Establishment of a reference standard database for use in the qualitative and semi-quantitative analysis of pharmaceutical contact materials within an extractables survey by GC-MS

Identification and quantification of medical device extractables and leachables via non-target analysis (NTA); Analytical uncertainty

Leachables are substances that are leached from a medical device during its clinical use and are important due to the patient health-related effects they may have. Thus, medical devices are profiled for leachables (and/or extractables as probable leachables) to assess their potential impact on patient health and safety. This profiling is accomplished by screening extracts or leachates of the medical device for released organic substances via non-targeted analysis (NTA) employing chromatographic methods coupled with mass spectrometric detection. Chromatographic mass spectral response factors (RFs) for extractables and leachables vary significantly from compound to compound, complicating the quantitation of these compounds and the application of assessment strategies such as the Analytical Evaluation Threshold (AET). The analytical uncertainty resulting from response factor variation can be expressed in terms of an uncertainty factor (UF), which estimates the magnitude of response factor variation. This manuscript discusses the concept and impact of analytical uncertainty and provides best practice recommendations for the calculation and use of the uncertainty factor, UF.

CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice

BACKGROUND

Due to the growing amount of COVID-19 research literature, medical experts, clinical scientists, and researchers frequently struggle to stay up to date on the most recent findings. There is a pressing need to assist researchers and practitioners in mining and responding to COVID-19-related questions on time.

METHODS

This paper introduces CoQUAD, a question-answering system that can extract answers related to COVID-19 questions in an efficient manner. There are two datasets provided in this work: a reference-standard dataset built using the CORD-19 and LitCOVID initiatives, and a gold-standard dataset prepared by the experts from a public health domain. The CoQUAD has a Retriever component trained on the BM25 algorithm that searches the reference-standard dataset for relevant documents based on a question related to COVID-19. CoQUAD also has a Reader component that consists of a Transformer-based model, namely MPNet, which is used to read the paragraphs and find the answers related to a question from the retrieved documents. In comparison to previous works, the proposed CoQUAD system can answer questions related to early, mid, and post-COVID-19 topics.

RESULTS

Extensive experiments on CoQUAD Retriever and Reader modules show that CoQUAD can provide effective and relevant answers to any COVID-19-related questions posed in natural language, with a higher level of accuracy. When compared to state-of-the-art baselines, CoQUAD outperforms the previous models, achieving an exact match ratio score of 77.50% and an F1 score of 77.10%.

CONCLUSION

CoQUAD is a question-answering system that mines COVID-19 literature using natural language processing techniques to help the research community find the most recent findings and answer any related questions.

Vertical profile and assessment of soil pollution from a typical coking plant by suspect screening and non-target screening using GC/QTOF-MS

A comprehensive workflow for suspect screening and non-target screening with gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC/QTOF-MS) was used to characterize the pollution characteristics of soil samples in a typical coking plant in China. Suspect screening confirmed 57 chemicals including PAHs, alkyl PAHs, and phthalates contained in high-resolution personal compound database and library (PCDL). Non-target screening detected 88 chemicals from soil samples in the NIST 17 library. A total of 122 chemicals were screened in soil samples, and many of them were of emerging concern. Their presence in the soil obtained from coking operations has been underestimated, such as the oxygenated PAHs (naphtho[2,1-b]furan and 9H-fluoren-9-one), and the alkyl biphenyls compounds (4,4'-dimethylbiphenyl, 3,3'-dimethylbiphenyl, 4-methyl-1,1'-biphenyl and 2,2',5,5'-tetramethyl-1,1'-biphenyl). Toxicity assays by luminescent bacteria proved that the extracts from soil samples at different depths showed varying toxicity to V. qinghaiensis sp.-Q67. Soil extracts from a depth of 20-40 cm exhibited the greatest toxicity to luminescent bacteria compared with the other six-layered soil samples, which was correlated with the number of detectable pollutants and total organic carbon content. This study provided a screening method for suspect and non-target contaminants in urban industrial soil sites, which was important in identifying localized contamination sources.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Trace level determination of eleven nervous system-active pharmaceutical ingredients by switchable solvent-based liquid-phase microextraction and gas chromatography-mass spectrometry with matrix matching calibration strategy

This study utilized switchable solvent liquid-phase microextraction (SS-LPME) to enrich eleven nervous system active pharmaceutical ingredients (APIs) from aqueous samples for their determination at trace levels by gas chromatography mass spectrometry. The analytes selected for the study included APIs utilized in antidepressant, antipsychotic, antiepileptic, and anti-dementia drugs. Parameters of the microextraction method including switchable solvent volume, concentration and volume of the trigger agent (sodium hydroxide), and sample agitation period were optimized univariately to boost extraction efficiency. Under the optimum conditions, the detection limits calculated for the analytes were in the range of 0.20-8.0 ng/mL, and repeatability for six replicate measurements as indicated by percent relative standard deviation values were below 10%. Matrix matching calibration strategy was used to enhance quantification accuracy for the analytes. The percent recovery results calculated for the eleven analytes ranged between 86 and 117%.

Relationship between tracheal intubation and the drugs used by patients with drug overdose due to self-harm

Background

Tracheal intubation may be performed in patients with drug overdose due to self-harm; however, the details of the causative drug are unknown. The purpose of this study was to clarify the relationship between drugs or its blood levels of patients with drug overdose and the need for tracheal intubation based on the actual measurement results.

Methods

From October 2018 to March 2020, 132 patients with drug overdose due to self-harm who were transported to the emergency department (ED) were studied. Patient drugs were measured using gas chromatography–mass spectrometry (GC-MS) and were analyzed on the basis of the GC/MS Forensic Toxicological Database. Logistic analysis was performed by combining patient information and GC-MS information.

Results

The Glasgow Coma Scale (GCS) and Japan Coma Scale (JCS) efficiently predicted tracheal intubation in patients with drug overdose during transport triage; GCS (cut-off value: 12, area under the curve (AUC): 0.81, 95% confidence interval (CI): 0.71–0.88, sensitivity: 0.85, specificity: 0.71, P < 0.05) and JCS (cut-off value: 3, AUC: 0.74, 95% CI: 0.60–0.84, sensitivity: 0.60, specificity: 0.84, P < 0.05). The drugs detected in all patients with drug overdose in order were benzodiazepine receptor agonists (BZs; 43.9%), anticonvulsants (38.6%), antipsychotics (25.0%), and antidepressants (9.8%). In univariate logistic analysis, antipsychotics (odds ratio (OR) 2.46, 95% CI 1.19–5.20, P < 0.05), anticonvulsants (OR 2.71, 95% CI 1.26–5.98, P < 0.05), and anticonvulsants above alert blood levels (OR 27.8, 95% CI 2.92–264.1, P < 0.05) were significantly associated with tracheal intubation in patients with drug overdose, but not BZs and antidepressants. Also, in multivariate logistic analysis, antipsychotics (OR 2.27, 95% CI 1.07–4.83, P < 0.05), anticonvulsants (OR 2.50, 95% CI 1.14–5.64, P < 0.05) and in multivariate logistic analysis of blood levels, anticonvulsants above the alert blood levels (OR 24.9, 95% CI 2.56–241.6, P < 0.05) were significantly associated with tracheal intubation in patients with drug overdose respectively.

Conclusions

Logistic analysis revealed that the use of anticonvulsants and antipsychotics were significantly associated with an increased OR in the tracheal intubation of patients with drug overdose due to self-harm.

Application of dispersive liquid-liquid microextraction based on solidification of floating organic drop for the determination of extractables from pharmaceutical packaging materials

A new method was established for the determination of the extractables from pharmaceutical packaging materials using dispersive liquid-liquid microextraction based on solidification of floating organic drop (DLLME-SFO) coupled with ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF MS). Packaging samples were filled with three kinds of buffer solutions: acid buffer (pH = 3), alkaline buffer (pH = 9) and 0.9% NaCl solution to extract as many extractables as possible, and then the extractables in buffer solutions were enriched by DLLME-SFO technique. Parameters affecting the efficiency of the extraction procedure were evaluated and optimized, including the type and volume of dispersant, extractant volume, pH and vortex-mixing time. After optimization, the values obtained for limits of detection and quantification for three kinds of common antioxidants were 0.3 and 1.0 μg/L respectively, and good linearity (R² > 0.99) was observed in their respective concentration ranges. The recoveries ranged from 80.61% to 117.87% at three spiked levels with the relative standard deviations (RSDs) between 0.92% and 9.29% (n = 6) in all three buffer solutions. The developed method was successfully applied to the analysis of extractables from pharmaceutical packaging materials. The results indicated that the proposed procedure is a novel, sensitive, fast and repeatable method and has a great significance for evaluation of safety of pharmaceutical packaging materials.