Analytical evaluation of five oral fluid drug testing devices

Introduction: The correlation with blood drug presence and the easiness of sample collection make oral fluid an ideal matrix for roadside drug tests targeting impaired drivers. Aim: To evaluate the reliability of five oral fluid testing devices: Varian OraLab®6, Dräger DrugTest® 5000, Cozart® DDS 806, Mavand RapidSTAT® and Innovacon OrAlert. Method: More than 760 samples were collected from volunteers either at drug addiction treatment centres or during roadside sessions. Target drug classes were amphetamines, cannabinoids, cocaine and opiates for all devices. Dräger DrugTest® 5000 (137 samples tested), Cozart® DDS 806 (n=138) and Mavand Rapid STAT® (n=133) could also detect the presence of benzodiazepines, while phencyclidine could be detected using Varian OraLab® 6 (n=249) and Innovacon OrAlert (n=110). Samples were tested on-site with one of the selected devices. Volunteers provided an additional oral fluid sample for confirmation analysis by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS). Sensitivity, specificity, accuracy and prevalence were calculated applying Belgian legal confirmation cut-offs.Results : All devices showed good specificity for all drug classes. Sensitivity and accuracy were very variable among devices and drug classes. Overall, when applying Belgian law cut-offs, sensitivity was always unsatisfactory for cocaine (highest sensitivity 50%), moderate or very low for cannabis and amphetamines (23-80% and 17-75% respectively).Conclusions : Considering that cannabis, followed by amphetamines, is the most prevalent drug among impaired drivers in Belgium, only one device was sensitive enough to be used during roadside police controls. This abstract has been produced under the project “Driving Under the Influence of Drugs, Alcohol and Medicines” (DRUID) financed by the European Community within the framework of the EU 6th Framework Program. This abstract reflects only the author's view. The European Community is not liable for any use that may be made of the information contained thereinIntroduction: The correlation with blood drug presence and the easiness of sample collection make oral fluid an ideal matrix for roadside drug tests targeting impaired drivers. Aim: To evaluate the reliability of five oral fluid testing devices: Varian OraLab®6, Dräger DrugTest® 5000, Cozart® DDS 806, Mavand RapidSTAT® and Innovacon OrAlert. Method: More than 760 samples were collected from volunteers either at drug addiction treatment centres or during roadside sessions. Target drug classes were amphetamines, cannabinoids, cocaine and opiates for all devices. Dräger DrugTest® 5000 (137 samples tested), Cozart® DDS 806 (n=138) and Mavand Rapid STAT® (n=133) could also detect the presence of benzodiazepines, while phencyclidine could be detected using Varian OraLab® 6 (n=249) and Innovacon OrAlert (n=110). Samples were tested on-site with one of the selected devices. Volunteers provided an additional oral fluid sample for confirmation analysis by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS/MS). Sensitivity, specificity, accuracy and prevalence were calculated applying Belgian legal confirmation cut-offs.Results : All devices showed good specificity for all drug classes. Sensitivity and accuracy were very variable among devices and drug classes. Overall, when applying Belgian law cut-offs, sensitivity was always unsatisfactory for cocaine (highest sensitivity 50%), moderate or very low for cannabis and amphetamines (23-80% and 17-75% respectively).Conclusions : Considering that cannabis, followed by amphetamines, is the most prevalent drug among impaired drivers in Belgium, only one device was sensitive enough to be used during roadside police controls. This abstract has been produced under the project “Driving Under the Influence of Drugs, Alcohol and Medicines” (DRUID) financed by the European Community within the framework of the EU 6th Framework Program. This abstract reflects only the author's view. The European Community is not liable for any use that may be made of the information contained thereinC