In-process Quality Control Research Articles

Point-of-care manufacturing of anti-CD19 CAR-T cells using a closed production platform: Experiences of an academic in Thailand

Anti-CD19 chimeric antigen receptor (CAR)-T cell therapy has evolved as a standard of care for various forms of relapsed/refractory B cell malignancies in major developed countries. However, access to industry-driven CAR-T cell therapy is limited in developing countries, partly due to the centralized manufacturing system. Here, we demonstrated the feasibility of the point-of-care (POC) manufacturing of anti-CD19 CAR-T cells from heavily pretreated patients and healthy graft donors at an academic medical center in Thailand using a closed semi-automated production platform, CliniMACS Prodigy, and established in-process quality control and release testing to ensure their identity, purity, sterility, safety, and potency. Nine out of the nine products manufactured were used in a pilot study (ISRCTN17901467). However, we did observe that starting Tcells with CD4/CD8 ratios of less than one-third had a high chance of manufacturing failure, which could be minimized by serum supplementation. Further analysis of Tcell phenotypes in the infused versus circulating CAR-T cells revealed the differentiation from early memory subtypes toward effector cells invivo. The POC manufacturing and quality control settings herein could be applied to other CAR-T cell products and may benefit other academics, especially those in developing countries, making CAR-T cells more accessible.

Use of a structure-borne sound-based in-process sensor system to identify Weld seam irregularities during electron beam welding

In this publication, an in-process quality assurance method for electron beam welding based on a structure-borne sound emission test for the detection of weld irregularities arising in the process is presented. For this purpose, different sheet materials, i.e., AISI 304, AZ31 and AlMg3, were welded in a butt-joint and the resulting process noises were recorded by means of two acoustic emission sensors specifically designed for structure-borne sound. During the welding experiments, typical irregularities, e.g. incidence points, pore lines and cracks, were deliberately induced. Subsequently, the recorded acoustic signals were examined with regard to defect-specific abnormalities. Various methods in the time and frequency domain as well as pre-trained machine learning models were used to analyze the acoustic emission data. The results show that the investigated irregularities can be identified and distinguished from other process emissions, eventually enabling a robust means of identification for weld seam irregularities and, thus, opening pathways towards cost-effective in-process quality control.

The Impact of Quality Control Implementation on Productivity and Product Quality in Industry

Furniture production is one of the activities that has the potential to generate income for educational institutions. The furniture production process is generally carried out by experienced students utilizing industry-standard facilities, namely the Wood Construction workshop along with its machinery equipment. Therefore, the implementation of Quality Control in the production process is necessary. This study aims to determine the impact of Quality Control implementation on improving the productivity and quality of furniture products. The method used is quantitative with 4 stages of Quality Control, including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC). Productivity measurement is divided into 3 parts: partial productivity, total factor productivity, and total productivity, which includes labor productivity, time, and production output. Meanwhile, product quality measurement is obtained from assessments by practitioners and product quality testing according to ISO 19682. Data is processed using the path analysis method with the help of a smart PLS application. The research results show that the productivity of production output is 87.5%, categorized as good, with labor productivity of 0.125 pieces/person/day and work hour productivity of 0.25 pieces/hour/day. Product quality based on production processes is categorized as good at 83%. Meanwhile, product quality testing, including visual aspects is good (82.3%), product stability (normal), strength (normal), durability (normal), stiffness (normal 34mm/m), and drop test (normal). Based on path analysis, it is known that quality control including product design, process planning, Incoming Quality Control (IQC), and In-Process Quality Control (IPQC) has an impact on improving the productivity and quality of furniture products. the quality control carried out to increase productivity and product quality can be said to be good with the validation of the final result of 0.188 including in the good category.

Drug Release and Stability Study of Innovated Losartan Potassium and Rosuvastatin Calcium Fixed-dose Combination Tablet.

Patient adherence to therapy and compliance is always a challenge for care providers in the management of chronic disorders with multiple medications. Our study focused on formulating concurrently prescribed ARB (Angiotensin Receptor Blocker), i.e., losartan potassium, and a cholesterol-lowering statin derivative, i.e., rosuvastatin calcium, in a fixed-dose combination tablet. The drugs were selected based on the presence of synergism and variation in solubility characteristics. Trial batches with fixed concentrations of both active pharmaceutical ingredients (APIs) and varying quantities of different excipients were prepared by dry granulation technique and subjected to different quality control tests for tablets. Batch F5 was selected on the basis of in-process quality control data for the development of a drug release protocol. Experimental conditions were optimized. Based on the sink condition, phosphate buffer (pH 6.8) was selected as the dissolution medium. Simultaneous determination of both APIs in samples collected at predetermined time intervals was carried out using the RP-HPLC technique with acetonitrile, methanol, and water (20:25:55 v/v/v) as mobile phase. Complete dissolution of both APIs in the FDC tablet was achieved in 45 min in 900 mL of the selected medium. The in vitro drug release protocol was validated for accuracy and precision without interference with sample analysis. In this study, a validated, accurate, and robust dissolution testing method was developed for the newly formulated FDC tablet.

Bioanalytical method development and validation for quantification of amivantamab in rat plasma by LC-MS/MS

BackgroundAmivantamab is a monoclonal bispecific anti-EGFR-MET antibody used to treat non-small cell lung cancer. There were no published methods using a liquid chromatographic—tandem mass spectrometric approach to develop and validate a feasible, novel, and thoroughly validated method for quantifying amivantamab in rat plasma.ResultsThe liquid–liquid extraction method was used to extract the analyte from rat plasma. The analyte was separated using acetonitrile–ammonium formate buffer (40:60) as a mobile phase on waters, alliance e-2695 model high-pressure liquid chromatographic system having Agilent eclipse C18, 150 mm × 4.6 mm, 3.5 µm column. The overall runtime was 6 min at a 1.0 ml/min flow rate. The method showed significant sensitivity and acceptable linearity over the 5.00–100.00 ng/ml concentration range. Accuracy was proved by mean percent recovery ranging from 98.03 to 99.99%. The intraday precision coefficient of variation (%) ranged between 0.31 and 5.43. Also, the findings such as Cmax, tmax, AUC0− t, AUC0− ∞, and half-life values of amivantamab showed that the technique was helpful for pharmacokinetic studies.ConclusionsAll the validated parameters were found to be within the acceptable range. The validated method was found to be simple, accurate, precise, and reproducible and hence can be used for the routine analysis of amivantamab, such as in-process quality control by liquid chromatographic—tandem mass spectrometry.

IMPATIENT-qPCR: monitoring SELEX success during in vitro aptamer evolution

SELEX (Systematic Evolution of Ligands by Exponential enrichment) processes aim on the evolution of high-affinity aptamers as binding entities in diagnostics and biosensing. Aptamers can represent game-changers as constituents of diagnostic assays for the management of instantly occurring infectious diseases or other health threats. Without in-process quality control measures SELEX suffers from low overall success rates. We present a quantitative PCR method for fast and easy quantification of aptamers bound to their targets. Simultaneous determination of melting temperatures (Tm) of each SELEX round delivers information on the evolutionary success via the correlation of increasing GC content and Tm alone with a round-wise increase of aptamer affinity to the respective target. Based on nine successful and published previous SELEX processes, in which the evolution/selection of aptamer affinity/specificity was demonstrated, we here show the functionality of the IMPATIENT-qPCR for polyclonal aptamer libraries and resulting individual aptamers. Based on the ease of this new evolution quality control, we hope to introduce it as a valuable tool to accelerate SELEX processes in general.IMPATIENT-qPCR SELEX success monitoring. Selection and evolution of high-affinity aptamers using SELEX technology with direct aptamer evolution monitoring using melting curve shifting analyses to higher Tm by quantitative PCR with fluorescence dye SYBR Green I.Key points• Fast and easy analysis.• Universal applicability shown for a series of real successful projects.Graphical

Abstract 5024: Analytical performance of a genome-wide methylome enrichment platform to detect minimal residual disease from plasma-derived cell-free DNA

Abstract Introduction: Plasma-derived cell-free DNA (cfDNA) can be used to identify cancer signals, including minimal residual disease (MRD), in patients who have undergone curative cancer treatments. The cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) methodology is combined with custom algorithms that leverage differentially methylated regions (DMRs) found in cfDNA to distinguish between cancer and non-cancer signals. This novel non-degradative, tissue-agnostic approach was developed to bypass the limitations of bisulfite-sequencing and tissue-informed methods used in other liquid biopsy technologies. Here we present preliminary analytical performance metrics of an algorithm in development for detecting MRD. Methods: In the genome-wide methylome enrichment platform, plasma-derived cfDNA is subjected to standard library preparation, combined with DNA filler, denatured, and immunoprecipitated using an anti-5-mC antibody. Captured DNA is amplified and sequenced. For this study, a candidate algorithm comprised of differentially methylated regions (DMRs) and 12 cancer types was used to quantify cancer-specific methylation. Control samples from 12 non-cancer donors were used to establish a selected 95% true negative rate threshold. This threshold was used to determine assay sensitivity, which was evaluated using contrived cancer samples intended to mimic low-level circulating tumor DNA (ctDNA) representative of MRD. Samples were contrived by titrating fragmented DNA from three immortalized tumor-derived cell-lines into plasma-derived cfDNA in a titration series targeting <1% ctDNA levels. Cell-lines were of non-small cell lung cancer and head and neck squamous cell carcinoma origin; titration series were replicated for a total of 65 tests. Results: All non-cancer and contrived cancer samples met in-process quality control metrics. This included ≥98.5% methylation specificity and ≥80 million unique molecules. Limit of detection calculations at 95% sensitivity (LoD95) were <0.1%. Conclusions: Tissue-agnostic approaches for detecting cancer signals from plasma have significant benefit, especially in settings where tissue is not accessible for evaluation. However, these tests must have highly sensitive methods of cancer signal detection for clinical applications. Our preliminary analytical data demonstrates the use of a blood-based, tissue- agnostic genome-wide methylome enrichment platform utilizing non-degradative methodology combined with specific algorithms and DMRs for MRD quantification and prognostic prediction, using treatment-naïve plasma samples. Future studies in post-treatment and longitudinal samples are ongoing to evaluate the utility of this genome-wide methylome enrichment platform for cancer management. Citation Format: Shu Yi Shen, Iulia Cirlan, Felicia Vincelli, Ben Brown, Jun Min, Justin Burgener, Junjun Zhang, Yulia Newton, Margaret Gruca, Abel Licon, Jing Zhang, Anne-Renee Hartman, Alan Williams, Hestia Mellert, Daniel D. De Carvalho. Analytical performance of a genome-wide methylome enrichment platform to detect minimal residual disease from plasma-derived cell-free DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5024.

In-process quality control in foot-and-mouth disease vaccine production by detection of viral non-structural proteins using chemiluminescence dot blot assay

Foot-and-mouth disease (FMD) is a contagious viral disease of cloven-footed animals. Immunization with inactivated virus vaccine is effective to control the disease. Six-monthly vaccination regimen in endemic regions has proven to be effective. To enable the differentiation of infected animals from those vaccinated, non-structural proteins (NSPs) are excluded during vaccine production. While the antibodies to structural proteins (SPs) could be observed both in vaccinated and infected animals, NSP antibodies are detectable only in natural infection. Quality control assays that detect NSPs in vaccine antigen preparations, are thus vital in the FMD vaccine manufacturing process. In this study, we designed a chemiluminescence dot blot assay to detect the 3A and 3B NSPs of FMDV. It is sensitive enough to detect up to 20 ng of the NSP, and exhibited specificity as it does not react with the viral SPs. This cost-effective assay holds promise in quality control assessment in FMD vaccine manufacturing.

Online monitoring of local defects in robotic laser additive manufacturing process based on a dynamic mapping strategy and multibranch fusion convolutional neural network

Online monitoring is essential for laser additive manufacturing (AM) to improve in-process quality control. Currently, accurate monitoring of local defects in the laser AM process remains a challenge. This paper proposes a method for predicting local defects in the laser AM process based on a dynamic mapping strategy and the multibranch fusion convolutional neural network (MBFCNN). In-situ sensing of the laser-material interaction zone is achieved using a camera integrated coaxially with the printing system. Experiment-based datasets are constructed, in which the in-process images were sampled and matched to the extracted local defect information based on their temporal-spatial correspondence. A dynamic mapping strategy using a sliding sampling window is introduced to achieve continuous monitoring. Considering the cyclic and layer-by-layer processing principle of laser AM, we propose MBFCNN to map the in-process images to local defect information. A multibranch feature extraction module is designed based on the deposited layers of the target region to be monitored, in which each branch extracts high-dimensional representations from in-process images corresponding to a certain layer. We further introduce an attention mechanism to distinguish the importance of each branch and a feature fusion module to fuse the high-level information. Experimental results and comparison with traditional convolutional neural networks demonstrate the effectiveness of our method.

Integrated deep learning-based online layer-wise surface prediction of additive manufacturing

Additive manufacturing (AM) is growing tremendously through its introduction into various industries over recent years, because of its capability of fabricating objects with complex designs. Despite its great successes, AM still has to deal with its main challenge, which is the quality assurance of the printed object. Although extensive studies have been conducted, there are still several critical gaps facing this technology. Due to layer-wise fabrication, one important aspect of quality assurance is to capture the surface morphology of the layer being printed online, which can help to better understand the process dynamics and greatly benefit the promotion of in-process quality control. Thus, this study developed an integrated deep learning model to achieve online layer-wise surface prediction of AM. The proposed deep learning model integrates the convolution autoencoder for surface representation learning and a long short-term memory (LSTM) network for layer-wise prediction. The proposed method is validated by a real-world case study in a common AM process, fused filament fabrication (FFF). The comparison with the benchmarks demonstrates that the developed method has great potential for online layer-wise prediction in AM.

Emulsification-assisted spectroscopic analysis of black seed oil in alginate beads: method development and validation

This study aimed to develop and validate an ultrasonication-aided UV-Vis spectroscopy method for quantifying black seed oil (BSO) in alginate beads. The method utilized sonication at 10% power rate for 120 seconds to stabilize the emulsion droplet size of 10 mL of the emulsion diluents derived from breaking BSO-alginate beads in phosphate buffer. Absorbance measurements were taken at 400 nm, which was found to be the optimal wavelength for measuring the absorbance of turbid emulsion diluents. The method showed excellent linearity between 0.8 - 5 mg/mL (R2 = 0.9977), with Limit of Detection (LOD) and Limit of Quantification (LOQ) values of 0.082 and 0.249 mg/mL, respectively. The method also exhibited good accuracy and precision, with recovery percentages ranging from 98.02 - 101.9% (RSD = 0.15 - 1.24%) and intra-day/inter-day precision with RSD less than 2%. These findings suggest that the ultrasonication-aided spectroscopy method is a quick, accurate, and precise way to quantify encapsulated oils and could be useful for oils analysis during R&D, In Process Quality Control (IPQC), and Quality Control (QC) tests, as well as in other applications such as industrial manufacturing and academic research.

Failure Mode and Effects Analysis of PCB for Quality Control Process

The aim of this study is to highlight the key elements for optimizing printed circuit board (PCB) fabrication productivity through improving manufacturing process efficiency. Failure mode and effect analysis (FMEA) is a technique used to reduce the percentage of finished goods that are found to be defective during the manufacturing process and final inspection, resulting in low rejection ratios and optimized PCB design. This paper presents all the quality steps to achieve high efficiency in PCB design. The study is done in electronics manufacturing industry in which its production begins from receiving PCBs, raw material then bringing them into punching and assembly processes through surface mount machines (SMT). To find defective items and lower the possibility of defective final products, or IPQC (in-process quality control), is used. The average of customer manufacturers lot reject rate (%LRR of CMs) has been improved by using improved quality control. For assessing the risk connected to probable issues discovered during a failure mode and effects analysis, the risk priority number (RPN) methodology technique is applied. The FMEA RPN assists the responsible team or individual in prioritizing risks and choosing the appropriate remedial measures. Lot reject rate (LRR) improved by FMEA is from 5500 parts per million (PPM) to 900 parts per million (PPM), and faults have decreased by 0.76% as a result of improved quality control.

Predicting laser powder bed fusion defects through in-process monitoring data and machine learning

Industry application of additive manufacturing demands strict in-process quality control procedures and high product quality. Feedback loop control is a reasonable solution and a necessary tool. This paper demonstrated our preliminary work on the laser powder-bed fusion feedback loop: predict local porosity through in-process monitoring images and machine learning. 3D models were rebuilt from in-situ optical tomography monitoring images and post-build X-ray CT images. They were registered to the original CAD. Dataset for machine learning was assembled from those registered 3D models. The trained machine learning model can precisely predict local porosity caused by lack of fusion and keyhole with multi-layer monitoring images. It also indicates the optimal processing window. It is impossible to be sure about the occurrence of defects in a layer based only on the abnormality of a single layer, and vice versa. Defects in a layer can be caused by improper parameters or anomalies in current layer or subsequent layers; defects in one layer can also be eliminated by proper parameters in the following layers. The work laid the basis for the next step feedback loop control of pore defect.

Flexible and high-resolution surface metrology based on stitching interference microscopy

Small optics of 10 mm-scale are widely used in miniature cameras with increasingly sophisticated surface shape. The surface features ranging from low to high frequency need to be measured efficiently for in-process quality control. Wavefront interferometry is applicable with specifically designed null optics for each surface, but not preferred for small optics because the surface radius is approaching the shortest measurable radius limited by the interferometer optics. We present a strategy for flexible surface metrology based on stitching interference microscopy. The full aperture surface is divided into a series of small subapertures with reduced size and slope which are then measurable with a standard interference microscope. The measurement principle is introduced and a method for subaperture design is proposed by checking the subaperture size and slope after coordinate transformation. A simultaneous stitching algorithm is proposed to minimize the overlapping deviations with overlapping points and subaperture configurations determined automatically in a way of alternating optimization. Instrumentation is easy by integrating a multi-axis platform with a commercial interference microscope. Both the lateral and the vertical scales need to be calibrated to give accurate subaperture measurement of three coordinates. The capability of the instrument is finally verified through a series of experiments compared with cross tests such as the null test and the stylus profilometry. It shows high flexibility to measure a variety of complex surfaces including the high-order even asphere, the “gull-wing” surface and microstructured curved surfaces without using any auxiliary null optics. The instrument enables “one-stop” measurement of surface form, waviness and roughness simultaneously.

Synergising stoichiometric modelling with artificial neural networks to predict antibody glycosylation patterns in Chinese hamster ovary cells

In-process quality control of biotherapeutics, such as monoclonal antibodies, requires computationally efficient process models that use readily measured process variables to compute product quality. Existing kinetic cell culture models can effectively describe the underlying mechanisms but require considerable development and parameterisation effort. Stoichiometric models, on the other hand, provide a generic, parameter-free means for describing metabolic behaviour but do not extend to product quality prediction. We have overcome this limitation by integrating a stoichiometric model of Chinese hamster ovary (CHO) cell metabolism with an artificial neural network that uses the fluxes of nucleotide sugar donor synthesis to compute the profile of Fc N-glycosylation, a critical quality attribute of antibody therapeutics. We demonstrate that this hybrid framework accurately computes glycan distribution profiles using a set of easy-to-obtain experimental data, thus providing a platform for process control applications.

Processing and Ex Vivo Expansion of Adipose Tissue-Derived Mesenchymal Stem/Stromal Cells for the Development of an Advanced Therapy Medicinal Product for use in Humans

Adipose tissue (AT) represents a commonly used source of mesenchymal stem/stromal cells (MSCs) whose proregenerative potential has been widely investigated in multiple clinical trials worldwide. However, the standardization of the manufacturing process of MSC-based cell therapy medicinal products in compliance with the requirements of the local authorities is obligatory and will allow us to obtain the necessary permits for product administration according to its intended use. Within the research phase (RD), we optimized the protocols used for the processing and ex vivo expansion of AT-derived MSCs (AT-MSCs) for the development of an Advanced Therapy Medicinal Product (ATMP) for use in humans. Critical process parameters (including, e.g., the concentration of enzyme used for AT digestion, cell culture conditions) were identified and examined to ensure the high quality of the final product containing AT-MSCs. We confirmed the identity of isolated AT-MSCs as MSCs and their trilineage differentiation potential according to the International Society for Cellular Therapy (ISCT) recommendations. Based on the conducted experiments, in-process quality control (QC) parameters and acceptance criteria were defined for the manufacturing of hospital exemption ATMP (HE-ATMP). Finally, we conducted a validation of the manufacturing process in a GMP facility. In the current study, we presented a process approach leading to the optimization of processing and the ex vivo expansion of AT-MSCs for the development of ATMP for use in humans.

Type of patients seeking Homeopathic treatment under different physico-cultural background in and around Kolkata - India.

Background: The concept of health and Health Care began in India in the middle of 18th Century. National Health Policy 2002 initiated the program – “health for all”. Earlier it was a concept of individual care. New philosophy of Heath Care Service is inter-sector, i.e., indigenous system can be found in public as well as private sector and so on. The sectors of heath care services in India are categorized as: 1.Public sector 2. Private sector 3. Indigenous systems of medicine which include a. Ayurveda and Siddha b. Unani and Tibbiya c. Homeopathy d. unregistered practitioners 4. Voluntary Heath Agencies 5. National Health Programmes. It needs to clarify who is a patient, according to World Health Organization (1948) defined health as a “state of complete physical, mental and social well-being and not merely the absence of disease or infirmity.” So a person is called healthy if he / she is physically fit, mentally sound and socially well adjusted. To explain further disease is the interruption or break in the state of equilibrium of all the components. Moreover, disease is lack of health, a disorder or illness caused by infection or deficiency with some characteristics or symptoms. The homeopathic doctors look into patient’s symptoms and take the medical history.
 Objective: The objectives of the study are to find out (i) Disease specificity in homeopathic treatment (ii) Variation of diseases with seasons (iii)Variation of diseases with economic condition (iv) Variation in different socio-economic groups seeking homeopathic treatment (v) Reasons of failure of homeopathic treatment.
 Methodology: Fifty (50) clinics of Kolkata and its suburbs and two (2) years data have been taken into consideration. Statistical methods like ANOVA are applied to find out the diseases related to homeopathy. Patients were classified according to their acute and chronic diseases. Acute diseases include seasonal ones like influenza, cough and cold, dengue, malaria, pox, common fever, diarrhea. Chronic diseases include arthritis, hepatic disorder, eczema, cardiac disorders, migraine, asthma, autism, epilepsy, tumors, skin diseases, pimples. Number of each chronic and acute cases in each clinic was recorded. All the numbers in 50 clinics were pooled together for each case. Socio – economic conditions of the patients were also recorded.
 Result: Acute diseases like influenza, diarrhea, common cold, fever dominate over other diseases. Among the chronic diseases rheumatoid arthritis, migraine and asthma are more common than other diseases. Common cold and asthma predominate during autumn while diarrhea is common in monsoon. 
 Discussion: Present paper tries to find out how unhealthy condition or disease is guided by two factors. 1. The climatic condition or the seasonal swing and 2. Economic condition of the patients surveyed. To specify, the paper seeks the variation of disease with seasonal swing and economic status of those who come to the homeopaths. The number of patients also varies with seasons. The number rises during monsoons (July to September) and falls in cold months (December and January). The upper socio-economic group seeks medical help for diseases like coronary heart disease, diabetes, obesity etc., where as lower income goes for diseases like bronchitis, gastroenteritis, diarrhea, etc. The paper also tries to find out the causes failure of homeopathic treatment in the study area, they are (i) limited number of skilled doctors available in suburbs of Kolkata. In urban areas skilled doctors cannot cope with the growing number of patients. (ii) The improper selection of medicines among the trained doctors, moreover, application of proper potencies often fails. (iii) The poor quality of medicines is a major factor of failure. In homeopathy quality control is difficult. In-process quality control is only possible by engaging a large number of inspectors by the Drug Regulator. At present the number is insufficient. (iv) As the patients have little knowledge or ignorant about the homeopathic medicines, they compare homeopathic medicines with other systems of medicine. Only 3% natural substance present in the medicine which cannot be possible to detect by the patient. As the patients cannot smell the medicine and all medicines appear similar for which they often doubt about it’s effects. 
 Conclusion: The causes for seeking homeopathic treatment are different in different socio-economic groups. The lower socio economic groups are attracted due to the low cost of treatment. The higher socio economic groups are interested because of long lasting effects and permanent cure, no side effect, diagnostic problems due to complexity of diseases and to avoid surgery.

Antioxidant HPTLC-DPPH Fingerprinting of Honeys and Tracking of Antioxidant Constituents Upon Thermal Exposure.

The use of High-Performance Thin-Layer Chromatography (HPTLC) coupled with the use of DPPH* (2,2-diphenyl-1-picrylhydrazyl) as a derivatisation reagent is a novel approach to the analysis of antioxidant activity of honeys. The method facilitates the visualisation of individual constituents that contribute to the overall antioxidant activity of the honey, even if they are not yet chemically identified, and allows for the quantification of their antioxidant activity as gallic acid equivalents. The method supports a more in-depth study of the antioxidant activity of honey as it allows for a comparative analysis of the antioxidant fingerprints of honeys of different floral origin and is able to capture differences in their individual bioactive constituents. Further, it supports the tracking of changes in antioxidant activity of individual honey constituents over time upon exposure to different temperature conditions, which demonstrates the potential value of the method for in-process quality control.

Meniscus-confined electrodeposition of metallic microstructures with in-process monitoring of surface qualities

Meniscus-confined electrodeposition is a potential approach to fabricate three-dimensional (3D) metallic microstructures. However, the quality of the deposited microstructures by this approach, which is conventionally checked by a scanning electron microscope (SEM) used off-process, cannot be well in-process qualified. This paper presents a study on meniscus-confined electrodeposition of metallic microstructures with in-process monitoring of deposition qualities. Firstly, to understand the fabrication mechanism in meniscus-confined electrodeposition which formed the fundamental for quality control, mathematical model was derived to study the geometric shape of the meniscus. Multi-physical field simulation was carried out to investigate the effect of several process parameters on the deposition results, including the micropipette aperture, biased voltage and solution concentration, etc. Meniscus-confined electrodeposition of metallic micro-wires by utilizing a micropipette was carried out. The ionic current during the electrodeposition is in-process monitored for contact point detection and fabrication quality monitoring. The corresponding relationship between the quality of the fabricated micro-wires and the in-process monitored ionic currents was investigated. This study provides a potential way for in-process quality control with the local electrodeposition method.

Novel Simultaneous Identification of Capsaicin and It’s Quantification in Transferosome Formulation By HP-TLC Technique

Introduction: Capsaicin (8-methy-N-vanillyl-6-nonenamide), a potential analgesic derived from Capsicum annuum (Chili peppers), widely used from ancient times for its pharmacological activities such as anti-inflammatory, anti-oxidant and analgesic and provides relief from migraine and diabetes. But for obvious reasons, capsaicin cannot be administered directly. The present work was designed with a focus to comply with mandatory requirement in various pharmacopeias to know the actual content of API present in final formulations. The formulation (TS3) consisting of 3% lipid, with 4:6 ratio of the polymer and solvent, was found to be the optimized formulation, which gave the best evaluation with regard to the particle size (97.03±2.68) nm, polydispersity index (0.20±0.00), higher zeta potential (61.28±2.06) mv, morphological studies and highest drug entrapment efficiency (68.34±4.24)%. The prepared transferosome formulation was subjected to characterization by validated HP-TLC method consisting of N-Hexane: Tert- Iso-butyl-methyl ether in ratio (5:15) v/v. Linearity was performed in the range of 50-1500 ng/spot with LOD/LOQ 50 ng and 150 ng, with regression analysis (R) of 99.91%. Recovery analysis was performed at 3 different levels at 80, 100 and 120 with an average recovery of 106.97%, respectively. Till now, no analytical method has been reported, associated with the characterization of pharmaceutical nano-forms (Capsaicin), like transferosomes. Thus, the maiden validated HP-TLC method for concurrent analysis of capsaicin as API in nano-transferosome may be employed in process quality control of formulations containing the said API. Background: The irritability and adverse effects post application, leading to inflammation and neural pain at the site of administration of newly Capsaicin API and its chemical entities and marketed formulations are usually related to poor permeability, leading to drug complex reactions in the development phases or therapeutic failure along with the quantification of the same in blood plasma. However, advancement in drug formulations with the use of polymer: alcohol ratio and modernized analytical techniques for the quantification of Pharmaceutical APIs seems to be emerging and promising for overcoming pain and related inflammatory complications by formulating the APIs in Transferosome formulation with Validated HP-TLC technique being used as an effective economic and precise tool for quantitative analysis of APIs in their respective nano-forms. Objective: The study proposes a novel standardized method development and validation of pharmaceutical nanoforms with Capsaicin as API. Method: Capsaicin Transferosomes were formulated using Ultra probe sonication by utilizing different proportions of phospholipid 90G dissolved in a mixture of ethanol and propylene glycol. The formulation was subjected to Dynamic Light Scattering (DLS) technique for nano-particle analysis followed by characterization with respect to particle size, polydispersity index, zeta potential and entrapment efficiency. The morphological study of vesicles was determined using SEM and TEM. A Validated HP-TLC method for the identification and determination of Capsaicin in transferosomes formulation was performed as per the ICH guidelines. Results: The formulation gave the best evaluation for particle size (97.03±2.68) nm, polydispersity index (0.20±0.00), higher zeta potential (61.28±2.06) mv, morphological studies (SEM & TEM) and highest drug entrapment efficiency (68.34±4.24)%. DSC thermograms and FTIR spectral patterns confirmed no physical interaction by polymers with API. The prepared formulation was then characterized using HP-TLC method. The best resolution was found in NHexane: Tert-Isobutyl methyl ether in a ratio of 5:15 v/v. The Rf was found to be 0.3±0.03. Linearity was performed in a range of 50-1500 ng/spot, with regression analysis (R) of 99.91% Further, recovery analysis was done at 3 different levels as 80, 100 and 120 with an average recovery of 106.97%. The LOD/LOQ was found to be 50 and 150 ng, respectively. Precision was carried out in which % RSD was found to be precise and accurate. Conclusion: The outcomes of the present study suggested that the proposed novel formulation analyzed by Validated planar chromatographic technique (HP-TLC) for Capsaicin quantification in nanoforms may be employed as a routine quality control method for the said API in various other formulations.