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In the past few years, there has been significant interest within the forensic community regarding the deployment of portable solutions that provide real‐time results. This article introduces an innovative technology or technology architecture that enables the integration of a handheld device, specifically, Viavi MicroNIR, with a cloud‐based system. This cloud system encompasses a server responsible for data processing and a mobile application acting as a user interface. To demonstrate the transformative impact of this technology on field operators, the analysis of cannabis specimens has been utilized. System's capacity to distinguish between CBD‐type and THC‐type cannabis has been particularly highlighted, along with the remarkable congruence observed between the near‐infrared (NIR) spectra and the reference analytical method involving ultra‐high‐performance liquid chromatography (UHPLC) The article will present the advantages of this application primarily focusing on its potential to alleviate the burden on laboratories by expediting routine illicit drug analysis. Viavi MicroNIR technology provides laboratory personnel with additional time to handle more complex cases, thereby enhancing overall efficiency. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.forsciint.2009.06.006 Byline: Annabel Bolck (a), Celine Weyermann (b), Laurence Dujourdy (c), Pierre Esseiva (b), Jorrit van den Berg (a) Keywords: Drug profiling; MDMA; Multivariate distributions; Pearson; Evidence evaluation; Likelihood ratio Abstract: Two likelihood ratio (LR) approaches are presented to evaluate the strength of evidence of MDMA tablet comparisons. The first one is based on a more 'traditional' comparison of MDMA tablets by using distance measures (e.g., Pearson correlation distance or a Euclidean distance). In this approach, LRs are calculated using the distribution of distances between tablets of the same-batch and that of different-batches. The second approach is based on methods used in some other fields of forensic comparison. Here LRs are calculated based on the distribution of values of MDMA tablet characteristics within a specific batch and from all batches. The data used in this paper must be seen as examples to illustrate both methods. In future research the methods can be applied to other and more complex data. In this paper, the methods and their results are discussed, considering their performance in evidence evaluation and several practical aspects. With respect to evidence in favor of the correct hypothesis, the second method proved to be better than the first one. It is shown that the LRs in same-batch comparisons are generally higher compared to the first method and the LRs in different-batch comparisons are generally lower. On the other hand, for operational purposes (where quick information is needed), the first method may be preferred, because it is less time consuming. With this method a model has to be estimated only once in a while, which means that only a few measurements have to be done, while with the second method more measurements are needed because each time a new model has to be estimated. Author Affiliation: (a) Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands (b) Institut de Police Scientifique, University of Lausanne, BAcentstiment de Chimie, CH-1015, Lausanne-Dorigny, Switzerland (c) Institut National de Police Scientifique, Laboratoire de Police Scientifique de Lyon, 31 Avenue Franklin Roosevelt, 69134 Ecully, France Article History: Received 28 January 2009; Revised 8 June 2009; Accepted 8 June 2009

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.forsciint.2009.02.017 Byline: Quentin Milliet, Celine Weyermann, Pierre Esseiva Keywords: Drug profiling; Organic impurities; Physical characteristics; GC-MS Abstract: The profiling of MDMA tablets can be carried out using different sets of characteristics. The first type of measurements performed on MDMA tablets are physical characteristics (i.e. post-tabletting characteristics). They yield preliminary profiling data that may be valuable in a first stage for investigation purposes. However organic impurities (i.e. pre-tabletting characteristics) are generally considered to bring more reliable information, particularly for presentation of evidence in court. This work aimed therefore at evaluating the added value of combining pre-tabletting characteristics and post-tabletting characteristics of seized MDMA tablets. In approximately half of the investigated cases, the post-tabletting links were confirmed with organic impurities analyses. In the remaining cases, post-tabletting batches (post-TBs) were divided in several pre-tabletting batches (pre-TBs), thus supporting the hypothesis that several production batches of MDMA powder (pre-TBs) were used to produce one single post-TB (i.e. tablets having the same shape, diameter, thickness, weight and score; but different organic impurities composition). In view of the obtained results, the hypotheses were discussed through illustrating examples. In conclusion, both sets of characteristics were found relevant alone and combined together. They actually provide distinct information about MDMA illicit production and trafficking. Author Affiliation: Ecole des Sciences Criminelles, Institut de Police Scientifique, University of Lausanne, Batochime, CH-1015 Lausanne-Dorigny, Switzerland Article History: Received 23 July 2008; Revised 13 February 2009; Accepted 25 February 2009

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.forsciint.2009.03.004 Byline: Federica Bonadio, Pierre Margot, Olivier Delemont, Pierre Esseiva Keywords: Drug profiling; HS-SPME; Ecstasy; Data treatment Abstract: A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40mg of crushed MDMA sample was heated at 80 [degrees]C for 15min, followed by extraction at 80 [degrees]C for 15min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing. Author Affiliation: Ecole des Sciences Criminelles, Institut de Police Scientifique, University of Lausanne, Batochime, CH-1015, Lausanne-Dorigny, Switzerland Article History: Received 14 September 2008; Revised 9 January 2009; Accepted 2 March 2009

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.forsciint.2007.12.008 Byline: S. Lociciro (a), P. Esseiva (a), P. Hayoz (a), L. Dujourdy (b), F. Besacier (b), P. Margot (a) Keywords: Cocaine; Drug profiling; Inter-laboratory comparison; ROC curve; Pre-treatments; Cosine and Pearson correlation; Statistics Abstract: Harmonisation and optimization of analytical and statistical methodologies were carried out between two forensic laboratories (Lausanne, Switzerland and Lyon, France) in order to provide drug intelligence for cross-border cocaine seizures. Part I dealt with the optimization of the analytical method and its robustness. This second part investigates statistical methodologies that will provide reliable comparison of cocaine seizures analysed on two different gas chromatographs interfaced with a flame ionisation detectors (GC-FIDs) in two distinct laboratories. Sixty-six statistical combinations (ten data pre-treatments followed by six different distance measurements and correlation coefficients) were applied. One pre-treatment (N+S: area of each peak is divided by its standard deviation calculated from the whole data set) followed by the Cosine or Pearson correlation coefficients were found to be the best statistical compromise for optimal discrimination of linked and non-linked samples. The centralisation of the analyses in one single laboratory is not a required condition anymore to compare samples seized in different countries. This allows collaboration, but also, jurisdictional control over data. Author Affiliation: (a) Institut de Police Scientifique, Ecole des Sciences Criminelles, Universite de Lausanne, BCH, 1015 Lausanne-Dorigny, Switzerland (b) Laboratoire de Police Scientifique de Lyon, 31 avenue Franklin Roosevelt, 69134 Ecully Cedex, France Article History: Received 27 September 2007; Revised 5 December 2007; Accepted 21 December 2007

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.forsciint.2007.10.001 Byline: Celine Weyermann (a), Raymond Marquis (a), Celine Delaporte (a), Pierre Esseiva (a), Eric Lock (c), Laura Aalberg (d), Joseph S. Bozenko (g), Susanne Dieckmann (e), Laurence Dujourdy (b), Frantisek Zrcek (f) Keywords: Drug profiling; Statistics; MDMA; Ecstasy; Organic impurities; GC/MS Abstract: The main objectives of the European project 'Collaborative Harmonisation of Methods for Profiling of Amphetamine Type Stimulants' (CHAMP) funded by the sixth framework programme of the European Commission, included the harmonisation of MDMA profiling methods and the creation of a common database in a drug intelligence perspective. In the preliminary stages of this project, the participating laboratories analysed the physical characteristics, the chemical composition and the organic impurities of MDMA tablets, using the previously harmonised methods. The aim of the present work was to apply statistical treatments to the recorded data in order to evaluate their potential in the fight against drug trafficking. Comparable working procedures were applied on the different types of data. The first part of this article deals with organic impurities data, while the second part focuses on the potential of the physical characteristics. Organic impurities data were recorded by a harmonised Gas Chromatography/Mass Spectrometry (GC/MS) method previously developed. Statistical analysis provided a selection of pertinent variables among the 46 organic impurities identified in the chromatograms. Correlation coefficients were used to yield separation between populations of samples coming from the same synthesis batch and samples coming from different batches. It was shown that correlation measurements based on Pearson and cosine functions applied to the data pre-treated by normalisation to the sum of peak responses followed by the square root provided an excellent discrimination between the two populations. The statistical methods applied to organic impurities profiles proved to be excellent techniques to differentiate samples from different batches and to highlight operational links between samples. Author Affiliation: (a) Institut de Police Scientifique, University of Lausanne, BAcentstiment de Chimie, CH-1015, Lausanne-Dorigny, Switzerland (b) Laboratoire Police Scientifique de Lyon, 31 Avenue Franklin Roosevelt, 69134 Ecully, France (c) Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands (d) National Bureau of Investigation, P.O. Box 285, FIN-01301 Vantaa, Finland (e) Bundeskriminalamt, Thaerstrasse 11, 65193 Wiesbaden, Germany (f) Police of Czech Republic, Institute of Criminalistics Prague, P.O. Box 62/KUP/Strojnicka 27, 17089 Prague, Czech Republic (g) Drug Enforcement Administration, Special Testing and Research Laboratory, 22624 Dulles Summit Court, Dulles, VA 20166, USA Article History: Received 23 May 2007; Revised 20 September 2007; Accepted 5 October 2007

Illicit drug profiling bears a long history. Developments in the field from mid‐90s have led to several international profiling programs. Several countries have put their efforts to develop and implement the routine use of illicit drug profiling in the investigation and prosecution of illicit drug‐related crimes. For more than 20 years, the School of Criminal Sciences (ESC) at the University of Lausanne has, through its illicit drug expertise laboratory, played a main role in promoting the use of illicit drug profiling. In Switzerland, there is no national illicit drug profiling practice and the ESC laboratory is the only one offering such service. However, only a limited number of Swiss jurisdictions send regularly all or part of their seized specimens for analysis to the ESC laboratory. Profiling results are furnished to investigators and prosecutors regardless if they have been requested or not and are stored in a database with limited contextual information with no further data treatment. In 2020, the interruption of a project intended to develop and implement an intercantonal database gathering traditional police data, forensic data (e.g., DNA, fingerprints, etc.), and physical and chemical links, to produce intelligence and support investigation, led to the fundamental question: Is illicit drug profiling in Switzerland condemned to disappear or is it a forgotten treasure, a neglected approach that deserves to be revalued? This paper reports the Swiss situation regarding illicit drug profiling practices and discusses some factors that are thought to impact its use in day‐to‐day work. [ABSTRACT FROM AUTHOR]