Thirty years of progresses in hair testing science, where do we go?

Abstract

Objective

Describe the evolution and challenges faced within hair testing and discuss progress to a foreseeable future.

Introduction

Hair testing science has progressed rapidly during the past 30 years; mainly due to advances in instrumentation, expanded substance detection and applications. At the same time, it has faced many challenges, both in acceptance (in the early times) and interpretation issues. As society and technology are progressing, the future of this science is heading in several promising directions including the artificial intelligence and machine learning, which could automate much of the analysis and interpretation of the results.

Results and discussion

The evolution of hair analysis is closely related to advances in analytical instrumentation. Thirty years ago, the vast majority of labs performing hair analysis applied GC-MS, while more sensitive techniques were used in a minority. Over the years, the scenario has been changing and currently most laboratories use LC-MS/MS; even some labs use imaging mass spectrometry (MALDI-TOF) on a single hair. This is demonstrated by the Proficiency Test organized by the Society of Hair Testing. In 2001, 93% of the participants used GC-MS and 7% LC-MS; just the opposite happened in 2023, when 3% used GC-MS and 97% LC-MS/MS. The development of advanced analytical techniques allowed the detection of more drugs and their metabolites. Initially hair analysis focused on a limited number of substances (e.g. opiates, cocaine and later with cannabis). With the introduction of high-resolution techniques in the routine, hair testing now includes a wider array of drugs, including alcohol markers (ethyl-glucuronide), or new psychoactive substances (NPS). In addition, advances in understanding drug metabolism have allowed for the detection of specific metabolites, providing insights into usage patterns and the timing of drug use. The number of applications of these analyses has been growing over the years and it includes different fields: forensic investigations, workplace drug testing, driver's license regranting, child custody, clinical settings, doping control, etc. In the last years, the application of more sensitive and accurate methodologies allowed the detection of traces of a drug even after a single use. Thus, the spectrum of applications was expanded to cases of drug facilitated crimes. The major challenge of hair testing has been and (even in some circumstances) continues to be the external contamination and the risk of reporting false positive results. A lot of research has been done to solve this issue. An initial approach was the introduction of cut-off values, then extensive and/or sequential washes, the analysis of endogenous and minor metabolites. Lately metabolic concentration ratios are being applied. Some key trends and potential directions for the future of hair testing could be related to: (a) technological advancements, including the possibility of the integration of automation in laboratory processes, which could streamline hair analysis, making it faster and more cost-effective; (b) expanded substance detection and metabolite profiling: (c) expanded applications; (d) integration of artificial intelligence and learning machines, which can significantly enhance hair testing in various ways (i.e. external contamination issue); (e) regulatory and standardization efforts, standardized protocols and guidelines will ensure consistency and reliability across laboratories.

Conclusion

In summary, the last 30 years have seen remarkable progress in hair testing, driven by instrumental developments, expanded applications, and increased acceptance. As the field continues to evolve, the future of hair analysis looks promising, with major advancements on the horizon in terms of accuracy, applications, and technology integration.