manual selection of a buffer solution at the right pH, decrease analysis time, and minimize the risk of human errors. Second, the combination of two fingerprints, the superfingerprint, contains more detailed information about the samples, which enhances the selectivity of the analytical technique. First, real-time pH measurements proved that the sample can be brought to the desired pH within a minute. Subsequently, an electrochemical study on the microfluidic platform with 1 mM illicit drug standards of MDMA, cocaine, heroin, and methamphetamine showed that the characteristic voltammetric fingerprints and peak potentials are reproducible, also in the presence of common cutting agents. Finally, the microfluidic concept was validated with real confiscated samples, showing promising results for the user-friendly identification of drugs of abuse. In short, this paper presents a successful proof-of-concept study of a multichannel microfluidic sensor system to enrich the fingerprints of illicit drugs at pH 5 and pH 12, thus providing a low-cost, portable, and rapid identification system of illicit drugs with minimal user intervention.

Evaluation of an electrochemical sensor and comparison with spectroscopic approaches as used today in practice for harm reduction in a festival setting-A case study: Analysis of 3,4-methylenedioxymethamphetamine samples.

More and more countries and organisations emphasise the value of harm reduction measures in the context of illicit drug use and abuse. One of these measures is drug checking, a preventive action that can represent a quick win by tailored consultation on the risks of substance use upon analytical screening of a submitted sample. Unlike drop-in centres that operate within a fixed setting, enabling drug checking in a harm reduction context at events requires portable, easy to use analytical approaches, operated by personnel with limited knowledge of analytical chemistry. In this case study, four different approaches were compared for the characterisation of 3,4-methylenedioxymethamphetamine samples and this in the way the approaches would be applied today in an event context. The four approaches are mid-infrared (MIR), near-infrared, and Raman spectroscopy, which are today used in drug checking context in Belgium, as well as an electrochemical sensor approach initially developed in the context of law enforcement at ports. The MIR and the electrochemical approach came out best, with the latter allowing for a direct straightforward analysis of the percentage 3,4-methylenedioxymethamphetamine (as base equivalent) in the samples. However, MIR has the advantage that, in a broader drug checking context, it allows to screen for several molecules and so is able to identify unexpected active components or at least the group to which such components belong. The latter is also an important advantage in the context of the growing emergence of new psychotropic substances.

Real-time electrochemical screening of cocaine in lab and field settings with automatic result generation.

This work presents the results of a novel application for the fast on-site screening of cocaine and its main cutting agents in suspicious and confiscated samples. The methodology behind the novel application consists of portable electrochemical detection coupled with a peak recognition algorithm for automated result output generation, validated both in laboratory and field settings. Currently used field tests, predominantly colorimetric tests, are lacking accuracy, often giving false positive or negative results. This presses the need for alternative approaches to field testing. By combining portable electrochemical approaches with peak recognition algorithms, an accuracy of 98.4% concerning the detection of cocaine was achieved on a set of 374 powder samples. In addition, the approach was tested on multiple "smuggled," colored cocaine powders and cocaine mixtures in solid and liquid states, typically in matrices such as charcoal, syrup, and clothing. Despite these attempts to hide cocaine, our approach succeeded in detecting cocaine during on-site screening scenarios. This feature presents an advantage over colorimetric and optical detection techniques, which can fail with colored sample matrices. This enhanced accuracy on smuggled samples will lead to increased efficiency in confiscation procedures in the field, thus significantly reducing societal economic and safety concerns and highlighting the potential for electrochemical approaches in on-the-spot identification of drugs of abuse.

Exploring machine learning methods for absolute configuration determination with vibrational circular dichroism.

The added value of supervised Machine Learning (ML) methods to determine the Absolute Configuration (AC) of compounds from their Vibrational Circular Dichroism (VCD) spectra was explored. Among all ML methods considered, Random Forest (RF) and Feedforward Neural Network (FNN) yield the best performance for identification of the AC. At its best, FNN allows near-perfect AC determination, with accuracy of prediction up to 0.995, while RF combines good predictive accuracy (up to 0.940) with the ability to identify the spectral areas important for the identification of the AC. No loss in performance of either model is observed as long as the spectral sampling interval used does not exceed the spectral bandwidth. Increasing the sampling interval proves to be the best method to lower the dimensionality of the input data, thereby decreasing the computational cost associated with the training of the models.

Unlocking the full potential of voltammetric data analysis: A novel peak recognition approach for (bio)analytical applications.

Bridging the gap between complex signal data output and clear interpretation by non-expert end-users is a major challenge many scientists face when converting their scientific technology into a real-life application. Currently, pattern recognition algorithms are the most frequently encountered signal data interpretation algorithms to close this gap, not in the least because of their straight-forward implementation via convenient software packages. Paradoxically, just because their implementation is so straight-forward, it becomes cumbersome to integrate the expert's domain-specific knowledge. In this work, a novel signal data interpretation approach is presented that uses this domain-specific knowledge as its fundament, thereby fully exploiting the unique expertise of the scientist. The new approach applies data preprocessing in an innovative way that transcends its usual purpose and is easy to translate into a software application. Multiple case studies illustrate the straight-forward application of the novel approach. Ultimately, the approach is highly suited for integration in various (bio)analytical applications that require interpretation of signal data.

Wearable Electrochemical Sensors for the Monitoring and Screening of Drugs.

Wearable electrochemical sensors capable of noninvasive monitoring of chemical markers represent a rapidly emerging digital-health technology. Recent advances toward wearable continuous glucose monitoring (CGM) systems have ignited tremendous interest in expanding such sensor technology to other important fields. This article reviews for the first time wearable electrochemical sensors for monitoring therapeutic drugs and drugs of abuse. This rapidly emerging class of drug-sensing wearable devices addresses the growing demand for personalized medicine, toward improved therapeutic outcomes while minimizing the side effects of drugs and the related medical expenses. Continuous, noninvasive monitoring of therapeutic drugs within bodily fluids empowers clinicians and patients to correlate the pharmacokinetic properties with optimal outcomes by realizing patient-specific dose regulation and tracking dynamic changes in pharmacokinetics behavior while assuring the medication adherence of patients. Furthermore, wearable electrochemical drug monitoring devices can also serve as powerful screening tools in the hands of law enforcement agents to combat drug trafficking and support on-site forensic investigations. The review covers various wearable form factors developed for noninvasive monitoring of therapeutic drugs in different body fluids and toward on-site screening of drugs of abuse. The future prospects of such wearable drug monitoring devices are presented with the ultimate goals of introducing accurate real-time drug monitoring protocols and autonomous closed-loop platforms toward precise dose regulation and optimal therapeutic outcomes. Finally, current unmet challenges and existing gaps are discussed for motivating future technological innovations regarding personalized therapy. The current pace of developments and the tremendous market opportunities for such wearable drug monitoring platforms are expected to drive intense future research and commercialization efforts.