Analytical quality by design based on knowledge organization: A case study of developing an ultrahigh-performance liquid chromatography method for the detection of phenolic compounds.

INTRODUCTION: Despite numerous successful cases, there are still some challenges in using analytical quality by design (AQbD) for the development of analytical methods. Knowledge organization helps to enhance the objectivity of risk assessment, reduce the number of preliminary exploratory experiments, identify potential critical method parameters (CMPs) and their scope. OBJECTIVE: In the present study, we aimed to develop a simple, rapid, and robust analytical method for detecting phenolic compounds in Xiaochaihu capsule intermediates utilizing knowledge organization. METHODS: Knowledge organization and AQbD were combined to obtain the initial analytical conditions through knowledge collection, extraction, reorganization, and analysis. The quantitative relationship between critical method attributes (CMAs) and CMPs was then established by a definitive screening design. The method operable design region was calculated using an exhaustive Monte Carlo approach based on the probability of reaching the standard. Robustness investigation and methodological validation were finally performed. RESULTS: Analytical target profiles, CMAs, potential CMPs, and initial analytical conditions were initially identified, and the optimized ranges of operating parameters were obtained. A UHPLC method was successfully established for the analysis of phenolic compounds in ginger-ginger pinellia percolate, and the method validation outcomes were also satisfactory. CONCLUSION: The developed method can be a reliable means to detect the phenolic compounds of Xiaochaihu capsule intermediates. Knowledge organization provides a new approach for making better use of prior knowledge, significantly enhancing the efficiency of analytical method development. The approach is versatile and can be similarly applied to the development of other methods.

Enhancing real-time cell culture monitoring: Automated Raman model optimization with Taguchi method.

Raman spectroscopy has found widespread usage in monitoring cell culture processes both in research and practical applications. However, commonly, preprocessing methods, spectral regions, and modeling parameters have been chosen based on experience or trial-and-error strategies. These choices can significantly impact the performance of the models. There is an urgent need for a simple, effective, and automated approach to determine a suitable procedure for constructing accurate models. This paper introduces the adoption of a design of experiment (DoE) method to optimize partial least squares models for measuring the concentration of different components in cell culture bioreactors. The experimental implementation utilized the orthogonal test table L25 (56 ). Within this framework, five factors were identified as control variables for the DoE method: the window width of Savitzky-Golay smoothing, the baseline correction method, the order of preprocessing steps, spectral regions, and the number of latent variables. The evaluation method for the model was considered as a factor subject to noise. The optimal combination of levels was determined through the signal-to-noise ratio response table employing Taguchi analysis. The effectiveness of this approach was validated through two cases, involving different cultivation scales, different Raman spectrometers, and different analytical components. The results consistently demonstrated that the proposed approach closely approximated the global optimum, regardless of data set size, predictive components, or the brand of Raman spectrometer. The performance of models recommended by the DoE strategy consistently surpassed those built using raw data, underscoring the reliability of models generated through this approach. When compared to exhaustive all-combination experiments, the DoE approach significantly reduces calculation times, making it highly practical for the implementation of Raman spectroscopy in bioprocess monitoring.

Exploring metabolic responses and pathway changes in CHO-K1 cells under varied aeration conditions and copper supplementations using 1 H NMR-based metabolomics.

The optimization of bioprocess for CHO cell culture involves careful consideration of factors such as nutrient consumption, metabolic byproduct accumulation, cell growth, and monoclonal antibody (mAb) production. Valuable insights can be obtained by understanding cellular physiology to ensure robust and efficient bioprocess. This study aims to improve our understanding of the CHO-K1 cell metabolism using 1 H NMR-based metabolomics. Initially, the variations in culture performance and metabolic profiles under varied aeration conditions and copper supplementations were thoroughly examined. Furthermore, a comprehensive metabolic pathway analysis was performed to assess the impact of these conditions on the implicated pathways. The results revealed substantial alterations in the pyruvate metabolism, histidine metabolism, as well as phenylalanine, tyrosine and tryptophan biosynthesis, which were especially evident in cultures subjected to copper deficiency conditions. Conclusively, significant metabolites governing cell growth and mAb titer were identified through orthogonal partial least square-discriminant analysis (OPLS-DA). Metabolites, including glycerol, alanine, formate, glutamate, phenylalanine, and valine, exhibited strong associations with distinct cell growth phases. Additionally, glycerol, acetate, lactate, formate, glycine, histidine, and aspartate emerged as metabolites influencing cell productivity. This study demonstrates the potential of employing 1 H NMR-based metabolomics technology in bioprocess research. It provides valuable guidance for feed medium development, feeding strategy design, bioprocess parameter adjustments, and ultimately the enhancement of cell proliferation and mAb yield.

An optimization strategy for charged aerosol detection to linearize the detector response in the multicomponent quantitative analysis of Qishen Yiqi dripping pills.

Charged aerosol detection, increasingly recognized for quantifying pharmaceutical compounds with weak ultraviolet absorption, is a universal detection technique for high-performance liquid chromatography (HPLC). Charged aerosol detection shows a non-linear response with increasing analyte concentration over a wide range, limiting its versatility in various analytical applications. In this work, a co-optimization strategy for power function value (PFV) and power laws was proposed and applied to broaden the linear range of the standard curve of saccharides in Qishen Yiqi dripping pills using the HPLC-charged aerosol detection (HPLC-CAD) method. Power function values for all analytes were optimized based on empirical models. Subsequently, the optimum power laws were investigated based on a preferred PFV. Additionally, various regression equations were evaluated to ensure the accuracy and precision of the results. With the optimized PFV and power law, the ordinary least squares model demonstrated a satisfactory fit. The optimal PFVs and power laws expanded the standard curve's linear range by 2.7 times compared to default settings, reducing model uncertainty. This paper presents a vital method for developing a multi-component quantitative HPLC-CAD approach without external data transformation outside the provided software, especially suitable for analytical applications of traditional Chinese medicine with significant quality differences.

Development of an in-line Raman analytical method for commercial-scale CHO cell culture process monitoring: Influence of measurement channels and batch number on model performance.

The mammalian cell culture process is a key step in commercial therapeutic protein production and needs to be monitored and controlled due to its complexity. Raman spectroscopy has been reported for cell culture process monitoring by analysis of many important parameters. However, studies on in-line Raman monitoring of the cell culture process were mainly conducted on small or pilot scale. Developing in-line Raman analytical methods for commercial-scale cell culture process monitoring is more challenging. In this study, an in-line Raman analytical method was developed for monitoring glucose, lactate, and viable cell density (VCD) in the Chinese hamster ovary (CHO) cell culture process during commercial production of biosimilar adalimumab (1500 L). The influence of different Raman measurement channels was considered to determine whether to merge data from different channels for model development. Raman calibration models were developed and optimized, with minimum root mean square error of prediction of 0.22 g L-1 for glucose in the range of 1.66-3.53 g L-1 , 0.08 g L-1 for lactate in the range of 0.15-1.19 g L-1 , 0.31 E6 cells mL-1 for VCD in the range of 0.96-5.68 E6 cells mL-1 on test sets. The developed analytical method can be used for cell culture process monitoring during manufacturing and meets the analytical purpose of this study. Further, the influence of the number of batches used for model calibration on model performance was also studied to determine how many batches are needed basically for method development. The proposed Raman analytical method development strategy and considerations will be useful for monitoring of similar bioprocesses.

Image processing-based online analysis and feedback control system for droplet dripping process.

Droplets find wide application across diverse industries, where maintaining their quality is paramount. Precise control over the substance content within droplets demands non-destructive and online analysis techniques, such as Process Analytical Technology (PAT), often integrated with control strategies. In this context, the present study focuses on the example of controlling droplet quality during the dripping process of pills. Leveraging the dripping and image acquisition systems established in previous research, a novel feedback control system centered on image processing was devised for the quality control of dripping pills. The system was developed and its efficacy was assessed, yielding satisfactory outcomes. The proposed system facilitates real-time monitoring of pill weight through the analysis of droplet images during the dripping process, thereby offering real-time feedback control of pill weight. Importantly, this system holds potential for broader applications beyond the scope of this study.

The effects of E'Jiao on body composition, bone marrow adiposity and skeletal redox status in ovariectomised rats.

Background: Menopause is accompanied by increased oxidative stress, partly contributing to weight gain and bone marrow adiposity. Traditional Chinese medication, E'Jiao, has been demonstrated to reduce excessive bone remodelling during oestrogen deprivation, but its effects on body composition and bone marrow adiposity during menopause remain elusive. Objective: To determine the effects of E'Jiao on body composition, bone marrow adiposity and skeletal redox status in ovariectomised (OVX) rats. Methods: Seven groups of three-month-old female Sprague Dawley rats were established (n=6/group): baseline, sham, OVX control, OVX-treated with low, medium or high-dose E'Jiao (0.26, 0.53, 1.06 g/kg, p.o.) or calcium carbonate (1% in tap water, ad libitum). The supplementation was terminated after 8 weeks. Whole-body composition analysis was performed monthly using dual-energy X-ray absorptiometry. Analysis of bone-marrow adipocyte numbers and skeletal antioxidant activities were performed on the femur. Results: Increased total mass, lean mass, and bone marrow adipocyte number were observed in the OVX control versus the sham group. Low-dose E'Jiao supplementation counteracted these changes. Besides, E'Jiao at all doses increased skeletal catalase and superoxide dismutase activities but lowered glutathione levels in the OVX rats. Skeletal malondialdehyde level was not affected by ovariectomy but was lowered with E'Jiao supplementation. However, peroxisome proliferator-activated receptor gamma protein expression was not affected by ovariectomy or any treatment. Conclusion: E'Jiao, especially at the low dose, prevented body composition changes and bone marrow adiposity due to ovariectomy. These changes could be mediated by the antioxidant actions of E'Jiao. It has the potential to be used among postmenopausal women to avoid adiposity.

QbD-Guided Traditional Chinese Medicine Manufacturing Process: Development and Optimization of Fluid-Bed Granulation and Drying Processes for Xiaochaihu Capsules.

Traditional methods of producing Xiaochaihu (XCH) capsules, a traditional Chinese medicine, are time-consuming, costly, and labor-intensive, which is not conductive to modernizing TCM. To address the challenges, new fluid-bed granulation and drying processes with water as the binder were developed and optimized guided by the principles of Quality by Design (QbD) in this study. Ishikawa diagram was applied to conduct a preliminary risk assessment, followed by 6-factor definitive screening design (DSD) serving as a QbD statistical tool to develop and optimize the new processes. Multiple potential factors and interactions were studied with a small number of experiments using the DSD. This study identified critical process parameters (CPPs), established quadratic regression models to reveal CPP-critical quality attributes (CQAs) connections within the DSD framework, and defined a dependable design space. Processes conducted by parameter combinations in the design space produced qualified granules with production yield and raw material utilization higher than 90% and moisture content lower than 4%. Furthermore, quantitative analysis of baicalin of all the granules ensured qualified contents of active pharmaceutical ingredient. The newly developed processes for XCH capsules, with advantages of shorter time, environmental friendliness, and decreased cost, exemplify the effective application of QbD and design of experiments (DoE) methodologies in the modernization of TCM manufacturing processes.

In-Line Detection of Bed Fluidity in Gas-Solid Fluidized Beds Using Near-Infrared Spectroscopy.

A novel approach was developed to detect bed fluidity in gas-solid fluidized beds using diffuse reflectance near-infrared (NIR) spectroscopy. Because the flow dynamics of gas and solid phases are closely associated with the fluidization state, the fluidization quality can be evaluated through hydrodynamic characterization. In this study, the baseline level of NIR spectra was used to quantify the voidage of the fluidized bed. Two indicators derived from the NIR baseline fluctuation profiles were investigated to characterize bed fluidity, named bubble proportion and skewness. To establish a robust fluidity evaluation method, the relationships between the indicators and bed fluidity were investigated under different conditions firstly, including static bed height and average particle size. Then, a generalized threshold was identified to distinguish poor and good bed fluidity, ensuring that the probability of the α- and ß-errors was less than 15% regardless of material conditions. The results show that both indicators were sensitive to changes in bed fluidity under the investigated conditions. The indicator of skewness was qualified to detect bed fluidity under varied conditions with a robust threshold of 1.20. Furthermore, the developed NIR method was successfully applied to monitor bed fluidity and for early warning of defluidization in a laboratory-scale fluidized bed granulation process.

Pharmaceutical Application of Process Understanding and Optimization Techniques: A Review on the Continuous Twin-Screw Wet Granulation.

Twin-screw wet granulation (TSWG) is a method of continuous pharmaceutical manufacturing and a potential alternative method to batch granulation processes. It has attracted more and more interest nowadays due to its high efficiency, robustness, and applications. To improve both the product quality and process efficiency, the process understanding is critical. This article reviews the recent work in process understanding and optimization for TSWG. Various aspects of the progress in TSWG like process model construction, process monitoring method development, and the strategy of process control for TSWG have been thoroughly analyzed and discussed. The process modeling technique including the empirical model, the mechanistic model, and the hybrid model in the TSWG process are presented to increase the knowledge of the granulation process, and the influence of process parameters involved in granulation process on granule properties by experimental study are highlighted. The study analyzed several process monitoring tools and the associated technologies used to monitor granule attributes. In addition, control strategies based on process analytical technology (PAT) are presented as a reference to enhance product quality and ensure the applicability and capability of continuous manufacturing (CM) processes. Furthermore, this article aims to review the current research progress in an effort to make recommendations for further research in process understanding and development of TSWG.

Application of I-Optimal Design for Modeling and Optimizing the Operational Parameters of Ibuprofen Granules in Continuous Twin-Screw Wet Granulation.

The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) ratio, TSWG feed rate, and numbers of the 30° and 60° mixing elements, on the granule quality in a TSWG process, but it can also provide a prediction of the response to determine the optimum operating conditions. Based on the constraints of the desired granule properties, a design space for the TSWG was determined, and the ranges of the operating parameters were defined. An acceptable degree of prediction was confirmed through validation experiments, demonstrating the reliability and effectiveness of using the I-optimal design method to study the TSWG process. The I-optimal design method can accelerate the screening and optimization of the TSWG process.

Application of the Analytical Procedure Lifecycle Concept to a Quantitative 1H NMR Method for Total Dammarane-Type Saponins.

Dammarane-type saponins (DTSs) exist in various medicinal plants, which are a class of active ingredients with effects on improving myocardial ischemia and immunomodulation. In this study, a quantitative 1H NMR method of total DTSs in herbal medicines was developed based on the analytical procedure lifecycle. In the first stage (analytical procedure design), the Ishikawa diagram and failure mode effects and criticality analysis were used to conduct risk identification and risk ranking. Plackett-Burman design and central composite design were used to screen and optimize critical analytical procedure parameter. Then, the method operable design region was obtained through modeling. In the second stage (analytical procedure performance qualification), the performance of methodological indexes was investigated based on analytical quality by design. As examples of continued procedure performance verification, the method was successfully applied to determine the total DTSs in herbal pharmaceutical preparations and botanical extracts. As a general analytical method to quantify total DTSs in medicinal plants or pharmaceutical preparations, the developed method provides a new quality control strategy for various products containing dammarane-type saponin.

Martynoside rescues 5-fluorouracil-impaired ribosome biogenesis by stabilizing RPL27A.

Martynoside (MAR), a bioactive component in several well-known tonic traditional Chinese herbs, exhibits pro-hematopoietic activity during 5-fluorouracil (5-FU) treatment. However, the molecular target and the mechanism of MAR are poorly understood. Here, by adopting the mRNA display with a library of even-distribution (md-LED) method, we systematically examined MAR-protein interactions in vitro and identified the ribosomal protein L27a (RPL27A) as a key cellular target of MAR. Structural and mutational analysis confirmed the specific interaction between MAR and the exon 4,5-encoded region of RPL27A. MAR attenuated 5-FU-induced cytotoxicity in bone marrow nucleated cells, increased RPL27A protein stability, and reduced the ubiquitination of RPL27A at lys92 (K92) and lys94 (K94). Disruption of MAR binding at key residues of RPL27A completely abolished the MAR-induced stabilization. Furthermore, by integrating label-free quantitative ubiquitination proteomics, transcriptomics, and ribosome function assays, we revealed that MAR restored RPL27A protein levels and thus rescued ribosome biogenesis impaired by 5-FU. Specifically, MAR increased mature ribosomal RNA (rRNA) abundance, prevented ribosomal protein degradation, facilitated ribosome assembly, and maintained nucleolar integrity. Collectively, our findings characterize the target of a component of Chinese medicine, reveal the importance of ribosome biogenesis in hematopoiesis, and open up a new direction for improving hematopoiesis by targeting RPL27A.

Mechanism modeling and application of Salvia miltiorrhiza percolation process.

Percolation is a common extraction method of food processing industry. In this work, taking the percolation extraction of salvianolic acid B from Salvia miltiorrhiza (Salviae Miltiorrhizae Radix et Rhizoma) as an example, the percolation mechanism model was derived. The volume partition coefficient was calculated according to the impregnation. experiment. The bed layer voidage was measured by single-factor percolation experiment and the internal mass transfer coefficient was calculated by the parameters obtained by fitting the impregnation kinetic model. After screening, the Wilson and Geankoplis, and Koch and Brady formulas were used to calculate the external mass transfer coefficient and the axial diffusion coefficient, respectively. After substituting each parameter into the model, the process of percolation of Salvia miltiorrhiza was predicted, and the coefficient of determination R2 was all greater than 0.94. Sensitivity analysis was used to show that all the parameters studied had a significant impact on the prediction effect. Based on the model, the design space including the range of raw material properties and process parameters was established and successfully verified. At the same time, the model was applied to the quantitative extraction and endpoint prediction of the percolation process.

1 H NMR-based process understanding and biochemical marker identification methodology for monitoring CHO cell culture process during commercial-scale manufacturing.

Controlling the process of CHO cell fed-batch culture is critical for biologics quality control. However, the biological complexity of cells has hampered the reliable process understanding for industrial manufacturing. In this study, a workflow was developed for the consistency monitoring and biochemical marker identification of the commercial-scale CHO cell culture process through 1 H NMR assisted with multivariate data analysis (MVDA). Firstly, a total of 63 metabolites were identified in this study object in 1 H NMR spectra of the CHO cell-free supernatants. Secondly, multivariate statistical process control (MSPC) charts were used to evaluate process consistency. According to MSPC charts, the batch-to-batch quality consistency was high, indicating the CHO cell culture process at the commercial scale was well-controlled and stable. Then, the biochemical marker identification was provided through orthogonal partial least square discriminant analysis (OPLS-DA) based S-line plots during the cell logarithmic expansion, stable growth, and decline phases. Identified biochemical markers of the three cell growth phases were as follows: L-glutamine, pyroglutamic acid, 4-hydroxyproline, choline, glucose, lactate, alanine, and proline were of the logarithmic growth phase; isoleucine, leucine, valine, acetate, and alanine were of the stable growth phase; acetate, glycine, glycerin, and gluconic acid were of the cell decline phase. Additional potential metabolic pathways that might influence the cell culture phase transitions were demonstrated. The workflow proposed in this study demonstrates that the combination of MVDA tools and 1 H NMR technology is highly appealing to the research of the biomanufacturing process, and applies well to provide guidance in future work on consistency evaluation and biochemical marker monitoring of the production of other biologics.

[Data mining in traditional Chinese medicine product quality review].

The traditional Chinese medicine(TCM) enterprises have accumulated a large amount of product quality review(PQR) data. Mining these data can reveal the hidden knowledge in production and helps improve pharmaceutical manufacturing technology. However, there are few studies involving the mining of PQR data and thus enterprises lack the guidance to analyze the data. This study proposed a method to mine the PQR data, which consisted of 4 functional modules: data collection and preprocessing, risk classification of variables, risk evaluation by batches, and the regression analysis of quality. Further, we carried out a case study of the formulation process of a TCM product to illustrate the method. In the case study, the data of 398 batches of products during 2019-2021 were collected, which contained 65 process variables. The risks of variables were classified according to the process performance index. The risk of each batch was analyzed through short-term and long-term evaluation, and the critical variables with the strongest impact on the product quality were identified by partial least square regression. The results showed that 1 variable and 13 batches were of high risk, and the critical process variable was the quality of the intermediates. The proposed method enables enterprises to comprehensively mine the PQR data and helps to enhance the process understanding and improve the quality control.

Real-time quality control of dripping pill's weight based on laser detection technology.

The present work reports developing the first process analytical technology (PAT)-based real-time feedback control system for maintaining the Ginkgo biloba leaf dripping pills weight during manufacturing. The opening degree of the drop valve and the weight of dripping pills were chosen as the manipulated variable and as the controlled variable, respectively. A proportional-integral controller was programmed to automatically reach the desired dripping pills weight by adjusting the opening degree of the drop valve. The closed-loop feedback control system could automatically compensate for the disturbances and ensure a predefined weight of the dripping pills with excellent robustness, high accuracy, and high efficiency during manufacturing. Furthermore, the closed-loop feedback control system improved the process capability of the dripping process, and the process capability index was > 1.67. This study provides a new approach to real-time control of the weight of dripping pills and improves the process capability during Ginkgo biloba leaf dripping pills manufacturing.

Effects of E'Jiao on Skeletal Mineralisation, Osteocyte and WNT Signalling Inhibitors in Ovariectomised Rats.

E'Jiao is a traditional Chinese medicine derived from donkey skin. E'Jiao is reported to suppress elevated bone remodelling in ovariectomised rats but its mechanism of action is not known. To bridge this research gap, the current study aims to investigate the effects of E'Jiao on skeletal mineralisation, osteocyte and WNT signalling inhibitors in ovariectomised rats. Female Sprague-Dawley rats (3 months old) were ovariectomised and supplemented with E'Jiao at 0.26 g/kg, 0.53 g/kg and 1.06 g/kg, or 1% calcium carbonate (w/v) in drinking water. The rats were euthanised after two months of supplementation and their bones were collected for Fourier-transform infrared spectroscopy, histomorphometry and protein analysis. Neither ovariectomy nor treatment affected the skeletal mineral/matrix ratio, osteocyte number, empty lacunar number, and Dickkopf-1 and sclerostin protein levels (p > 0.05). Rats treated with calcium carbonate had a higher Dickkopf-1 level than baseline (p = 0.002) and E'Jiao at 0.53 g/kg (p = 0.002). In conclusion, E'Jiao has no significant effect on skeletal mineralisation, osteocyte and WNT signalling inhibitors in ovariectomised rats. The skeletal effect of E'Jiao might not be mediated through osteocytes.

A multivariate curve resolution-alternating least squares (MCR-ALS) technology assisted 1 H-NMR methodology for multi-component quantitation of Trichosanthis Pericarpium injection.

INTRODUCTION: Trichosanthis Pericarpium injection (TPI) is a traditional Chinese medicine preparation obtained from Trichosanthis Pericarpium by extraction, purification and sterilisation. It contains amino acids, alkaloids, nucleotides and other components. Existing quantitative methods only analyse a few components in injections, so this study intends to develop a method for comprehensive analysis of TPI components. OBJECTIVE: To develop a method for quantification of components in TPI by multivariate curve resolution-alternating least squares (MCR-ALS) assisted proton nuclear magnetic resonance (1 H-NMR). METHODS: A 1 H-NMR method was developed for the quantification of components in TPI. For components with independent signals, 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid sodium salt (TSP) was used as an internal standard to calculate the component contents. For components with overlapping signals, the method of MCR-ALS was used. RESULTS: A total of 36 components were identified in TPI, of which 33 were quantified. Methodological validation results showed that the developed 1 H-NMR method has good linearity, accuracy, precision, robustness and specificity. CONCLUSION: The use of 1 H-NMR provides a reliable and universal method for the TPI components identification and quantification. Also, it can be used as a powerful tool for analysing the contents in a complex mixture as a quality control measure.

Mechanosynthesis of magnolol multicomponent crystalline solids for improved natural antibiotics and customizable release profiles.

Antibiotic is one of the most important discoveries in human and animal medicine. However, the inefficient use of antibiotics has caused widespread and persistent contamination of ecosystems, setting off microbial resistance storms. Magnolol is a botanical antibiotic, but poor physicochemical properties result in low bioavailability. Increasing solubility of magnolol can help to reduce the doses of medications to patients, minimize bothersome side effects. In this work, three novel multicomponent crystalline solids were synthesized from magnolol and isomeric coformers by mechanochemistry. It was found that the multicomponent crystalline solids achieved the customizable release profile of magnolol by manipulating the substituent positions of the isomers and complexation. Antibacterial activity test showed that bioactivity on two bacteria was considerably improved by designed MGN multicomponent crystals. In addition, the coformers controlled the dissolution behavior and further stabilized the improvement according to the variable statistical analysis. In conclusion, the properties of antibiotic multicomponent solids can be manipulated through the coformers. This provides an effective strategy for managing the release of drugs to meet individual biological differences and diverse therapeutic needs.