Quality control for serological testing.

OBJECTIVES: The quality control of serological assays remains controversial. The aim of this project was to describe the problems associated with a working model for controlling these assays and solutions, including using a source of well-defined targets and acceptable limits, a process to identify lot-to-lot reagent variation and an interpretation of the result that accounted for the clinical situation. False-negative results are problematic but can be reduced by identifying and comparing reagent lot variation with previous results. METHODS: The components of the Quality Assurance strategy are the following: Lot-to-lot reagent and calibrator variation assessment; dynamic, big-data approach to determine accurate targets and acceptable limits for manufacturer-provided QC material; negative QC monitoring process; use of commutable EQA with a sufficient method subgroup size to assess bias; clinical assessment of any statistically flagged error; and provision of support to the clinician for the interpretation of results. RESULTS: The model described has been used for twelve months, and acceptable variation has been maintained. CONCLUSIONS: The paper presents a solution that emphasizes the early detection of reagent lot variation and patient risk rather than instrument control. Reducing the risk of a false result to patients requires optimal assay quality control and an effective mechanism to support the clinician's use of these results in diagnosis and monitoring. The problems of serological assays are well-known, but there remain few integrated solutions in the literature.

A Comprehensive Guide to Quality Assessment and Data Submission for Genomic Surveillance of Enteric Pathogens.

This document outlines the steps necessary to assemble and submit the standard data package required for contributing to the global genomic surveillance of enteric pathogens. Although targeted to GenomeTrakr laboratories and collaborators, these protocols are broadly applicable for enteric pathogens collected for different purposes. There are five protocols included in this chapter: (1) quality control (QC) assessment for the genome sequence data, (2) validation for the contextual data, (3) data submission for the standard pathogen package or Pathogen Data Object Model (DOM) to the public repository, (4) viewing and querying data at NCBI, and (5) data curation for maintaining relevance of public data. The data are available through one of the International Nucleotide Sequence Database Consortium (INSDC) members, with the National Center for Biotechnology Information (NCBI) being the primary focus of this document. NCBI Pathogen Detection is a custom dashboard at NCBI that provides easy access to pathogen data plus results for a standard suite of automated cluster and genotyping analyses important for informing public health and regulatory decision-making.

[Quality identification of Aurantii Fructus Immaturus from different origins and their adulterants].

Aurantii Fructus Immaturus(AFI) is a traditional Chinese herbal medicine with multiple origins from Citrus aurantium and its legally cultivated variants. With advancements in agricultural biotechnology, many new cultivated varieties have sprung up,leading to an abundance of AFI adulterants and chaos in the herbal medicine markets. This study developed a specific identification method for AFI and its closely related adulterants by examining the appearance trait, content of extract, and multiple ingredients,involving indicators such as the ratio of pulp capsule to cross section diameter(Pc/Cs ratio), the content of extract, and the profile of 11 ingredients. The research finds that:(1) Pc/Cs ratio can conveniently identify adulterants such as Poncirus trifoliata, Ju, and Babagan from the genuine AFI.(2) The extract content can be used to identify adulterants originated from C. wilsonii with C. aurantium.(3) The contents of synephrine in all the samples were in accordance with the Chinese Pharmacopoeia except for the adulterants from P. trifoliata, C. wilsonii, C. aurantium 'Changshanhuyou' and orah mandarins. The synephrine content was high as 1. 40% in some C. sinensis varieties. The mass fraction of hesperidin was over 10. 00% in C. sinensis, while it was below 2. 50% in C. aurantium. C. aurantium contained high levels of naringin(3. 96%-15. 21%) and neo-hesperidin(9. 38%-21. 93%).(4) The compositions of adulterants from P. trifoliata and C. wilsonii were more similar to that of C. aurantium 'Daidai', but with significantly lower neo-hesperidin content(0. 03%-0. 14%) than that in C. aurantium, and they lacked hesperetin and tangeretin. C. maxima(originating from C. maxima) showed closer composition to Choucheng and hybrid originated from Citrus aurantium × Poncirus trifoliata, but had higher hesperidin content(3. 13%) than that in C. aurantium. Ju was closely related to C. sinensis and neither contained naringin nor neo-hesperidin. Hesperidins in Babagan and orah mandarins were similar to that in C. sinensis, with none containing rhoifolin. These quality indicators in combination can accurately distinguish between C. sinensis, C. aurantium, and their closely related adulterants(P. trifoliata, C. wilsonii, C. maxima, orah mandarins and C. reticulata), which are expected to provide a systematic method for quality control of AFI.

[Prediction model of Reduning Injection content based on near-infrared and mid-infrared technology combined with spectral fusion].

In this paper, a method for rapidly determining the content of chlorogenic acid, neochlorogenic acid, cryptochlorogenic acid, gardeniside, and strychnoside in Reduning Injection(RI) was established based on near-infrared spectroscopy(NIRS), midinfrared spectroscopy(MIRS), and spectral fusion technology. Six pretreatment methods and five variable screening methods were investigated, and the best method was selected to establish a partial least square(PLS) model of two single spectra. At the same time,the NIRS and MIRS were fused with equal weights and characteristic bands, and the PLS model was established. The prediction effect of the four models on the quality control components was compared: NIRS>characteristic band fusion>MIRS>equal weight fusion. The relative standard error of prediction(RSEP) of the NIRS models on the five quality control components was less than 2. 5%, and the ratio of performance to deviation(RPD) was greater than 9. 5. The results show that the single spectrum model of NIRS is the best quantitative detection method, and the model of NIRS combined with the PLS algorithm can be used for the rapid detection of Reduning Injection.

[Research strategy for homogenization feeding of Chinese patent medicines].

Chinese patent medicine constitutes a vital segment of the traditional Chinese medicine(TCM) industry and stands as a significant emblem of TCM modernization. At present, the quality stability between batches of Chinese patent medicine preparations has become a pivotal factor directly restricting the high-quality development of the TCM industry. Consequently, addressing the homogeneity of Chinese patent medicines, this paper proposes a research scheme of homogenization feeding. It systematically elaborates on the object and pretreatment of homogenization, operational procedures of homogenization feeding, selection of homogenization evaluation indices, homogenization feeding algorithm, and homogenization feeding process. With the key quality control indicators as the homogenization target, the homogenization feeding process and its quality analysis were discussed. Finally, a demonstration strategy for homogenization feeding of Chinese patent medicine was formed, providing the scientific basis for advancing the research of quality consistency across batches of Chinese patent medicine preparations.

[Quality standards of medicinal and food homologous substances based on dual attributes].

Medicine and food homology culture has a long history in China. With the continuous improvement of people's living standards, there has been a growing investment in health care, leading to significant development in the health industry. Medicinal and food homologous substances, receiving increasing attention, have become the breakthrough and mainstay of the health industry, with broad prospects for related industries. However, the medicinal and edible industry currently faces numerous challenges, especially regarding the research on quality standards for medicinal and food homologous substances, where the study of food attributes is still in its infancy. Therefore, this article elaborated on the current research status of quality standards for medicinal and food homologous substances, clarified the confusion surrounding the concept of medicinal and food homologous substances, and analyzed the weaknesses in the research on food attributes in the quality standards of medicinal and food homologous substances, as well as the lack of unified safety indicators. Based on the dual attributes of medicinal and food homologous substances, it is suggested that research on quality stan-dards should encompass authenticity, safety, nutrition, and efficacy. Under the premise of ensuring authenticity, the safety of exogenous toxic substances should be evaluated in combination with their dual attributes. In the formulation of standards, the nutritional aspect of food properties should be strengthened, and different indicators should be selected for comprehensive quality control based on the sources and properties of medicinal and food homologous substances. By employing multiple techniques for holistic control from various perspectives, a set of systematic quality standards applicable to medicinal and food homologous substances can be established. This study is expected to provide references for the quality control, safe use, and regulation of medicinal and food homologous substances, thereby promoting the healthy development of the entire industry.

[Progress and trend of identification of traditional Chinese medicine based on chemical features].

Variety identification is the prerequisite and foundation for ensuring the quality of traditional Chinese medicine. The safety risks, legal risks, and regulatory trends underline the importance of traditional Chinese medicine varieties. With the industrialization of traditional Chinese medicine and the production of Chinese medicinal materials from wild growing to cultivation and breeding, new varieties of traditional Chinese medicine keep emerging. At the same time, facing the requirements of the entire process control of traditional Chinese medicine quality under the new situation, the current identification technology of traditional Chinese medicine is facing severe challenges. According to the current situation and evolution trend of technologies for traditional Chinese medicine identification, chemical components as the material basis for the effects of traditional Chinese medicine not only have rich characteristics but also can run through the entire quality formation and transmission process of traditional Chinese medicine. Identifying traditional Chinese medicine based on chemical components is the only way to achieve integrated medicine quality and whole-process quality control. The introduction of modern analytical instruments improves the scope and efficiency of obtaining chemical information of traditional Chinese medicine. Big data and artificial intelligence provide new opportunities for deeply interpreting the scientific connotation of chemical characteristic information of traditional Chinese medicine and comprehensively identifying traditional Chinese medicine based on chemical characteristics. Artificial intelligence can be employed to extract high-dimensional chemical information patterns from comprehensive chemical quantitative information collected from a large number of samples, remove the interference of noise information, and discover the chemical characteristics(components, quantity values, and relative proportions of components) that determine the variety. This approach can help to achieve integrated quality identification based on chemical characteristics, reflect the quality transmission process of traditional Chinese medicine, and achieve quality information traceability, providing support for building a whole-process quality control system of traditional Chinese medicine.

ICH M10 Bioanalytical Method Validation Guideline-1 year Later.

The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) adopted Guideline M10 entitled "Bioanalytical Method Validation and Study Sample Analysis" in May 2022. In October 2023, approximately one year after the adoption of the ICH M10 guideline, a "Hot Topic" session was held during the AAPS PharmSci 360 meeting to discuss the implementation of the guideline. The session focused on items the bioanalytical community felt were challenging to implement or ambiguous within the guideline. These topics included cross-validation, parallelism, comparative bioavailability studies, combination drug stability, endogenous analyte bioanalysis, and dilution QCs. In addition, the regulatory perspective on the guideline was presented. This report provides a summary of the Hot Topic session.

Quality assessment of common anti-malarial medicines marketed in Gambella, National Regional State, South Western-Ethiopia.

BACKGROUND: Over the past years, there has been a growing concern that a considerable amount of anti-malarial supply in the underdeveloped world particularly in the private sector, is of poor quality. The World Health Organization (WHO) has received about 1500 reports that mentions instances of substandard and falsified products since 2013. The majority of the reports concerned antibiotics and anti-malarials. The majority of reports (42%) originate from the WHO African region. OBJECTIVE: This study intends to assess the quality of the most widely used anti-malarial medications [artemether-lumefantrine tablets, chloroquine phosphate tablets, primaquine phosphate tablets, artesunate, and artemether injections] in Gambella, South-West, Ethiopia. METHODS: A total of 52 samples were collected on June 2022 from Gambella National Regional State, Ethiopia. Half of the districts (six) located in the four zones of the region were chosen using simple random sampling technique. All drug retail outlets available in the selected districts (locally known as woredas) were included. The samples were subjected to visual inspection with a tool adopted from the joint WHO/FIP/ USP checklist. The pharmacopeial tests for identification, uniformity of dosage forms, assay, thickness, diameter, hardness, friability, disintegration test, dissolution, and sterility tests were carried out according to the USP 44-NF 39 and International Pharmacopoeia 11th edition, 2022 monographs. RESULTS AND DISCUSSION: Only 25% of the samples were registered on the Ethiopian Food and Drug Authority (EFDA's) electronic regulatory/ registration system (ERIS). Besides, 88.8% of artemether injection products were presented in clear glass ampoules. This might expose the products to photochemical degradation that leads to in loss of anti-plasmodial activity. In addition, 50% of the artemether products assessed were not bioequivalent with the comparator product in the in vitro dissolution comparison tests. Overall, the study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. The stated percent of the samples had failed in one or more of the quality test parameters assessed in this study. CONCLUSION: The study findings reveal a high prevalence (58.3%) of substandard anti-malarial drugs in the region. Only a quarter were registered and 38% of the unregistered products failed the quality tests. Hence, the national, regional medicine regulatory bodies and other stake holders should perform the required roles to circumvent presence of Substandard and Falsified (SF) anti-malarial drugs in the study sites.

Label-free ghost cytometry for manufacturing of cell therapy products.

Automation and quality control (QC) are critical in manufacturing safe and effective cell and gene therapy products. However, current QC methods, reliant on molecular staining, pose difficulty in in-line testing and can increase manufacturing costs. Here we demonstrate the potential of using label-free ghost cytometry (LF-GC), a machine learning-driven, multidimensional, high-content, and high-throughput flow cytometry approach, in various stages of the cell therapy manufacturing processes. LF-GC accurately quantified cell count and viability of human peripheral blood mononuclear cells (PBMCs) and identified non-apoptotic live cells and early apoptotic/dead cells in PBMCs (ROC-AUC: area under receiver operating characteristic curve = 0.975), T cells and non-T cells in white blood cells (ROC-AUC = 0.969), activated T cells and quiescent T cells in PBMCs (ROC-AUC = 0.990), and particulate impurities in PBMCs (ROC-AUC ≧ 0.998). The results support that LF-GC is a non-destructive label-free cell analytical method that can be used to monitor cell numbers, assess viability, identify specific cell subsets or phenotypic states, and remove impurities during cell therapy manufacturing. Thus, LF-GC holds the potential to enable full automation in the manufacturing of cell therapy products with reduced cost and increased efficiency.

[Guidelines for quality control of human use experience study on traditional Chinese medicine].

National Medical Products Administration released the Special provisions on the administration of registration of traditio-nal Chinese medicine(TCM) in February 2023, encouraging high-quality human use experience(HUE) study in TCM clinical practice to obtain sufficient evidence for TCM registration support. The provisions suggested that the HUE study should meet the relevant requirements and accept the drug registration verification. This paper aims to standardize the HUE study, obtain high-quality HUE data to support registration applications, and promote the standardization of research. In accordance with the relevant laws and regulations of the state and the requirements of the technical guidelines for the HUE study in the drug review center of the National Medical Products Administration, the clinical characteristics of TCM were considered, and the Clinical Evaluation Committee of Traditional Chinese Me-dicine of the Chinese Pharmaceutical Association organized and formulated the Guidelines for quality control of human use experience study on traditional Chinese medicine,including the conditions of medical institutions carrying out HUE study, researchers, sponsors, key information and requirements of pharmacy, research programs, key points of ethical review, requirements of the research implementation process, risk management, and subject protection of HUE study. After several rounds of consultation with experts, a guideline document suitable for supporting drug registration and guiding HUE study on TCM was finally formed.

Quality Evaluation of Locally Manufactured Paracetamol Tablets in East Africa.

Background: Paracetamol, also known as acetaminophen, is categorized as an analgesic and antipyretic medication and is available as over the counter (OTC) medication. It is commonly used in conditions associated with pain and fever. There is a tendency for community to prefer using imported paracetamol tablets from Europe and United States than from Asia and Africa worrying of the quality of the products. Safety, effectiveness, and efficacy of a medicine can be guaranteed when its quality is reliable; however, there is limited data on the quality of locally manufactured paracetamol tablets, thus necessitating this study. Aim: This study is aimed at assessing the quality of paracetamol tablets 500 mg manufactured by local companies by evaluating their physical parameters, assay results, and dissolution profiles. The compliance of these tablets with the specifications outlined in the British Pharmacopoeia (BP) was analyzed. Additionally, a comparative dissolution test was conducted to assess dissolution profile for innovator product and generics. Method: Five different brands from East African countries with 76 tablets from each brand were compared with the innovator product regarding weight variation, hardness, friability, assay, and dissolution test based on the BP specifications. Results and discussion: All samples of paracetamol tablets 500 mg from the local manufacturers in this study met the specifications set by the BP for physical parameters, including weight variation, friability, hardness, and disintegration tests. The weight variation test, directly related to drug content variation, demonstrated compliance within the acceptable deviation of 5%. Similarly, the assay test, which determines the concentration of the active pharmaceutical ingredient (API), confirmed that all samples complied with the acceptable concentration range of 90%-110% for paracetamol. The dissolution test, assessing the percentage release of the API within a specified time, demonstrated that at 15 min, two samples (diodol and enamol) exhibited lower concentration releases than the required 80%, indicating potential delays in their bioavailability and onset of action. Conclusion: To conclude, all samples had good quality and they can be used for their therapeutic purposes.

Generating pooled quality control samples of volatile organic compounds.

Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace are influenced by several confounding factors not represented in reference standards. In this study, we propose a method of generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow with thermal desorption tubes. Sample tubes were desorbed and split from each sample and recollected onto a single tube, generating a pooled QC sample. This QC sample was then repeatedly desorbed and recollected with a sequentially lower split ratio allowing injection of multiple QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects.

Quality control of elbow joint radiography using a YOLOv8-based artificial intelligence technology.

BACKGROUND: To explore an artificial intelligence (AI) technology employing YOLOv8 for quality control (QC) on elbow joint radiographs. METHODS: From January 2022 to August 2023, 2643 consecutive elbow radiographs were collected and randomly assigned to the training, validation, and test sets in a 6:2:2 ratio. We proposed the anteroposterior (AP) and lateral (LAT) models to identify target detection boxes and key points on elbow radiographs using YOLOv8. These identifications were transformed into five quality standards: (1) AP elbow positioning coordinates (XA and YA); (2) olecranon fossa positioning distance parameters (S17 and S27); (3) key points of joint space (Y3, Y4, Y5 and Y6); (4) LAT elbow positioning coordinates (X2 and Y2); and (5) flexion angle. Models were trained and validated using 2,120 radiographs. A test set of 523 radiographs was used for assessing the agreement between AI and physician and to evaluate clinical efficiency of models. RESULTS: The AP and LAT models demonstrated high precision, recall, and mean average precision for identifying boxes and points. AI and physicians showed high intraclass correlation coefficient (ICC) in evaluating: AP coordinates XA (0.987) and YA (0.991); olecranon fossa parameters S17 (0.964) and S27 (0.951); key points Y3 (0.998), Y4 (0.997), Y5 (0.998) and Y6 (0.959); LAT coordinates X2 (0.994) and Y2 (0.986); and flexion angle (0.865). Compared to manual methods, using AI, QC time was reduced by 43% for AP images and 45% for LAT images (p < 0.001). CONCLUSION: YOLOv8-based AI technology is feasible for QC of elbow radiography with high performance. RELEVANCE STATEMENT: This study proposed and validated a YOLOv8-based AI model for automated quality control in elbow radiography, obtaining high efficiency in clinical settings. KEY POINTS: QC of elbow joint radiography is important for detecting diseases. Models based on YOLOv8 are proposed and perform well in image QC. Models offer objective and efficient solutions for QC in elbow joint radiographs.

Fluorescence hyperspectral imaging technology combined with chemometrics for kiwifruit quality attribute assessment and non-destructive judgment of maturity.

Dry matter content (DMC), firmness and soluble solid content (SSC) are important indicators for assessing the quality attributes and determining the maturity of kiwifruit. However, traditional measurement methods are time-consuming, labor-intensive, and destructive to the kiwifruit, leading to resource wastage. In order to solve this problem, this study has tracked the flowering, fruiting, maturing and collecting processes of Ya'an red-heart kiwifruit, and has proposed a non-destructive method for kiwifruit quality attribute assessment and maturity identification that combines fluorescence hyperspectral imaging (FHSI) technology and chemometrics. Specifically, first of all, three different spectral data preprocessing methods were adopted, and PLSR was used to evaluate the quality attributes (DMC, firmness, and SSC) of kiwifruit. Next, the differences in accuracy of different models in discriminating kiwifruit maturity were compared, and an ensemble learning model based on LightGBM and GBDT models was constructed. The results indicate that the ensemble learning model outperforms single machine learning models. In addition, the application effects of the 'Convolutional Neural Network'-'Multilayer Perceptron' (CNN-MLP) model under different optimization algorithms were compared. To improve the robustness of the model, an improved whale optimization algorithm (IWOA) was introduced by modifying the acceleration factor. Overall, the IWOA-CNN-MLP model performs the best in discriminating the maturity of kiwifruit, with Accuracytest of 0.916 and Loss of 0.23. In addition, compared with the basic model, the accuracy of the integrated learning model SG-MSC-SEL was improved by about 12%-20 %. The research findings will provide new perspectives for the evaluation of kiwifruit quality and maturity discrimination using FHSI and chemometric methods, thereby promoting further research and applications in this field.

[Effects of exogenous 6-BA on flag leaf physiology, yield, and quality of wheat after low temperature stress at booting stage]. / 外源6-BA对孕穗期低温胁迫后小麦旗叶生理、产量及品质的影响.

Low temperature (LT) in spring usually occurs at the booting of winter wheat, resulting in reduction of wheat yield. In this study, we used the LT-sensitive wheat cultivar 'Wanmai 52' and the LT-insensitive wheat cultivar 'Yannong 19' as experimental materials to conduct LT treatment (-2 ℃ and 0 ℃) at booting stage. After the LT treatment, we sprayed 6-benzylaminoadenine (6-BA) solutions with concentrations of 10, 20, and 30 mg·L-1 respectively, with equal mass distilled water as control to investigate the effects of spraying 6-BA on the physiological characteristics, yield and quality of wheat flag leaves after LT stress at booting stage. The results showed that compared with the control, young ear of wheat treated with exogenous spraying 6-BA was fuller, the floret morphology was improved, and the number of vascular bundles under the spike was increased. 6-BA application promoted the accumulation of soluble sugar, soluble protein, and proline in flag leaves. The activities of peroxidase and superoxide dismutase were increased, and the content of malondialdehyde was decreased. Exogenous 6-BA application decreased the number of degenerated spikes of wheat, increased the number of grains per spike and 1000-grain weight, as well as the contents of grain protein, wet gluten, and sedimentation value. In summary, exogenous 6-BA application could effectively alleviate the effects of LT stress on flag leaf and yield of wheat. Under the conditions of this experiment, the mitigation effect of spraying 6-BA solution on Yannong 19 was higher than that of Wanmai 52, and the mitigation effect of spraying 20 mg·L-1 6-BA solution on low temperature stress was the best.

Automated particle inspection of continuously freeze-dried products using computer vision.

The pharmaceutical industry is progressing towards more continuous manufacturing techniques. To dry biopharmaceuticals, continuous freeze drying has several advantages on manufacturing and process analytical control compared to batch freeze-drying, including better visual inspection potential. Visual inspection of every freeze-dried product is a key quality assessment after the lyophilization process to ensure that freeze-dried products are free from foreign particles and defects. This quality assessment is labor-intensive for operators who need to assess thousands of samples for an extensive amount of time leading to certain drawbacks. Applying Artificial Intelligence, specifically computer vision, on high-resolution images from every freeze-dried product can quantitatively and qualitatively outperform human visual inspection. For this study, continuously freeze-dried samples were prepared based on a real-world pharmaceutical product using manually induced particles of different sizes and subsequently imaged using a tailor-made setup to develop an image dataset (with particle sizes from 50µm to 1 mm) used to train multiple object detection models. You Only Look Once version 7 (YOLOv7) outperforms human inspection by a large margin, obtaining particle detection precision of up to 88.9% while controlling the recall at 81.2%, thus detecting most of the object present in the images, with an inference time of less than 1 s per vial.