Effective validation of chromatographic analytical methods: The illustrative case of androgenic steroids.

The increasing need to develop quantitative chromatographic methods with upgradable multi-targeted approach, allowing flexible and reliable application on large daily workload makes the implementation of an efficient strategy of method's validation and maintenance crucial for the quality assurance policy. The expounding case of a gas chromatographic-mass spectrometric method for the urinary endogenous steroid profiling is presented to illustrate a validation strategy that combines rigorous estimation of validation parameters with highly efficient use of the collected data. The analysis of blank urine samples fortified at six concentration levels with 18 targeted steroids was replicated nine times in three working sessions along twelve days. This dataset of 54 analysis formed the groundwork on which the statistical evaluation of several validation parameters was founded, including calibration, intra- and inter-day accuracy and precision, limit of detection (LOD), limit of quantification, ion abundance ratio repeatability, selectivity, specificity, and carry-over. The preliminary comparison of the response variances at different concentration levels provided the evaluation for heteroscedasticity. Then, the most appropriate calibration model was determined for each steroid, in terms of order (linear vs. quadratic) and weighting, allowing to complete their quantitation in each solution. Intra- and inter-day accuracy and precision were calculated therefrom. LOD values were computed with the Hubaux-Vos method from the weighted linear segment of the calibration curves. Only the assessment of recovery and ionization suppression/enhancement required the execution of further independent experiments. The case study demonstrated that the application of adequate statistical testing typically produced non-homogeneous models of calibration curves, mostly arising from heteroscedastic and quadratic distribution of datasets, unlike what is reported in overly simplified approaches. The misleading information obtained from the regression coefficient R2 to evaluate linearity was evidenced. The strong dependence of calculated LOD and accuracy from the selected calibration parameters was highlighted, making the implementation of an adequate calibration maintenance policy highly advisable.

DNA mixtures interpretation - A proof-of-concept multi-software comparison highlighting different probabilistic methods' performances on challenging samples.

The present study investigated the capabilities and performances of semi-continuous and fully-continuous probabilistic approaches to DNA mixtures interpretation, particularly when dealing with Low-Template DNA mixtures. Five statistical interpretation software, such as Lab Retriever and LRmix Studio - involving semi-continuous algorithms - and DNA•VIEW®, EuroForMix and STRmixTM- employing fully-continuous formulae - were employed to calculate likelihood ratio, comparing the prosecution and the defense hypotheses relative to a series of on-purpose prepared DNA mixtures that respectively contained 2 and 3 known contributors. National Institute of Standards and Technologies (NIST) certified templates were used for samples set up, which contained different DNA amounts for each contributor. 2-person mixtures have been prepared with proportions equal to 1:1, 19:1 and 1:19 in terms of DNA concentration. Conversely, three person mixtures were constituted by proportions equal to 20:9:1, 8:1:1, 6:3:1 and 1:1:1 in terms of DNA concentration. Furthermore, 8 equally-proportioned 3-person mixtures were prepared by means of scalar dilutions starting from an overall amount of 0.500 ng, then ranging up to DNA samples with concentrations equal to 0.004 ng (i.e. Low-Template DNA). DNA mixtures were set up in triplicate and amplified with 7 DNA amplification kits (i.e. GlobalFiler PCR Amplification Kit, NGM SElect PCR Amplification Kit, MiniFiler PCR Amplification Kit, Power Plex Fusion, PowerPlex 6C Matrix System, Power Plex ESI 17 Fast and Power Plex ESX 17 Fast) in order to evaluate whether the selection of a certain kit might represent a bias factor, capable of altering the whole interpretation process. A multi-software approach helped us to highlight any trend in the likelihood ratio results provided by semi- and fully-continuous software. As a matter of fact, fully-continuous computations provided different (higher) results in terms of degrees of magnitude of the likelihood ratio values with respect to those from the semi-continuous approach, regardless of the amplification kit that was utilized.

Development and validation of a Partial Least Squares-Discriminant Analysis (PLS-DA) model based on the determination of ethyl glucuronide (EtG) and fatty acid ethyl esters (FAEEs) in hair for the diagnosis of chronic alcohol abuse.

The chronic intake of an excessive amount of alcohol is currently ascertained by determining the concentration of direct alcohol metabolites in the hair samples of the alleged abusers, including ethyl glucuronide (EtG) and, less frequently, fatty acid ethyl esters (FAEEs). Indirect blood biomarkers of alcohol abuse are still determined to support hair EtG results and diagnose a consequent liver impairment. In the present study, the supporting role of hair FAEEs is compared with indirect blood biomarkers with respect to the contexts in which hair EtG interpretation is uncertain. Receiver Operating Characteristics (ROC) curves and multivariate Principal Component Analysis (PCA) demonstrated much stronger correlation of EtG results with FAEEs than with any single indirect biomarker or their combinations. Partial Least Squares Discriminant Analysis (PLS-DA) models based on hair EtG and FAEEs were developed to maximize the biomarkers information content on a multivariate background. The final PLS-DA model yielded 100% correct classification on a training/evaluation dataset of 155 subjects, including both chronic alcohol abusers and social drinkers. Then, the PLS-DA model was validated on an external dataset of 81 individual providing optimal discrimination ability between chronic alcohol abusers and social drinkers, in terms of specificity and sensitivity. The PLS-DA scores obtained for each subject, with respect to the PLS-DA model threshold that separates the probabilistic distributions for the two classes, furnished a likelihood ratio value, which in turn conveys the strength of the experimental data support to the classification decision, within a Bayesian logic. Typical boundary real cases from daily work are discussed, too.

Effects of various sample pretreatment procedures on ethyl glucuronide quantification in hair samples: Comparison of positivity rates and appraisal of cut-off values.

The quantification of ethylglucuronide (EtG) in hair is nowadays recognized as the approach with the highest diagnostic performance to evaluate harmful drinking. A widely accepted cut-off of 30pg/mg has been selected after several accurate compared studies. While most of the studies that were used to establish the appropriate cut-off value prescribed to cut hair into small segments before their extraction, hair milling has subsequently been identified as the most efficient pretreatment procedure and was therefore recommended in the last Consensus document issued by the Society of Hair Testing. In this study, we initially compared the results obtained with the two sample preparations, namely cutting and milling, both being applied to the same specimens (n=781). Among these, 205 samples produced measurable EtG values with both methods, with differences ranging from -41.7% up to +415% (the mean increase in EtG concentration, switching from cutting to milling, was +62.1% and the median was +42.3%). Among the aforementioned 205 samples, 29 specimens (3.7% of the total 781 samples) produced significantly different outcome, being classified as negative (i.e., below 30pg/mg) if the cutting procedure is used, but largely positive (above 40pg/mg) when milling is used. Subsequently, the positivity rates obtained on a large population dataset (>27,000 samples) with the two procedures, were retrospectively compared using variable cut-offs values. The percentage of head hair samples with EtG concentration exceeding 30pg/mg upon application of the milling procedure shows a 45% increase (from 10.9% to 15.8%) with respect to cutting procedure, whereas the fraction of hair samples with EtG exceeding 40pg/mg (10.5%) overlaps the percentage of positive samples obtained after cutting pretreatment and applying a cut-off of 30pg/mg. On the basis of these results, it would be worth considering the application of cut-off values linked with the pretreatment procedure, taking into account the results of forthcoming inter-laboratory calibrations.