Current Quality Control Methods Research Articles

From biological potency absorbed components to artificial intelligence mining: A review of analytical strategies for the discovery and validation of quality marker in traditional Chinese medicine in the past decade

Quality control of Traditional Chinese Medicine (TCM) is fundamental to ensuring its clinical efficacy, with TCM formulas being the primary form used in clinical practice. Current quality control methods for TCM formulas often rely on pharmacopoeial standards for individual medicinal materials, typically encompassing only characteristic or partial active ingredients. These methods fail to fully reflect the clinical efficacy of TCM formulas. Consequently, exploring the multiple efficacious components in TCM formulas and establishing the correlation between multi-component content and efficacy has become an urgent issue in the modern quality assessment of TCM formulas. The quality marker (Q-marker) has emerged as a crucial standard in this field, achieving notable success in recent years. This paper reviews recent progress in the development of the Q-marker system in TCM by highlighting strategies based on the correlation between efficacy and constituents, using analytical techniques to investigate the material basis and efficacy of TCM. However, the aforementioned methods inevitably involve human selection factors. With the widespread application of artificial intelligence (AI) learning algorithms, it is now possible to develop a modern quality evaluation method for the multi-component “efficacy-quality” correlation in TCM formulas. This approach leverages AI techniques to explore novel and quantifiable methods for scientific and rational quality control in TCM formulas. In this paper, important future directions and questions in this field are also discussed.

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.

Analysis of an Aqueous Extract from Turkish Galls Based on Multicomponent Qualitative and Quantitative Analysis Combined with Network Pharmacology and Chemometric Analysis.

The current quality control method for Turkish gall (TG) is limited to assessing total tannin or gallic acid (GA), which offers a basic level of quality control but does not fully capture the true quality of TG. Therefore, it is essential to establish a comprehensive method that utilizes multiple indicators to assess the intrinsic quality of TG. This research utilized UPLC-Q-TOF-MS/MS technology to qualitatively analyze the chemical composition of TG. Subsequently, the potential main active ingredients, targets, and pathways of TG in treating recurrent aphthous ulcers (RAU) were explored and analyzed using network pharmacology technology. Quantitative analysis of multicomponents by single marker (QAMS) was then employed to quantify the primary pharmacodynamic components in TG. Finally, chemometrics analysis was utilized to interpret the measured results and identify the markers of scavenging quality. The study identified 36 chemical components in TG, highlighting ellagic acid (EA), GA, and so on as key components in treating RAU. A method for simultaneously determining GA, EA, 1,2,3,6-tetra-O-galloyl-β-D-glucose (TEGG) and 1,2,3,4,6-penta-O-galloyl-β-D-glucose (PEGG) in TG was established. Statistical analysis revealed significant differences in the content of these 4 components across 14 batches of TG, with GA and PEGG identified as the primary contributors to the variations. This study determined a quality index for TG, providing a reference for quality evaluation and introducing a cost-effective and efficient quality control method. Furthermore, it addressed the challenge of developing new Chinese medicine by overcoming the lack of reference substances.

Exploring new dimensions: Single and multi-block analysis of essential oils using DBDI-MS and FT-IR for enhanced authenticity control

BackgroundEssential oils (EOs) are complex mixtures of volatile hydrocarbons with a wide range of applications in the pharmaceutical, fragrance and food industry. The composition of EOs is highly variable and can affect their quality and pharmaceutical efficacy. Moreover, the high economic value of EOs, such as those obtained from Rosa damascena, make falsification and misclassification a lucrative business. Consequently, adulterations can lead to serious health consequences for consumers. While current quality control methods for EOs involve analysing their chromatographic profile or comparing their Fourier transform infrared (FT-IR) spectra, these methods can be time-consuming or lack sensitivity. To address these issues, we compared state-of-the-art quality control methods, including gas chromatography flame ionization detection (GC-FID) quantification and enantiomeric ratio determination, FT-IR spectrometry with dielectric barrier discharge ionization coupled to triple quadrupole mass spectrometer (DBDI-MS), in a chemometric single- and multi-block approach. ResultsOur results show that the best classification accuracy of 94.7% for R. damascena samples was obtained using GC-FID combined with partial least square discriminant analysis (PLS-DA). Comparatively, the enantiomeric ratios did not improve classification accuracy. In contrast, fragmentation data from DBDI-MS (Q3), which was acquired in a fraction of the analysis time and without extensive sample preparation, achieved a classification accuracy of 84.2%. We also found that combining FT-IR with parent ion DBDI-MS (Q1) data in a multi-block sequentially orthogonalized partial least squares linear discriminant analysis (SO-PLS-LDA) model improved classification accuracy, compared to their respective single-block PLS-DA models. SignificanceOverall, our study demonstrates that DBDI, as an ambient ionization method, has significant potential for high-throughput screening. When combined with MS, it can produce comparable classification accuracies to conventional methods, while offering the added benefits of speed and convenience. As such, DBDI-MS is a promising tool for EO quality control.

Identification of the anti-inflammatory quality markers of Chrysanthemi Flos (Juhua) using spectrum-effect relationships combined with bioactivity re-evaluation.

Chrysanthemi Flos (Juhua), an edible herbal medicine that possesses efficacies of dispersing wind, clearing heat and detoxifying. Studies have demonstrated that the health benefits of Chrysanthemi Flos are largely attributable to its anti-inflammatory effects. However, the correlation between the compounds monitored by the current quality control methods and the anti-inflammatory effects of Chrysanthemi Flos is unclear. In order to better control the quality of Chrysanthemi Flos, the identification of anti-inflammatory quality markers (Q-markers) of Chrysanthemi Flos was performed. The chemical components of Chrysanthemi Flos were profiled by HPLC fingerprints combined with chemometrics methods. Simultaneously, the anti-inflammatory activities of 10 batches of water extracts of Chrysanthemi Flos were evaluated in lipopolysaccharide-activated RAW 264.7 macrophages cells. Gray correlation analysis was performed to assess the relationship between the anti-inflammatory activity and chemical properties. The results showed that 13 common peaks were closely correlated with the anti-inflammatory effect, and further bioactivity re-evaluation confirmed that 10 known compounds exerted a strong anti-inflammatory effect. The quantitative analysis of the 10 Q-markers showed that the 25 batches of samples could be discriminated into different zones according to their producing areas. Conclusively, the present work identified 10 anti-inflammatory Q-markers of Chrysanthemi Flos using spectrum-effect relationships combined with bioactivity re-evaluation.

Relate building information modeling to quality management according to the different quality management phases

Buildings are becoming larger and more complex in today’s world. As a result, the old method of personally inspecting a building’s design is no longer efficient, as it is time-consuming and labor-intensive. Establishing and automating systems for inspecting building quality is becoming increasingly crucial. Building Information modeling (BIM) enables for quick decision-making and evaluation by automatically verifying if buildings meet standards. In this case. Real-time quality control and early fault detection are still the most effective methods for decreasing project schedule and expense overrun in the construction process. Current quality control methods on construction sites are inefficient and time-consuming since they only offer data at specified locations and times to reflect the work in progress, limiting a quality manager’s ability to quickly identify and handle faults. The goal of this research is to show how important BIM is in quality management in terms of its many phases. (inspection, control, and quality assurance).

Less is more: Vital roles of bioactive equivalency in assessing food quality

Less is more: Vital roles of bioactive equivalency in assessing food quality

Real-Time Nondestructive Evaluation of Additive Manufacturing Using a Laser Vibrometer and Shock Tube

Abstract Additive manufacturing (AM) parts retain a certain degree of individuality and could suffer from a combination of different defect types, and therefore the nondestructive evaluation on AM parts remains a challenging task. Engineering non-contact and nondestructive real-time inspection and in situ quality assurance of AM parts would be a net improvement compared to current quality control methods that are conducted post-production. Here, the authors propose to combine the use of a laser vibrometer with a compression-driven shock tube to assess the quality of AM parts through the evaluation of the vibration spectra of the part. An AM of a cylindrical part was selected for the study, along with different defect types and sizes. These defects include internal voids of different sizes at different locations, local changes in thickness (infill), and local changes in melting temperatures. A numerical model was created and validated using experimental data to conduct model-assisted probability of detection (MAPOD). Results were analyzed by evaluating correlation matrices between different models. Results showed that vibration spectra induced by a shock wave were sensitive to different types and sizes of defects under the studied geometry. The defect index yielded an approximately linear relationship with respect to defect void severity. MAPOD curve studies revealed a minimum detectable void defect of 0.039% of the AM part’s volume.

Study on quality control of Zuojin pill by HPLC fingerprint with quantitative analysis of multi-components by single marker method and antioxidant activity analysis

Current quality control methods for Zuojin Pill (ZJP) lack comprehensiveness and practicability. This study aimed to develop a comprehensive strategy for the quality evaluation of ZJP and the prediction of potential bioactive components in ZJP. First, an HPLC method with excellent separation of main components was developed and was used to establish the chromatographic fingerprint of ZJP. Similarities were calculated by comparing 28 batches of ZJPs with the reference fingerprint and the resulting similarity values were all greater than 0.976. The 28 samples were classified into different groups according to their origins by Hierarchical Cluster Analysis, Principal component analysis, and orthogonal partial least squares discriminant analysis. Based on the classification, eight quality markers (Q-Markers) affecting the quality of ZJP were discovered. Then, using berberine as an internal standard substance, quantitative analysis of multi-components by single marker method (QAMS) for the determination of eight Q-markers was developed. The results showed that there was no significant difference between QAMS and external standard method (P＞0.05). Finally, using an off-line antioxidant system and partial least-squares model (PLS), the fingerprint-efficacy relationship of ZJP was constructed to explore and predict the bioactive components in ZJP. The present study strategy could be also applied to comprehensive quality study of other TCMs.

Rapid and Simultaneous Quantification of Six Aristolochic Acids and Two Lignans in Asari Radix et Rhizoma Using Ultra-Performance Liquid Chromatography-Triple Quadrupole Tandem Mass Spectrometry.

Asari Radix et Rhizoma (AR) is a widely-used Chinese herbal medicine containing multiple active lignans and rare nephrotoxic components-aristolochic acids derivatives (AAs). However, the current quality control method carried out by Chinese Pharmacopoeia has defects in trace AAs detection and insufficient marker ingredients, which is unable to comprehensively evaluate the efficacy and safety of AR. To improve the quality control method of AR, a rapid, sensitive, and reliable chromatographic analytic method based on ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry (UHPLC-QqQ-MS) was established for the simultaneous analysis of multiple AAs and lignans in AR samples. Positive electrospray ionization mode with multiple reaction monitoring (MRM) was applied for the detection of the eight analytes. The method showed available linearity (R2 ≥ 0.991), the limit of quantification (2–5 ng/mL), precision (RSD <8.12%), and accuracy (89.78–112.16%). A total of 6 AAs and 2 lignans were quantified for their content in 15 AR samples. The content of AA-IVa, AA-VIIa, and aristololactam I (AL-I) was much higher than the AA-I controlled by pharmacopoeia. Considering the potential toxicity of AAs, AA-IVa, AA-VIIa, and AL-I should also be controlled in AR. A considerable amount of active sesamin was detected in AR, suggesting that it could be added as a quality marker for the quality control of AR. The newly developed analytical method could be applied for the fast evaluation of toxic AA's content and quality during quality control of AR or preparations containing AR.

Assessment of quality predictions achieved with machine learning using established measurement process capability procedures in manufacturing

Abstract The increasing amount of available process data from machining and other manufacturing processes together with machine learning methods provide new possibilities for quality control and condition monitoring. A prediction of the workpiece quality in an early machining stage can be used to alter current quality control strategies and could lead to savings in terms of time, cost and resources. However, most methods are tested under controlled lab conditions and few implementations in real manufacturing processes have been reported yet. The main reason for this slow uptake of this promising technology is the need to prove the capability of a machine learning method for quality prediction before it can be applied in serial production and supplement current quality control methods. This article introduces and compares approaches from the fields of machine learning and quality management in order to assess predictions. The comparison and adaption of the two approaches is carried out for an industrial use case at Bosch Rexroth AG where the diameter and the roundness of bores are predicted with machine learning based on process data.

Improving Tolerance Control on Modular Construction Project with 3D Laser Scanning and BIM: A Case Study of Removable Floodwall Project

Quality control is essential to a successful modular construction project and should be enhanced throughout the project from design to construction and installation. The current methods for analyzing the assembly quality of a removable floodwall heavily rely on manual inspection and contact-type measurements, which are time-consuming and costly. This study presents a systematic and practical approach to improve quality control of the prefabricated modular construction projects by integrating building information modeling (BIM) with three-dimensional (3D) laser scanning technology. The study starts with a thorough literature review of current quality control methods in modular construction. Firstly, the critical quality control procedure for the modular construction structure and components should be identified. Secondly, the dimensions of the structure and components in a BIM model is considered as quality tolerance control benchmarking. Thirdly, the point cloud data is captured with 3D laser scanning, which is used to create the as-built model for the constructed structure. Fourthly, data analysis and field validation are carried out by matching the point cloud data with the as-built model and the BIM model. Finally, the study employs the data of a removable floodwall project to validate the level of technical feasibility and accuracy of the presented methods. This method improved the efficiency and accuracy of modular construction quality control. It established a preliminary foundation for using BIM and laser scanning to conduct quality control in removable floodwall installation. The results indicated that the proposed integration of BIM and 3D laser scanning has great potential to improve the quality control of a modular construction project.

Quality consistency evaluation of commercial transfer factor injections by chromatographic fingerprint combined with multivariate statistical analysis.

The current quality control methods relying mainly on chromogenic reaction can hardly ensure the quality and safety of the biochemical drug with complex chemical composition. Therefore, a chromatographic fingerprint method was developed for the quality evaluation of a multicomponent biochemical drug, transfer factor injection. High-performance liquid chromatography fingerprint was measured by using a C18 column (250 × 4.6mm, 5 µm) with a mobile phase composed of 0.1% trifluoroacetic acid-water and 0.085% trifluoroacetic acid-acetonitrile under gradient elution. The developed method was validated and was subsequently applied to 57 batches of commercial products which were sampled by National Drug Assessment Program. High-resolution mass spectrometry analysis was performed on characteristic peaks of fingerprints, and a series of amino acids, nucleosides, and deoxynucleosides were identified. In the fingerprint assessments, principal component analysis and Hotelling T2 analysis yielded the best results. The results generally indicated that there was a significant difference among products of batch-to-batch or from different manufacturers. Abnormal samples and its discriminatory components were also explored. In summary, the established fingerprinting method with multivariate statistical analysis could offer an efficient, reliable, and practical approach for quality consistency evaluation of transfer factor injection, providing a reference for the quality control of other multicomponent biochemical drugs.

A Quality Control Method Based on an Improved Kernel Regression Algorithm for Surface Air Temperature Observations

An improved kernel regression (IKR) method based on an adaptive algorithm and particle swarm optimization is proposed. Considering the limitations of current quality control methods in different regions and on multiple time scales, the kernel regression algorithm is applied to the quality control of surface air temperature observations. Observations of 12 reference stations in Jiangsu from 1961 to 2008 and of 14 regions in China from 2010 to 2014 were selected. The analysis of surface air temperature observations was performed in terms of the mean absolute error (MAE), root mean square error (RMSE), consistency indicator (IOA), and Nash–Sutcliffe model efficiency coefficient (NSC). The results indicate that compared with the traditional IDW and SRT methods, the IKR method has a high error detection rate. Furthermore, the IKR method achieves better predictions and fitting in the single-station and multistation regression experiments in Jiangsu and in the national multistation regression prediction experiment.

Mass Spectrometry-Sensitive Probes Coupled with Direct Analysis in Real Time for Simultaneous Sensing of Chemical and Biological Properties of Botanical Drugs.

The development of botanical materials as therapeutic agents involves the meticulous assessment of safety, efficacy, and quality. Compared with small-molecule drugs, quality control of botanical drugs confronts with more significant challenges due to their inherent complexity. Current quality control methods for botanical drugs, either prevailing chemical tests or emerging biological assays, are not able to meet recent demands of multiplexing, sensitivity, and speed. Here, we propose an on-demand strategy based on a direct analysis in real time-mass spectrometry (DART-MS) platform, which is capable of simultaneously analyzing multiple constituents and bioactivities of botanical drugs. Notably, the bioactivities are assessed by a multiple-enzyme assay that adopts cleavable mass spectrometry probes as enzymatic substrates: these probes labeled with a piperazine tag make possible sensitive, multiplexed, and quantitative enzyme activity measurements. The concept is successfully demonstrated via a case study of Danshen (Salvia miltiorrhiza) Injection where simultaneous detection of 34 constituents and inhibitory activities on two target enzymes can be achieved in just minutes. This proof-of-concept application also gives evidence that combining MS-sensitive probes with DART-MS can provide an environmentally friendly, highly sensitive analytical approach for botanical quality control.

The Application of Standard Material Absorbance for QC of QuantiFERON-TB Test

In the QuantiFERON-TB test, the concentration of interferon gamma released by activated T cells exposed to tuberculosis-specific antigen is measured by ELISA. Nil, TB Ag, and mitogen of positive or negative patient samples were pooled and used internal QC. We analyzed the suitability of quality control using OD of standard for No1 to No4 instead of self-manufactured pool plasma. A total of 348 tests from September 2016 to March 2017 were included. The OD of standards of four levels was detected, and the calculation according to the formula and the creation of a standard curve related to the OD and concentration were performed every test. We computed the mean, standard deviation (SD), and coefficient of variation (CV) of the calculated values and the ranges of slope, intercept, and correlation coefficient (r) of standard curve. The values of calculation using OD satisfied the acceptability of every test compared with the result of the self-manufactured material. The means of the standards were 0.840 to 1.318 for S1, 0.204 to 0.401 for S2, 0.054 to 0.131 for S3, and 0.008 to 0.046 for S4. The ranges of the standard curve were 0.808 to 0.979 for slope, –0.383 to 0.642 for intercept, and 0.986 to 1.008 for r. The overall quality control results with OD of standard material were acceptable and correlated to the results of self-manufactured material, so we suggest that the substitution from the current quality control method to this number-based method could solve the manufacturing difficulty. It will be more delicate and accurate quality control if we apply the allowable range verified on its own.

Non-destructive quality assessment of herbal tea blends using hyperspectral imaging

The consumption of herbal teas is increasing as consumers become more appreciative of the health benefits. Herbal tea blends comprise of two or more plant species blended to improve taste and multiply the health benefits. Quality control (QC) of herbal teas like other nutraceuticals, is important to ensure safety and efficacy. Current QC methods are chromatography-based and require destructive sample preparation using solvents. In this study, hyperspectral imaging is applied as a fast and non-destructive method for the quality control of herbal tea blends. The technique combines conventional spectroscopy and digital imaging to gather chemical information and visualise spatial distribution of chemical constituents within a matrix. Certified raw materials (Sceletium tortuosum and Cyclopia genistoides) and herbal tea blends were acquired from Parceval Pty (Ltd). Hyperspectral images of the raw material and tea blends were captured on a SisuChema® SWIR (short wave infrared) hyperspectral pushbroom imaging system using ChemaDAQ® software. The images were analysed using Evince® multivariate analysis software 2.4.0. Principal component analysis (PCA) revealed 54.2% chemical variation between S. tortuosum and C. genistoides raw materials. A partial least squares-discriminant analysis (PLS-DA) model with predictive ability of 95.8% was developed. Based on pixel classification, it was possible to visualise the tea blend constituents as S. tortuosum and C. genistoides and quantitatively predict C. genistoides as the major constituent (>97%) while S. tortuosum was present in lower amounts (<3%). The predictions confirm that HSI is a potentially favourable visual tool for the quality assessment of herbal tea blends. However, due to low instrument sensitivity quantitative determinations showed some deviation from the company formulation.

Precision scan-imaging for paperboard quality inspection utilizing X-ray fluorescence

Paperboard is typically made up of a core of cellulose fibers [C6H10O5] and a coating layer of [CaCO3]. The uniformity of these layers is a critical parameter for the printing quality. Current quality control methods include chemistry based visual inspection methods as well as X-ray based methods to measure the coating thickness. In this work we combine the X-ray fluorescence signals from the Ca atoms (3.7 keV) in the coating and from a Cu target (8.0 keV) placed behind the paper to simultaneously measure both the coating and the fibers. Cu was selected as the target material since its fluorescence signal is well separated from the Ca signal while its fluorescence's still are absorbed sufficiently in the paper. A laboratory scale setup is built using stepper motors, a silicon drift detector based spectrometer and a collimated X-ray beam. The spectroscopic image is retrieved by scanning the paperboard surface and registering the fluorescence signals from Ca and Cu. The exposure time for this type of setups can be significantly improved by implementing spectroscopic imaging sensors. The material contents in the layers can then be retrieved from the absolute and relative intensities of these two signals.

Biomonitoring for traditional herbal medicinal products using DNA metabarcoding and single molecule, real-time sequencing

Global concerns have been paid to the potential hazard of traditional herbal medicinal products (THMPs). Substandard and counterfeit THMPs, including traditional Chinese patent medicine, health foods, dietary supplements, etc. are potential threats to public health. Recent marketplace studies using DNA barcoding have determined that the current quality control methods are not sufficient for ensuring the presence of authentic herbal ingredients and detection of contaminants/adulterants. An efficient biomonitoring method for THMPs is of great needed. Herein, metabarcoding and single-molecule, real-time (SMRT) sequencing were used to detect the multiple ingredients in Jiuwei Qianghuo Wan (JWQHW), a classical herbal prescription widely used in China for the last 800 years. Reference experimental mixtures and commercial JWQHW products from the marketplace were used to confirm the method. Successful SMRT sequencing results recovered 5416 and 4342 circular-consensus sequencing (CCS) reads belonging to the ITS2 and psbA-trnH regions. The results suggest that with the combination of metabarcoding and SMRT sequencing, it is repeatable, reliable, and sensitive enough to detect species in the THMPs, and the error in SMRT sequencing did not affect the ability to identify multiple prescribed species and several adulterants/contaminants. It has the potential for becoming a valuable tool for the biomonitoring of multi-ingredient THMPs.

Simultaneous Determination of 11 High-Polarity Components from Fructus Corni: A Quantitative LC-MS/MS Method for Improved Quality Control.

Fructus Corni, the dried ripe sarcocarp of Cornus officinalis Sieb.et Zucc (Cornaceae), is widely used in traditional medicine. Pharmacological studies to date have attributed many biological effects to the high-polarity components. However, current quality control methods focus on only several iridoid glycoside components, and, of note, there is no comprehensive method available to simultaneously quantify the high-polarity components in Fructus Corni. Here, a simple, sensitive and robust liquid chromatography-electrospray ionization-tandem mass spectrometry method was developed to simultaneously determine 11 high-polarity constituents (5-hydroxymethyl-2-furfural, gallic acid, sweroside, cornin, loganin, morroniside, 7α-O-methylmorroniside, 7β-O-methylmorroniside, 7α-O-ethylmorroniside and 7β-O-ethylmorroniside, cornuside) of Fructus Corni. This method showed good specificity, linearity (r2 ≥ 0.9907), repeatability (RSD < 5.98%) and recovery (93.24 ~ 112.92%, RSD < 9.06%). This validated method was successfully employed to assess the component variation of crude Fructus Corni of three regional origins as well as after processing. In particular, the iridoid isomers were, for the first time, included as the quality markers for Fructus Corni. We propose that this method may provide a new and powerful tool for achieving comprehensive quality control of Fructus Corni.