Optimization of cloned enzyme donor immunoassay cut-offs for drugs of abuse in whole blood of drivers involved in road accidents

Optimization of biochip assay for illegal substances on drug abusers' whole blood: Randox Evidence vs LC-MS/MS

Immunoassay tests are used in clinical and forensic toxicology laboratories to determine illicit drug use in biological samples. Therefore, this study aims to optimize the cutoff concentrations of DOA I Plus in the blood and compare the LC-MS/MS results. 680 authentic forensic whole blood specimens with Randox Evidence DOA I Plus array were screened for drug of abuse and confirmed by LC-MS/MS. Regarding the manufacturer recommended threshold values, 139 out of 680 authentic blood samples were positive for one or more analytes, while 541 were negative. Nearly all of the 139 positive blood samples confirmed by LC-MS/MS were true positive for one or more analytes, while 522 of the 541 negative blood samples were true negative. The overall sensitivity and the specificity were 87.8% and 99.6%, respectively. THC was considered in detail, and a receiver operator characteristic curve analysis was performed to determine the optimum cutoff for THC, as it accounts for 78% of all positive results according to the manufacturer's recommended thresholds. The optimal threshold value for THC was determined at a concentration of 23 ng/mL, while these values for other parameters were defined as recommended by the manufacturer.

Rapid screening procedures for a variety of complex forensic samples using laser diode thermal desorption (LDTD) coupled to different mass spectrometers

RATIONALE

The applications shared in this paper demonstrate the wide variety of samples that can be analyzed when Laser Diode Thermal Desorption (LDTD) is interfaced with a high-resolution mass spectrometer and show the speed at which high quality data can be generated from complex matrices.

METHODS

Samples are solvent extracted and spotted in a 96-well plate. In the case of biological fluids, hydrolysis followed by solid-phase extraction is required. The solvent in the 96-well plate is evaporated followed by mass spectrometric (MS) analysis with atmospheric pressure chemical ionization. Where applicable, the instrument is operated in data-dependent mode, with a full-scan mass spectrum followed by MS/MS spectra of the top 10 ions with a total runtime of 0.4 min.

RESULTS

Four applications (MAAQ and Tear Gas, twelve rodenticides, seven explosives, and 40 drugs of abuse) are reported in this paper. MAAQ, tear gas, and rodenticides were identified by full-scan, followed by MS/MS experiments at levels of 125 μg/L, 125 μg/L, and 500 μg/L, respectively. Explosives were all identified at 102 μg/L by full-scan experiments. The drugs of abuse were identified by multiple reaction monitoring (MRM) experiments at defined cutoff levels from 2 to 1000 μg/L.

CONCLUSIONS

Interfacing LDTD with a mass spectrometer allows for rapid screening of a wide range of samples, with either minimal or complex sample preparation. Using a high-resolution mass spectrometer with the combination to perform full-scan and MS/MS experiments adds a high level of specificity.

Development and validation of a rapid LC-MS/MS method for the detection of 182 novel psychoactive substances in whole blood

Introduction

The analysis of novel psychoactive substances (NPS) represents a challenge in forensic toxicology, due to the high number of compounds characterized by different structures and physicochemical properties both among different subclasses and within a single subclass of NPS. The aim of the present work is the development and validation of a targeted liquid chromatography tandem mass spectrometry (LC‐MS/MS) method for the detection of NPS in whole blood.

Materials and methods

A protein‐precipitation based LC‐MS/MS method for the detection of more than 180 NPS was developed and validated by assessing the following parameters: selectivity, linearity, accuracy, precision, limit of detection (LOD) and of quantification (LOQ) recovery, and matrix effect. Then, the method was applied to real forensic samples.

Results

The method allowed the identification of 132 synthetic cannabinoids, 22 synthetic opioids, and 28 substances among synthetic cathinones, stimulants, and other drugs. Validation was successfully achieved for most of the compounds. Linearity was in the range of 0.25–10 ng/ml for synthetic cannabinoids and 0.25–25 ng/ml for other drugs. Accuracy and precision were acceptable according to international guidelines. Three cases tested positive for fentanyl and ketamine, in the setting of emergency room administration.

Conclusions

The present methodology represents a fast, not expensive, wide‐panel method for the analysis of more than 180 NPS by LC‐MS/MS, which can be profitably applied both in a clinical context and in postmortem toxicology.

Adjusted binary classification (ABC) model in forensic science: An example on sex classification from handprint dimensions

Binary classification techniques are commonly used in forensic examination to test if a specimen belongs to a particular group and base the expert opinion on the questioned evidence. However, most of the currently used methods do not achieve sufficient accuracy due to the ignoring of the specimens classified in the overlapping area. To address the issue, we proposed a novel Adjusted binary classification (ABC) algorithm that automatically adjusts posterior probabilities to reach classification accuracy and positive/negative predicted values (PPV, NPV) of 95 %. In the presented example, we used three handprint measurements from 160 participants (80 males and 80 females) to develop models that would classify sex from their dimensions. The sample was split into the training/cross-validated (70 %) and testing sample (30 %). We developed four classification models using linear discriminant analysis (LDA) by employing traditional single cut-off values and ABC approach that for each group provides a specific posterior probability cut-off threshold. In the cross-validated sample, the accuracy of traditional models was 78.7-92.5 %, while PPVs/NPVs ranged between 78.2 and 93 %. ABC models provided 95 % accuracy, PPV, and NPV, and could classify 35.5-88.1 % of specimens. In the testing sample, ABC models achieved accuracy of 97.3-100 %, PPV/NPV 95.4-100 %, and could be applied to 29.1-87.5 % of specimens. The study demonstrated that the ABC approach could adjust classification models to reach predefined values of accuracy, PPV, and NPV. Therefore, it could be an efficient tool for conducting a binary classification in forensic settings and minimizing the possibilities of incorrect classifications.

Optimization of cloned enzyme donor immunoassay cut-offs for drugs of abuse in post-mortem whole blood

INTRODUCTION

Immunoassay (IA) tests are not widely applied in post-mortem samples, since they are based on technologies requiring relatively non-viscous specimens, and compounds originating from the degradation of proteins and lipids during the post-mortem interval can alter the efficiency of the test. However, since the extraction techniques for IA tests are normally rapid and low-cost, IA could be used as near-body drug-screening for the classes of drugs most commonly found in Italy and Europe. In this study, semi-quantitative results on post-mortem whole blood samples obtained through CEDIA analysis (cannabinoids, cocaine, amphetamine compounds, opiates and methadone), were compared with results of confirmatory analysis obtained using GC-MS. Screening cut-offs for all drugs were retrospectively optimized.

METHODS

Post-mortem whole blood samples from autopsy cases of suspected fatal intoxication were collected over 3 years. Samples were initially analyzed through CEDIA (CEDIA, ILab 650, Werfen). Confirmatory analyses were then performed by GC-MS (QP 2010 Plus, Shimadzu). Screening cut-offs were retrospectively optimized using Receiver Operating Characteristic (ROC) analysis.

RESULTS

CEDIA results were available for 125 samples. Two-hundred-eighty-nine (289) positive screening results were found. Among these, 162 positive confirmation results were obtained. Optimized screening cut-offs were as follows: 6.5ng/ml for THC; 4.2ng/ml for THC-COOH; 12.0ng/ml for cocaine; 6.6ng/ml for benzoylecgonine; 6.4ng/ml for opiates; 2.0ng/ml for methadone. Analysis of ROC-curves showed a satisfying degree of separation in all tests except for amphetamine compounds, with areas under the curve (AUC) between 0.915 (THC) and 0.999 (for benzoylecgonine and methadone).

DISCUSSION

The results of the study showed that CEDIA screening at the optimized cut-offs exhibits a very high sensitivity and good specificity and positive predictive value (PPV) for cannabinoids, cocaine and metabolites, opiates and methadone. A high number of false positives (n=19) for amphetamine compounds was observed at the optimized cut-off, resulting in a very low PPV, which is also influenced by the very low number of TP (n=4).

CONCLUSION

The results of the study show that the CEDIA is a valuable screening test on post-mortem whole blood for cannabinoids, cocaine and metabolites, opiates and methadone, but it is not recommended for amphetamine compounds, due to the high number of false positives. The strengths of the study are the large sample size, the inclusion of post-mortem cases only and the high level of sensitivity and specificity obtained at the optimized cut-offs.

Alcohol and illicit drugs in drivers involved in road traffic crashes in Italy. An 8-year retrospective study

This study aims to investigate the prevalence of alcohol and drugs of abuse in Italian drivers involved in road traffic crashes between 2011 and 2018. Toxicological analyses were performed on the whole blood of 7593 injured drivers. Alcohol and illicit drugs, namely tetrahydrocannabinol (THC; cut-off 2ng/ml), cocaine (cut-off 10ng/ml), illicit opiates (cut-off 10ng/ml) and amphetamines (amphetamine, methamphetamine, MDMA, MDA; cut-off 20ng/ml) were investigated. The age and gender of the driver, the time of the crash (weekend/weekday and day/night), the road crash year and Blood Alcohol Concentration (BAC) were also considered. The 16.2% of samples tested positive for alcohol, 2.5% for cocaine, followed by opiates (2.0%), cannabinoids (1.5%), and amphetamines (0.5%). The overall prevalence of alcohol and drugs was lower than those reported in previous epidemiological studies of the DRUID project. The year 2011 showed the highest prevalence of drug-positive cases (24.1%), while the lowest prevalence was found in 2016 (16.8%), after the update of the Road Traffic Law (RTL) that increased punishments for driving under the influence. A progressive increase in the number of alcohol-positive female drivers was observed from 2011 to 2018, and the highest prevalence was found in the 26-35-year-old age range. Illicit drugs showed the highest overall prevalence in drivers <26 years of age but, if considering single drugs, cocaine and opiates were mostly found in subjects older than 36 years of age. A higher percentage of drug-positive drivers was found on weekend nights for alcohol and on both weekend and weekday nights for drugs. The types of drugs used by drivers did not change during the studied period.

Prevalence of therapeutic drugs in blood of drivers involved in traffic crashes in the area of Bologna, Italy

INTRODUCTION

Psychoactive medicines, such as benzodiazepines and Z-drugs (BdZ), antidepressants and antipsychotics (AA) and medical opioids (MO), have an impairing effect on driving ability. In previous epidemiological studies performed on impaired and/or injured drivers, not all relevant psychoactive substances were included in the toxicological assessment, and their prevalence may be underestimated. This study aims to assess the prevalence of a large set of psychoactive substances (n=53) in Italian drivers involved in a road traffic crash and in predefined population subgroups.

MATERIALS AND METHODS

The toxicological analyses were performed on the whole blood of 1026 drivers involved in a road traffic crash in the area of Bologna, Italy, from January 2017 to March 2018. Analyses were performed using GC-FID (alcohol), GCMS (illicit drugs) and LC/HRMS (psychoactive drugs). The population was divided into subgroups according to gender, age and crash time. Descriptive statistics were used in order to assess differences among sub-groups.

RESULTS

The highest prevalence was found for alcohol (17.3%), followed by medicinal drugs (13.6%) and illicit drugs (5.5%). The prevalence of BdZ, AA and MO were 7.3%, 7.2% and 3.1%, respectively. The frequency of BDZ and AA was significantly higher in female drivers and showed higher prevalence at increasing age. The presence of medicinal drugs was significantly higher during the week and in crashes occurring during the day.

CONCLUSION

Results for alcohol and illicit drugs partially overlap with those reported in previous European and Italian studies, but the prevalence of BdZ was much higher. We also found a high prevalence of AA, which are rarely investigated in epidemiological studies performed on drivers, but may cause impairment of the ability to drive, especially when taken in combination with alcohol or other drugs. The pattern of medication use differs from that involving drugs of abuse, since it is mainly observed in female subjects and older drivers and does not follow the same weekly trend observed for alcohol and other illicit drugs.