Product Quality Specifications Research Articles

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

Evaluasi SPO Pengujian Produk Jadi Pre-Marketing terhadap Mutu Sediaan COL (Cairan Obat Luar) Tradisional di Salah Satu Industri X

Introduction: The traditional medicine industry (TMI) is an industry that can produce all types of traditional medicinal preparations including EML (external medicine liquid). In the process of making traditional medicine (TM), TMI is obliged to follow the rules of GMPTM (good manufacturing practices traditional medicines) which aims to ensure the quality of the preparations produced. In the process, an SOP (standard operating procedure) is needed which contains the steps that must be taken to realize the goals and product quality (specifications) that have been determined. Pre-marketing finished product testing is part of the production process, so it also requires an SOP. One of the IOT X that has made CML has been established long time, of course it already has a Finished Products Pre-Marketing EML Preparations Testing SOP. Objective: to evaluate the SOP of Pre-Marketing Finished Product Testing on the quality of COL preparations, based on quality standards finished products which are regulated in BPOM Regulation No. 32 of 2019 concerning the Safety and Quality Requirements for Traditional Medicine and 1996 SNI (Indonesian National Standard), and GMPTM 2021. Methods: literature study and observational description with a qualitative approach in the form of interviews Results: SOP is in accordance with existing EML quality standards, its implementation has also been implemented well (during the production of COL X products never happened not eligible), and there has never been a recall of EML products during the production period. Conclusion: The SOP for testing finished products in the pre-marketing phase has been implemented properly in accordance with applicable regulations.

Model-Based Approach to Selecting Pegfilgrastim Dose for Pharmacokinetic and Pharmacodynamic Similarity Studies in Biosimilar Development.

This study applied modeling and simulation (M&S) approaches to evaluate the sensitivity of pegfilgrastim pharmacokinetics (PKs) and pharmacodynamics (PDs) to changes in dose amount, and linear or nonlinear clearance (CL) over pegfilgrastim subcutaneous dose of 2-6 mg. A previously published model was adapted to better describe pegfilgrastim PK and PD data in healthy subjects and used in simulation. Nonlinear CL accounts for 98% and 77%, respectively, of the total CL of pegfilgrastim at 2 and 6 mg. The sensitivity analyses showed: (i) PK of 2 and 6 mg doses are similarly sensitive to detect differences for a 5% change in dose; (ii) PK of 2 mg dose is more sensitive to changes in receptor binding affinity, a model parameter for nonlinear CL, and a product quality attribute characterized with orthogonal methods as part of demonstrating analytical similarity between products; (iii) PK of approved 6 mg dose is more sensitive to changes in linear CL, which has not been associated with any specific product quality attributes, and (iv) the PDs are not sensitive to changes in linear or nonlinear CL. Taken together, our analyses support that the approved pegfilgrastim dose of 6 mg is appropriate for detecting differences between a biosimilar and the reference products in pegfilgrastim PK and PD similarity studies. The described M&S approaches can be adopted to support dose selection for biosimilars with nonlinear PK and complex PK-PD interplay.

DoE-assisted development and validation of a stability-indicating HPLC-DAD method for simultaneous determination of five cannabinoids in Cannabis sativa L. based on analytical quality by design (AQbD) concept.

Medical uses of Cannabis sativa L. have gained interest in recent decades, which highlights the need for defining appropriate quality specifications for Cannabis-based products. However, the complexity of plant matrices and structural similarity between cannabinoids make analytical development a challenging task. Thus, the application of analytical quality by design (AQbD)-driven approaches can favour the development of fit-for-purpose methods. To develop a high-performance liquid chromatography diode array detector (HPLC-DAD) method for simultaneous quantification of cannabidiol, Δ9 -tetrahydrocannabinol, cannabidiolic acid, tetrahydrocannabinolic acid, and cannabinol in C. sativa by applying an AQbD-driven approach. Critical method attributes (CMA) were established following the analytical target profile. Critical method variables (CMV) were categorised based on risk assessment and literature review. Selected CMV regarding sample preparation and chromatographic conditions were optimised using response surface methodology (RSM). The working point was estimated by multiple response optimisation using Deringer's desirability function. The validity of the optimal conditions was confirmed experimentally. Method validation was performed according to ANVISA and ICH guidelines. Relative response factors (RRFs) were also determined. Baseline resolution of 12 major cannabinoids was achieved in a 35 min chromatographic analysis. All experimental responses obtained during confirmatory analyses were within the prediction intervals (PI95% ). Method's selectivity, linearity (10-100 μg/mL), precision, bias, extraction recovery, and ruggedness were satisfactorily demonstrated. The application of an AQbD-driven approach allowed for a better understanding of the effects of the ensemble of CMV on the analyte's behaviour, enabling the definition of appropriate conditions to ensure consistent achievement of the intended method's performance.

Simplified strategy for developing purification processes for antibody-drug conjugates using cation-exchange chromatography in flow-through mode

The development of manufacturing processes for antibody-drug conjugates (ADCs) presents many challenges compared to a standard monoclonal antibody. Conjugation processes typically start with an antibody intermediate that was purified to have very low levels of aggregates. The additional processing required for ADCs, including a hydrophobic small molecule and co-solvents, contributes to unacceptable levels of protein aggregate species. A post-conjugation purification step could be necessary to ensure that the process robustly delivers a product that achieves the desired product quality specifications. This paper describes a methodology for developing chromatographic purification steps to remove very high molecular weight species (vHMWS) in ADCs and was applied to three products, decreasing the vHMWS by ≥ 85% to ≤ 0.1%. Leveraging the antibody intermediate purification conditions to streamline development, we efficiently developed robust flow-through cation-exchange chromatography steps for ADC products.

Automated immersion ultrasonic testing technology for debonding defects of the brazed joint of DOME in EAST divertor

Aiming at the problem of non-destructive evaluation of debonding defects on joint interface of DOME in EAST divertor, an automatic water immersion ultrasonic C-scan testing technology based on a six-axis robot is proposed in this research. First, the research and development ideas, principles and control logic of the testing system are explained. Second, testing technologies such as probe selection, reference sensitivity and gate setting, and scanning path planning based on robotic arm teaching technology are introduced in detail. Finally, the testing results of the test blocks and products are presented, and the distribution state and formation reasons of the debonding defects on the bonding surface are analyzed. The results show that the automatic water immersion ultrasonic C-scan inspection system based on the six-axis robot has good adaptability to the surface and high testing sensitivity, which can meet the requirements for product quality and technical specifications. In summary, the proposed technology can realize the non-destructive quantitative assessment of the debonding defects of the brazed joint of DOME.

Identification, Isolation and Characterization of Degradation Products (DPs) in Osimertinib Mesylate (OSM) Tablets by UHPLC-IMS-QTOF-MS, and NMR: Evaluation of Genotoxicity for OSM and DPs

The aim of this study is identification, isolation, structural characterization and qualification of degradation products DP-1, DP-2, DP-3 and DP-4. These impurities are major acid hydrolysis degradation products identified i n Osimertinib M esylate ( OSM) Tablets. T he O SM i s o bserved s table u nder thermal, photolytic and neutral conditions. The degradation of drug is observed under acidic, basic and oxidative conditions. Basic and oxidative degradation products already been reported, however, four novel degradation products are formed in acid hydrolysis which are not reported in the literature. Therefore, Using HPLC/PDA gradient program with waters X-bridge (250 mm × 4.6 mm, 5 µm) C18 column, the four acid hydrolysis degradants were identified and further characterized using UHPLC-IMS-QTOF-MS (ion mobility quadrupole time-of-flight m ass spectrometer) a nd N MR. T he s tructures o f D P-1, D P-2, D P-3 a nd D P-4 w ere further elucidated as hydroxy OSM Impurity, Des-acryl OSM impurity, Chloro OSM impurity and OSM dimer impurity, respectively. The structural characterization was followed by qualification of Impurities DP-1, DP-2, DP-3 and DP-4 using several different in-silico methodologies. From the results obtained, it can be concluded that no new structural alerts have been generated for DP-1 and DP-4 relative to the parent compound OSM. However, the degradation products, DP-2 and DP-3 shows structural alert positive for genotoxicity, which were both potential genotoxic substances. The current study presents separation, isolation, characterization and in-silico toxicity study for major acid degradants of OSM. The OSM generates DP-1 around 3.1%, DP-2 around 14.1%, DP-3 around 18.3% and DP-4 around 2.8% under acid hydrolysis on HPLC. The stress study was carried out in order to properly define the quality specifications for OSM drug products.

A cyber-physical system approach to zero-defect manufacturing in light-gauge steel frame assemblies

Recent advances in manufacturing research have set the stage for the industrial integration of zero-defect manufacturing strategies, aiming towards a more sustainable production paradigm. A systematically deployment guideline to implement zero-defect manufacturing is needed to transform the future cyber-physical factory floor. This paper describes a novel framework based on a well-known cyber-physical architecture that provides advanced information analytics, robust information flows, and data acquisition systems that support defect detection and prediction introduces repair technologies and sets up procedures for preventive maintenance. Through continuous inspection of product and equipment status during the manufacturing process, raw quality and tool health data from different sources is used to obtain key performance indicators. Statistical tools such as cross-correlation are then applied to quantify underlying relationships between product quality specifications and equipment health. The resulting correlations are then used to reduce non-conformance of products manufactured by implementation of preventive maintenance. A unified implementation for zero-defect manufacturing cyber-physical processes eases their integration in future Industry 4.0 facilities and validated in the context of offsite construction manufacturing of steel frame assemblies.

Rapid cGMP manufacturing of COVID-19 monoclonal antibody using stable CHO cell pools.

Therapeutic proteins, including monoclonal antibodies, are typically manufactured using clonally derived, stable host cell lines, since consistent and predictable cell culture performance is highly desirable. However, selecting and preparing banks of stable clones takes considerable time, which inevitably extends overall development timelines for new therapeutics by delaying the start of subsequent activities, such as the scale‐up of manufacturing processes. In the context of the coronavirus disease 2019 (COVID‐19) pandemic, with its intense pressure for accelerated development strategies, we used a novel transposon‐based Leap‐In Transposase® system to rapidly generate high‐titer stable pools and then used them directly for large scale‐manufacturing of an anti‐severe acute respiratory syndrome coronavirus 2 monoclonal antibody under cGMP. We performed the safety testing of our non‐clonal cell bank, then used it to produce material at a 200L‐scale for preclinical safety studies and formulation development work, and thereafter at 2000L scale for supply of material for a Phase 1 clinical trial. Testing demonstrated the comparability of critical product qualities between the two scales and, more importantly, that our final clinical trial product met all pre‐set product quality specifications. The above expediated approach provided clinical trial material within 4.5 months, in comparison to 12–14 months for production of clinical trial material via the conventional approach.

Shrinking-Core Model Integrating to the Fluid-Dynamic Analysis of Fixed-Bed Adsorption Towers for H2S Removal from Natural Gas

Natural gas sweetening is an essential process within hydrocarbon processing operations, enabling compliance with product quality specifications, avoiding corrosion problems, and enabling environmental care. This process aims to remove hydrogen sulfide (H2S), carbon dioxide, or both contaminants. It can be carried out in fixed-bed adsorption towers, where iron oxide-based solid sorbent reacts with the H2S to produce iron sulfides. This study is set out to develop a fluid-dynamic model that allows calculating the pressure drop in the H2S adsorption towers with the novelty to integrate reactivity aspects, through an iron sulfide layer formation on the solid particles’ external skin. As a result of the layer formation, changes in the particle diameter and the bed void fraction of the solid sorbent tend to increase the pressure drop. The shrinking-core model and the H2S adsorption front variation in time support the model development. Experimental data on pressure drop at the laboratory scale and industrial scale allowed validating the proposed model. Moreover, the model estimates the bed replacement frequency, i.e., the time required to saturate the fixed bed, requiring its replacement or regeneration. The model can be used to design and formulate new solid sorbents, analyze adsorption towers already installed, and help maintenance-planning operations.

Dynamic optimization of cryogenic distillation operation for hydrogen isotope separation in fusion power plant

Stable operation of a hydrogen isotope separation system is one of the most important issues in the sustainable operation of fusion power plants. Owing to the present limitation in retention time of fusion reaction, fusion reactors are run in repeated batch operations, causing large fluctuating flows in the system. Hence, to reliably produce required products, counteractive operational strategies must be devised. To this end, we perform dynamic optimization in this paper to derive an optimal control policy that can minimize the tritium inventory and satisfy the product quality specifications. In addition, a rigorous dynamic model for packed columns is developed to simulate realistic behaviors of cryogenic distillation. We demonstrate that the optimization results yield vital operational strategies, such as operation mode switching, without any expertise provided.

Experimental analysis on machining parameters and cooling conditions affecting surface integrity of Ti6Al4V

Machining continues to dominate the market among manufacturing processes requiring in-depth investigation on how material removal processes influence the surface integrity of the products. In this paper, experimental studies were carried out to evaluate the influence of several process parameters on surface integrity changes of Ti6Al4V alloy and to improve the overall process/product performance. In particular, orthogonal cutting operations were conducted varying the process parameters as cutting speed, feed rate and cooling conditions (dry, MQL and cryogenic cooling). Product quality specifications have been monitored in terms of microstructure, hardness modification, phase changes, also including tool wear analysis. Indeed, a systematic study is necessary since various factors are simultaneously involved, as well as changes during processing. Thus, due to the complexity of the process and the number of factors involved, the analysis of variance (ANOVA) was performed to optimize the process through the identification of significant parameters to maximize the useful tool-life and minimize the time of production.

Optimal design and operation of reactive distillation systems based on a superstructure methodology

A novel methodology for the simultaneous optimisation of design and operation of a complex reactive distillation process, considering a number of process alternatives (e.g. pre-/side-reactor, side-stripper, additional columns etc.), is presented. The methodology is based on a superstructure approach, and a detailed cost-based objective function, solved by MINLP optimisation. The methodology is illustrated using different case studies of industrial interest with varying separation and reaction characteristics. For easy separations, in terms of relative volatilities and boiling points order, a single reactive distillation column is found to be optimal for both fast and slower kinetics. However, when the separation is more challenging (i.e. product is a middle-boiler), the design is more complex, even for fast kinetics, and additional processing units, such as a pre-reactor and/or additional distillation columns, are required to meet the product quality specifications. It is found that the design, i.e. the capital cost, mainly depends on the relative boiling point rankings. For operation, chemical reaction equilibrium is the dominant factor. It is demonstrated, however, that the combined effects of separation and reaction must be considered carefully when designing a reactive distillation process. The liquid holdup has an impact on the reaction performance, and proper choice of holdup can lead to a more flexible design, able to mitigate production failure issues even for slower reactions.

Simulation strategy to reduce quality uncertainty in the sugar cane honey process design

This work proposes to increase the acceptability of the sensory quality attributes of sugarcane honey by simulating and decreasing the uncertainty of operational parameters. To this effect, it relies on the development of a case study through a strategy that contemplates the analysis of the initial data and performs calculations through the use of mathematical models, the determination of the Sigma quality level, and the use of the GUM methodology (Guide to the expression of uncertainty in measurement). It was demonstrated that a range with a great variability in the initial operational parameters generated a Sigma level of less than three and a decrease in revenues of 30-52% due to low product sales for the studied productions. By decreasing pH uncertainty from 3,79 to 4,21, and Brix degrees from 75,13 to 76,88, an increase in the Sigma level of quality was observed, which exceeded six, in compliance with product quality specifications, as well as a reduction in economic losses due to defective products. The importance of quality in the product design and the process is evinced, given its influence on the acceptability of the product and the feasibility of the process.

Optimal design of flexible heat-integrated crude oil distillation units using surrogate models

The design of distillation columns often considers a given fixed feedstock and nominal operating conditions. Here we present an optimization-based approach for the optimal design of these units considering a flexible operation under a range of potential feedstocks. Our method combines an artificial neural network with a support vector machine to model the crude oil distillation unit. The artificial neural network model predicts the performance of the distillation unit for a given crude oil feedstock whilst the support vector machine classifier filters out infeasible design alternatives from the solution space (i.e., designs that are unlikely to converge when simulated using a rigorous model). The inputs to the artificial neural network include the column structural variables and operating conditions, whilst the outputs are process variables linked to the column performance. The artificial neural network models and support vector machines constructed for different crude oil feedstocks are integrated into a two-stage optimization framework in order to optimize the column structural variables and operating conditions, where the minimum utility demand is estimated using the pinch analysis. An effective solution strategy that combines stochastic and deterministic optimization algorithms is applied to search for economically viable and flexible design alternatives that can operate over a given range of crude oil feedstocks while satisfying the product quality specifications. The capabilities of the proposed approach are illustrated using an industrially-relevant case study, where we clearly show that the proposed approach can identify design alternatives capable of handling various feedstocks effectively.

Towards a controllability analysis of multiscale systems: Application of the set-theoretic approach to a semi-batch emulsion polymerization process

This work presents a framework to evaluating the controllability of multiscale systems based on a set-theoretic approach. Calculation of the Controllable Trajectories Set is the core of the set-theoretic approach. From a multi-scale perspective, such calculation is a computationally- intractable problem. Therefore, to overcome the intrinsic curse of dimensionality of the problem, Variance Algebra concepts and a statistical modeling approach are combined to obtain a closed-form allowing to perform an output-controllability analysis for a multiscale system. A semi-batch emulsion polymerization process is adopted as a case study. Results have shown that both, the final Particle Size Distribution (mesoscopic variable) and the secondary particle nucleation rate (microscopic variable) are output-controllable. Evaluating the controllability of lower-scale variables (i.e. below macroscopic) could mitigate the dependency of the current control strategies of on-line measurements at the lower scales as well as help to better understand the process capabilities of achieving the desired product quality specifications.

Evaluation of Determinants of Software Quality in Offshored Software Projects

Successful offshoring engagements of Indian software vendors is increasingly dependent upon the quality of the projects delivered rather than cost considerations. However, delivering quality software is reliant on effective management of various organizational, technological and people aspects. This research is to identify and evaluate the determinants of quality on software projects delivered by vendors through offshoring. Data related to recently completed projects were collected through a survey of 440 project managers from Indian vendors. Based on structural equation modeling, the authors analyze the influence determinants on specific product quality attributes. It is found that, out of six determinants, technical infrastructure and process maturity have significant influence on most of the attributes of quality in offshored IS projects from India. The authors provide a set of implications for practice and directions for further research.

Relationship between the geology, soil assessment, and terroir of Gewürtztraminer vineyards: A case study in the Dolomites of northern Italy

The study of the geological identity of rare vineyards introduces new classification approaches for the geological natural environment, which is sometimes underestimated in agriculture. This research examines the geological features related to quaternary soil sediments in the Italian Alps, near the village of Tramin. The local winemakers have constantly encountered differences between vineyards over the decades, such as growth of vines and quality of the grapes and wine, even in Gewürtztraminer vineyards close to each other. A detailed geological territorial study with more precise classification at the vineyard scale would therefore be significant, because it could explain the source of these differences. A new term for this approach, Vineyard Geological Identity (VGI), has been coined. The purpose is to standardize the geological information and enhance scientific comparisons between vineyards, but it is also useful for vintners as they attempt to obtain scientific confirmation for their personal observations or for supporting the territorial subdivision provided by the wine's product quality specification. Our findings show a very marked variability of sediments in the study area and how the more recent geological processes are directly related to their varied chemical and mineralogical distributions. Many dolomitic or silicate soil sediments marked by different history, and therefore with different chemical and physical properties, lie adjacent in a very restricted territory. Some of the analysed vineyards are evidently siliciclastic, whereas others are mostly carbonate. In adjacent vineyards, the content of carbonate mineral can range from 36.3% to 0.6%. A marked alternation of layers with different mineralogy can typify the sediment layers where the grapevine root systems grow. The Mn and dolomitic Mg mean concentration were 1.1 mg/kg and 343 mg/kg, respectively, in strictly siliciclastic layers compared with 6.9 mg/kg and 1081 mg/kg in the more carbonate layers. Several minerals characterize the different sediments, and relations between some of them and the fruit orchard soil reaction classes were found. Further studies should verify direct links with the biochemical processes related to the variable mineral macronutrients observed. A correct geopedological classification and mapping of both the sediments and related soils are essential to eliminate incongruities in the interdisciplinary data.

Integrated ionic liquid and process design involving azeotropic separation processes

In process industries, separation techniques need to be employed to match product quality and purity specifications. Most vapour-liquid based separation techniques involving the separation of close-boiling or azeotropic as well as gaseous mixtures are energy intensive. Downstream separations from bioreactors are, on the other hand, difficult because of relatively small amounts of products in large amounts of reactants and carriers such as water. With growing energy and environmental challenges, novel, sustainable and innovative separation techniques are receiving increasing attention. Because of their non-volatility and other tuneable properties, ionic liquids (ILs) based separation techniques are promising alternatives. In this work, a systematic method that combines group contribution (GC)-based property prediction and IL-based separation process design is presented. That is, the optimal IL molecular structure and the corresponding optimal flowsheet configuration for a specific IL-based separation process are simultaneously identified. Case studies involving the separation of azeotropic mixtures such as ethanol-water and acetone-methanol are presented to highlight the application of the method for synthesis-design of the IL-based separation technology.

Проблемы классификации несоответствий требованиям GMP: регуляторный опыт

The article gives an overview of current regulatory practices for classification of GMP-inspection deficiencies together with analysis of relevant definitions used. Special focus is given to potential mechanisms of classification of deficiencies based on risk-based evaluation of associated product-specific quality defects.