A novel natural Syk inhibitor suppresses IgE-mediated mast cell activation and passive cutaneous anaphylaxis.

Spleen tyrosine kinase (Syk) plays a crucial role as a target for allergy treatment due to its involvement in immunoreceptor signaling. The purpose of this study was to identify natural inhibitors of Syk and assess their effects on the IgE-mediated allergic response in mast cells and ICR mice. A list of eight compounds was selected based on pharmacophore and molecular docking, showing potential inhibitory effects through virtual screening. Among these compounds, sophoraflavanone G (SFG) was found to inhibit Syk activity in an enzymatic assay, with an IC50 value of 2.2 µM. To investigate the conformational dynamics of the SYK-SFG system, we performed molecular dynamics simulations. The stability of the binding between SFG and Syk was evaluated using root mean square deviation (RMSD) and root mean square fluctuation (RMSF). In RBL-2H3 cells, SFG demonstrated a dose-dependent suppression of IgE/BSA-induced mast cell degranulation, with no significant cytotoxicity observed at concentrations below 10.0 µM within 24 h. Furthermore, SFG reduced the production of TNF-α and IL-4 in RBL-2H3 cells. Mechanistic investigations revealed that SFG inhibited downstream signaling proteins, including phospholipase Cγ1 (PLCγ1), as well as mitogen-activated protein kinases (AKT, Erk1/2, p38, and JNK), in mast cells in a dose-dependent manner. Passive cutaneous anaphylaxis (PCA) experiments demonstrated that SFG could reduce ear swelling, mast cell degranulation, and the expression of COX-2 and IL-4. Overall, our findings identify naturally occurring SFG as a direct inhibitor of Syk that effectively suppresses mast cell degranulation both in vitro and in vivo.

Sample Size Requirements of a Pharmaceutical Material Library: A Case in Predicting Direct Compression Tablet Tensile Strength by Latent Variable Modeling.

The material library is an emerging, new data-driven approach for developing pharmaceutical process models. How many materials or samples should be involved in a particular application scenario is unclear, and the impact of sample size on process modeling is worth discussing. In this work, the direct compression process was taken as the research object, and the effects of different sample sizes of material libraries on partial least squares (PLS) modeling in the prediction of tablet tensile strength were investigated. A primary material library comprising 45 materials was built. Then, material subsets containing 5 × i (i = 1, 2, 3, …, 8) materials were sampled from the primary material library. Each subset underwent sampling 1000 times to analyze variations in model fitting performance. Both hierarchical sampling and random sampling were employed and compared, with hierarchical sampling implemented with the help of the tabletability classification index d. For each subset, modeling data were organized, incorporating 18 physical properties and tableting pressure as the independent variables and tablet tensile strength as the dependent variable. A series of chemometric indicators was used to assess model performance and find important materials for model training. It was found that the minimum R2 and RMSE values reached their maximum, and the corresponding values were kept almost unchanged when the sample sizes varied from 20 to 45. When the sample size was smaller than 15, the hierarchical sampling method was more reliable in avoiding low-quality few-shot PLS models than the random sampling method. Two important materials were identified as useful for building an initial material library. Overall, this work demonstrated that as the number of materials increased, the model's reliability improved. It also highlighted the potential for effective few-shot modeling on a small material library by controlling its information richness.

Association between Dietary Acid Load and Hypertension in Chinese Adults: Analysis of the China Health and Nutrition Survey (2009).

(1) Background: Current studies show conflicting results regarding the relationship between dietary acid load (DAL) and blood pressure. (2) Methods: The study used data from the Chinese Health and Nutrition Survey (CHNS) 2009. DAL was assessed on the basis of potential renal acid load (PRAL) and net endogenous acid production (NEAP). To examine the link between DAL and the risk of hypertension, a multivariate logistic regression model was utilized. (3) Results: A total of 7912 subjects were enrolled in the study, of whom 2133 participants had hypertension, a prevalence of 27.0%. After accounting for potential covariates, higher PRAL and NEAP scores were associated with a greater likelihood of developing hypertension, with ORs of 1.34 (95% CI, 1.10-1.62) and 1.29 (95% CI, 1.09-1.53) for PRAL and NEAP scores in Q4, respectively, compared with Q1. In the male group, PRAL and NEAP scores were positively linked to hypertension risk, with ORs of 1.33 (95% CI, 1.06-1.67) and 1.46 (95% CI, 1.14-1.85) for PRAL and NEAP scores in Q4, respectively, compared with Q1, while no significant associations were observed in the female group. Correlations between PRAL scores and hypertension risk lacked significance in the subgroup analyses for participants aged <60 years. There was a significant nonlinear connection observed in the dose-response relationship between DAL (based on PRAL) and hypertension; (4) Conclusions: In Chinese adults, higher PRAL and NEAP scores were positively linked to hypertension risk. This implies that a diet with a low DAL may be a favorable dietary pattern for lowering blood pressure.

[Intelligent co-design of material, process, and equipment for manufacturing high-quality traditional Chinese medicine preparations].

In the context of Pharma 4.0, the design tools that support the pharmaceutical Quality by Design(QbD) are iterating fast toward intelligent or smart design. The conventional development methods for traditional Chinese medicine(TCM) preparations have the limitations such as over dependence on experience, low dimensions for the designed experiment parameters, poor compatibility between the process and equipment, and high trial-and-error cost during process scale-up. Therefore, this paper innovatively proposed the intelligent co-design involving material, process, and equipment for manufacturing high-quality TCM preparations, and introduced the design philosophy, targets, tools, and applications with TCM oral solid dosage(OSD) as an example. In terms of design philosophy, the pharmaceutical design tetrahedron composed of critical material attributes, critical process parameters, critical equipment attributes, and critical quality attributes was developed. The design targets were put forward based on the product performance classification system. The design tools involve a design platform that contains several modules, such a as the iTCM material database, the processing route classification system, the system modeling and simulation, and reliability-based optimization. The roles of different modules in obtaining essential and universal design knowledge of the key common manufacturing units were introduced. At last, the applications of the co-design methodology involving material, process, and equipment in the high shear wet granulation process development and the improvement of the dissolving or dispersion capability of TCM formula granules are illustrated. The research on advanced pharmaceutical design theory and methodology will help enhance the efficiency and reliability of drug development, improve the product quality, and promote the innovation of high-end TCM products across the industry.

[Manufacturing classification system for oral solid dosage forms of traditional Chinese medicines(â ¢): classification of granule dissolving behaviors].

Solubility is an important sensory quality attribute of traditional Chinese medicine(TCM) granules. In this paper, 90 batches of granules(30 batches of TCM formula granules, 30 batches of Chinese patent medicine granules and 30 batches of Japanese Kampo granules) were used as the research objects. The turbidity sensor was used to characterize the turbidity curve of the granule dissolution process. The classification system of granule dissolution behaviors was constructed from three dimensions: dissolution degree, equilibrium time, and dissolution mechanism. According to the equilibrium time, the granule dissolution rates were divided into three categories : faster(<100 s), general(101-300 s) and slow(>301 s). According to the turbidity curve profile, the granule dissolution mechanisms were classified into dissolution-controlled type(α-type), dispersion-controlled type(ß-type), and dispersion-controlled type followed by dissolution-controlled type(γ-type). The proportion of TCM formula granules, Chinese patent medicine granules and Japanese Kampo granules with complete dissolution or slight turbidity at the end of dissolution was 46.7%, 96.7%, and 10.0%. The proportion of TCM formula granules, Chinese patent medicine granules, and Japanese Kampo granules with faster dissolution rates(<100 s) was 23.3%, 26.7%, and 40.0%. The average dissolution rate of Japanese Kampo granules was faster than that of TCM formula granules, and it was slightly faster than the average dissolution rate of Chinese patent medicine granules. The dissolution mechanism of Chinese patent medicine granules was mainly α-type, while that of Japanese Kampo granules was mainly ß-type, and the three types of dissolution mechanisms of TCM formula granules accounted for a relatively average. The purpose of improving the solubility and dispersion of granules can be achieved by combining the comprehensive application of various functional excipients with the small dosage of Japanese Kampo granules and the wide addition scope of excipients. In the process of transforming TCM compound prescriptions into formulas, there is still much room for innovation in formula excipients and process optimization.

A tabletability change classification system in supporting the tablet formulation design via the roll compaction and dry granulation process.

In this paper, the material library approach was used to uncover the pattern of tabletability change and related risk for tablet formulation design under the roll compaction and dry granulation (RCDG) process. 31 materials were fully characterized using 18 physical parameters and 9 compression behavior classification system (CBCS) parameters. Then, each material was dry granulated and sieved into small granules (125-250 µm) and large granules (630-850 µm), respectively. The compression behavior of granules was characterized by the CBCS descriptors, and were compared with that of ungranulated powders. The relative change of tabletability (CoTr) index was used to establish the tabletability change classification system (TCCS), and all materials were classified into three types, i.e. loss of tabletability (LoT, Type I), unchanged tabletability (Type II) and increase of tabletability (Type III). Results showed that approximately 65% of materials presented LoT, and as the granules size increased, 84% of the materials exhibited LoT. A risk decision tree was innovatively proposed by joint application of the CBCS tabletability categories and the TCCS tabletability change types. It was found that the LoT posed little risk to the tensile strength of the final tablet, when Category 1 or 2A materials, or Category 2B materials with Type II or Type III change of tabletability were used. Formulation risk happened to Category 2C or 3 materials, or Category 2B materials with Type I change of tabletability, particularly when high proportions of these materials were involved in tablet formulation. In addition, the risk assessment results were verified in the material property design space developed from a latent variable model in prediction of tablet tensile strength. Overall, results suggested that a combinational use of CBCS and TCCS could aid the decision making in selecting materials for tablet formulation design via RCDG.

[Four critical engineering and technical problems in manufacturing measurement of traditional Chinese medicine].

Focusing on the development and quality improvement strategy of the traditional Chinese medicine(TCM) industry, the scientific and technological innovation of the new engineering of TCM should be paid attention to solve the "stuck neck" dilemma. Under the background of the ecological and industrial revolution of the scientific and technological innovation system, the super-scale information interaction and multi-dimensional integration will inevitably lead to profound changes in the manufacturing mode of TCM. Manufacturing measurement of TCM is formed on the basis of the reliability engineering theory of process control of TCM production. It is the development extension of system theory and system science ideas and a cross-fertilization discipline that combines theory with practice and adheres to the "four-oriented" re-epistemology improvement of the TCM discipline. In response to the problems of complex raw material sources, coarse process technology, unclear material basis, and poor applicability of equipment and technology in the manufacture of TCM, the transformation research mode of "aiming at the integration of pharmaceutical industry-developing intelligent production line-enabling industrial transformation" has been developed. This paper proposed the four key engineering technical problems, i.e., the identification of critical quality attributes(CQA) in the manufacture of TCM, the quality by design(QbD) and product development of the manufacturing process of TCM, the quality transfer principle and multivariate process capability index of TCM manufacturing, and the development of measurement technology and equipment of the manufacturing measurement of TCM, to achieve the systematization of quality control indicators, real-time process control, digitalization of manufacturing process, transparency of quality transfer, and intelligent whole-process control. In this paper, the new concepts, new theories, and new technologies provide a reference for the industrialization of TCM.

[Research progress and maturity assessment of continuous manufacturing of traditional Chinese medicine].

The pharmaceutical manufacturing model is gradually changing from intermittent manufacturing to continuous manufacturing and intelligent manufacturing. This paper briefly reviewed the supervision and research progress in continuous pharmaceutical manufacturing in China and abroad and described the definition and advantages of continuous pharmaceutical manufacturing. The continuous manufacturing of traditional Chinese medicine(TCM) at the current stage was summarized in the following three terms: the enhancement of the continuity of intermittent manufacturing operations, the integration of continuous equipment to improve physical continuity between units, and the application of advanced process control strategies to improve process continuity. To achieve continuous manufacturing of TCM, the corresponding key technologies, such as material property characterization, process modeling and simulation, process analysis technology, and system integration, were analyzed from the process and equipment, respectively. It was proposed that the continuous manufacturing equipment system should have the characteristics of high speed, high response, and high reliability, "three high(H~3)" for short. Considering the characteristics and current situation of TCM manufacturing, based on the two dimensions of product quality control and production efficiency, a maturity assessment model for continuous manufacturing of TCM, consisting of operation continuity, equipment continuity, process continuity, and quality control continuity, was proposed to provide references for the application of continuous manufacturing technology for TCM. The implementation of continuous manufacturing or the application of key continuous manufacturing technologies in TCM can help to systematically integrate advanced pharmaceutical technology elements and promote the uniformity of TCM quality and the improvement of production efficiency.

[Manufacturing classification system for oral solid dosage forms of traditional Chinese medicines(â ): classification of processing routes].

Oral solid dosage(OSD) occupies a key position in the market of Chinese patent medicines and new traditional Chinese medicines. Processing route is the foundation for the research and development of traditional Chinese medicine OSDs. On the basis of prescriptions and preparation methods of 1 308 traditional Chinese medicine OSDs recorded in the Chinese Pharmacopoeia, we summarized the patterns of processing routes of both modern dosage forms(tablets, granules, and capsules) and traditional dosage forms(pills and powder) and constructed a manufacturing classification system(MCS) based on the processing routes. Based on the MCS, statistical analyses were conducted respectively on medicinal materials, pharmaceutical excipients, extraction solvents in the pretreatment process, crushed medicinal materials, methods of concentration and purification, and methods of drying and granulation, aiming to uncover the process features. The results showed that each dosage form can be prepared via different routes with different processing methods of decoction pieces and raw materials for dosage preparation. The raw materials for dosage form preparation of traditional Chinese medicine OSDs included total extract, semi-extract, and total crushed powder, which accounted for different proportions. The raw materials for traditional dosage forms are mainly decoction pieces powder. Semi-extracts are the main raw materials for tablets and capsules, which account for 64.8% and 56.3%, respectively. Total extracts are the main raw materials for granules, with a proportion of 77.8%. Compared with tablets and capsules, traditional Chinese medicine granules with dissolubility requirements had a larger proportion of water extraction process, a higher proportion of refining process(34.7%), and a lower proportion of crushed medicinal mate-rials in semi-extract granules. There are four ways to add volatile oil to the modern dosage forms of traditional Chinese medicine. In addition, some new technologies and processes have been used in concentration, filtration, and granulation processes of traditional Chinese medicine OSDs, and the application of pharmaceutical excipients is diversified. The results of this study are expected to provide reference for the processing route design and upgrading of OSDs for new traditional Chinese medicines.

[Manufacturing classification system for oral solid dosage forms of traditional Chinese medicines (â ¡): classification of tablets disintegration behavior].

In this paper, 50 batches of representative traditional Chinese medicine tablets were selected and the disintegration time was examined with the method in Chinese Pharmacopoeia. The disintegration time and disintegration phenomenon were recorded, and the dissolution behaviors of water-soluble and ultraviolet-absorbent components during the disintegration process of tablets were characterized by self-control method. The results revealed that coating type and raw material type influenced the disintegration time of tablets. It was found that only 4% of traditional Chinese medicine tablets had obvious fragmentation during the disintegration process, while 96% of traditional Chinese medicine tablets showed gradual dissolution or dispersion. Furthermore, according to the disintegration speed, disintegration phenomenon, and whether the cumulative dissolution of measured components was > 90% at complete disintegration, a disintegration behavior classification system(DBCS) was created for the regular-release traditional Chinese medicine tablets. As a result, the disintegration behaviors of 50 batches of traditional Chinese medicine tablets were classified into four categories, i.e. ⅠA_2, ⅠB_1, ⅡB_1, and ⅡB_2. traditional Chinese medicine tablets(Class I) with disintegration time ≤ 30 min were defined to be rapid in disintegration, which can be the objective of optimization or improvement of Chinese herbal extract(semi extract) tablets. Different drug release models were used to fit the dissolution curve of traditional Chinese medicine tablets with gradual dissolution or dispersion phenomenon(i.e. Type B tablets). The results showed that the dissolution curves of water-soluble components in the disintegration process conformed to the zero order kinetics and the Ritger-Peppas model. It could be inferred that the disintegration mechanisms of type B tablets were a combination of dissolution controlled and swelling controlled mechanisms. This study contributes to understanding the disintegration behavior of traditional Chinese medicine tablets, and provides a reference for the design and improvement of disintegration performance of traditional Chinese medicine tablets.

[Patent application of intelligent quality control technology in traditional Chinese medicine production process: a review].

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

Data-driven engineering framework with AI algorithm of Ginkgo Folium tablets manufacturing.

Smart manufacturing still remains critical challenges for pharmaceutical manufacturing. Here, an original data-driven engineering framework was proposed to tackle the challenges. Firstly, from sporadic indicators to five kinds of systematic quality characteristics, nearly 2,000,000 real-world data points were successively characterized from Ginkgo Folium tablet manufacturing. Then, from simplex to the multivariate system, the digital process capability diagnosis strategy was proposed by multivariate Cpk integrated Bootstrap-t. The Cpk of Ginkgo Folium extracts, granules, and tablets were discovered, which was 0.59, 0.42, and 0.78, respectively, indicating a relatively weak process capability, especially in granulating. Furthermore, the quality traceability was discovered from unit to end-to-end analysis, which decreased from 2.17 to 1.73. This further proved that attention should be paid to granulating to improve the quality characteristic. In conclusion, this paper provided a data-driven engineering strategy empowering industrial innovation to face the challenge of smart pharmaceutical manufacturing.

Using a Material Library to Understand the Change of Tabletability by High Shear Wet Granulation.

Understanding the tabletability change of materials after granulation is critical for the formulation and process design in tablet development. In this paper, a material library consisting of 30 pharmaceutical materials was used to summarize the pattern of change of tabletability during high shear wet granulation and tableting (HSWGT). Each powdered material and the corresponding granules were characterized by 19 physical properties and nine compression behavior classification system (CBCS) parameters. Principal component analysis (PCA) was used to compare the physical properties and compression behaviors of ungranulated powders and granules. A new index, namely the relative change of tabletability (CoTr), was proposed to quantify the tabletability change, and its advantages over the reworking potential were demonstrated. On the basis of CoTr values, the tabletability change classification system (TCCS) was established. It was found that approximately 40% of materials in the material library presented a loss of tabletability (i.e., Type I), 50% of materials had nearly unchanged tabletability (i.e., Type II), and 10% of materials suffered from increased tabletability (i.e., Type III). With the help of tensile strength (TS) vs. compression pressure curves implemented on both powders and granules, a data fusion method and the PLS2 algorithm were further applied to identify the differences in material properties requirements for direct compression (DC) and HSWGT. Results indicated that increasing the plasticity or porosity of the starting materials was beneficial to acquiring high TS of tablets made by HSWGT. In conclusion, the presented TCCS provided a means for the initial risk assessment of materials in tablet formulation design and the data modeling method helped to predict the impact of formulation ingredients on the strength of compacts.

Functional and binding studies of gallic acid showing platelet aggregation inhibitory effect as a thrombin inhibitor.

Objective: This study was devoted to identifying natural thrombin inhibitors from traditional Chinese medicine (TCM) and evaluating its biological activity in vitro and binding characteristics. Methods: A combination strategy containing molecular docking, thrombin inhibition assay, surface plasmon resonance (SPR) and molecular dynamics simulation were applied to verify the study result. Results: Gallic acid was confirmed as a direct thrombin inhibitor with IC50 of 9.07 µmol/L and showed a significant inhibitory effect on thrombin induced platelet aggregation. SPR-based binding studies demonstrated that gallic acid interacted with thrombin with a KD value of 8.29 µmol/L. Molecular dynamics and binding free energy analysis revealed that thrombin-gallic acid system attained equilibrium rapidly with very low fluctuations, the calculated binding free energies was -14.61 kcal/mol. Ala230, Glu232, Ser235, Gly258 and Gly260 were the main amino acid residues responsible for thrombin inhibition by gallic acid, providing a mechanistic basis for further optimization. Conclusion: This study proved that gallic acid is a direct thrombin inhibitor with platelet aggregation inhibitory effect, which could provide a basis for the follow-up research and development for novel thrombin inhibitors.

A Discovery Strategy for Active Compounds of Chinese Medicine Based on the Prediction Model of Compound-Disease Relationship.

An accurate characterization of diseases and compounds is the key to predicting the compound-disease relationship (CDR). However, due to the difficulty of a comprehensive description of CDR, the accuracy of traditional drug development models for large-scale CDR prediction is usually unsatisfactory. In order to solve this problem, we propose a new method that integrates the molecular descriptors of compounds and the symptom descriptors of diseases to build a CDR two-dimensional matrix to predict candidate active compounds. The Matlab software draws grayscale images of CDRs, which are used as a benchmark dataset for training convolutional neural network (CNN) models. The trained model is used to predict candidate antitumor active compounds. Among the AlexNet and GoogLeNet models, we selected the GoogLeNet model for the prediction of active compounds in Chinese medicine, and its Acc, Sen, Pre, F-measure, MCC, and AUC are 0.960, 0.956, 0.965, 0.960, 0.920, and 0.964, respectively. In the prediction results of compounds, 1624 candidate CDRs were found in 124 Chinese medicines. Among them, we obtained 31 features of candidate antitumor active compounds. This method provides new insights for the discovery of candidate active compounds in Chinese medicine.

Safety assessment of marigold flavonoids from marigold inflorescence residue.

ETHNOPHARMACOLOGICAL RELEVANCE: Marigold flavonoids, extracted from marigold (Tagetes erecta L.) inflorescence residues, have attracted significant attention with respect to antioxidant, anti-inflammatory and chelating properties. However, the toxicity of marigold flavonoids have not yet been fully investigated. AIM OF THE STUDY: The main purpose of this study was to assess the safety of marigold flavonoids extracted from Marigold (Tagetes erecta L.) in order to provide information on its nonclinical safety. Thus, the acute oral toxicity, in vitro Ames test, sperm aberration study, bone marrow micronucleus test, subchronic oral toxicity test, and teratogenic potential were carried out in rats or mice. MATERIALS AND METHODS: For an acute oral toxicity test, SD rats and ICR mice (male and female, n = 5) orally received a single dose of 5000 mg/kg marigold flavonoids. Evaluation of marigold flavonoids genotoxic potential with a battery of tests, including an in vitro bacterial reverse mutation test using four mutant strains of Salmonella typhimurium (TA97、TA98、TA100、TA102), an sperm aberration test and an in vivo micronucleus test using bone marrow cells ICR mice that were orally administered marigold flavonoids, an subchronic oral toxicity study and teratogenic test employing male and female SD rats that were orally administered marigold flavonoids. All animals tests were completed in accordance with GB 15193 for toxicity tests. RESULTS: In the acute oral toxicity test, marigold flavonoids given at the dose of 5000 mg/kg body weight for 14 days didn't produce any abnormal clinical symptoms or mortality in SD rats and ICR mice (both sex, n = 5). There was no evidence of genotoxicity of marigold flavonoids based on the results of the in vitro bacterial reverse mutation test (up to 1250 µg/plate), the sperm aberration test (up to 5000 mg/kg body weight), the in vivo micronucleus test (up to 5000 mg/kg body weight), the subchronic oral toxicity study (up to 10 g/kg feed dose) and the teratogenic test (up to 1250 mg/kg body weight). CONCLUSIONS: We found that marigold flavonoids are safe with regard to acute toxicity in rats or mice as well as genotoxicity such as mutagenesis or clastogenesis under the present experimental conditions. These results might support the safety of marigold flavonoids as a potential therapeutic material for the traditional use of herbal medicines and for the further development of novel antioxidant.

NIR robustness model of variable selection investigation of critical quality attributes coupled with different simulate noises by prediction capability and reproducibility.

variable selection is critical to select characteristic variables of critical quality attributes to improve model performance and interpret the identified variables in multivariate calibration. However, classical variable selection methods were developed and optimized by the prediction error. It is rare for the robustness evaluation of variable selection methods. In this study, the robustness of four different variable selection methods was investigated by adding different types of simulate noises to validation set and calibration and validation sets, respectively. The reproducibility as well as root mean squared error of prediction (RMSEP) were used together as common measure in assessing the robustness of different variable selection methods. The robustness of four variable selection methods method was investigated using two near infrared (NIR) datasets including open-source dataset of corn and Chinese herbal medicine (CHM) dataset. The result illustrated that variable importance in projection (VIP) was substantially more robust to additive noise, with smaller RMSEP value and high reproducibility. This provides a novel strategy for the reliability evaluation of variable selection methods in NIR model of critical quality attributes.

[Material manufacturability classification in high shear wet granulation process of Chinese medicine].

The high shear wet granulation(HSWG) process of Chinese medicine has a complicated mechanism. There are many influencing factors that contribute to this process. In order to summarize the manufacturability of different kinds of materials in HSWG, this paper constructed a material library composed of 11 materials, including 4 Chinese medicine extracts and 7 pharmaceutical excipients. Each material was described by 22 physical parameters. Several binders were employed, and their density, viscosity and surface tension were characterized. Combining empirical constraints and the principle of randomization, 21 designed experiments and 8 verification experiments were arranged. The partial least squares(PLS) algorithm was used to establish a process model in prediction of the median granule size based on properties of raw materials and binders, and process parameters. The surface tension and density of binders, as well as the maximum pore saturation were identified as key variables. In the latent variable space of the HSWG process model, all materials could be divided into three categories, namely the Chinese medicine extracts, the diluents and the disintegrants. The granulation of Chinese medicine extracts required low viscosity and low amount of binder, and the resulted granule sizes were small. The diluent powders occupied a large physical space, and could be made into granules with different granule sizes by adjusting the properties of binders. The disintegrants tended to be made into large granules under the condition of aqueous binder. The combination use of material database and multivariate modeling method is conducive to innovate the knowledge discovery of the wet granulation process of Chinese medicine, and provides a basis for the formulation and process design based on material attributes.

Development of MIF/IL-1ß biosensors for discovery of critical quality attributes and potential allergic rhinitis targets from clinical real-world data by intelligent algorithm coupled with in vitro and vivo mechanism validation.

There are still huge challenges from clinical real-world data to accurate targets and critical quality attributes (CQAs) for effective treatment of allergic rhinitis (AR). Here, we present a novel integrated strategy that biosensors and intelligent algorithms were used to angle AR targets and CQAs from clinical real world. Firstly, bagging and boosting partial least squares discrimination analysis (PLS-DA) and Monte-Carlo sampling were proposed to screen accurate AR targets. Macrophage migration inhibitory factor (MIF) and Interleukin-1beta (IL-1ß) potential targets were obtained based on large-scale analysis of one thousand proteins and in-depth precise screening of seventy proteins. Furthermore, high electron mobility transistor (HEMT) biosensors were fabricated and successfully modified by MIF and IL-1ß potential targets with a low detection concentration as 1 pM and quantitative range from 1 pM to 10 nM. Surprisingly, through MIF/IL-1ß biosensors, we angled 5-O-methylvisammioside, amygdalin, and cimicifugoside three CQAs. The strong interaction was discovered among three CQAs and MIF/IL-1ß biosensors with almost all KD up to 10-11 M. Finally, interaction among three CQAs and MIF/IL-1ß biosensors were evaluated by in vitro and vivo experiments. In this paper, two critical potential targets and three effective CQAs for AR treatment were discovered and validated by biosensor and advanced algorithms. It provides a superior integrated idea for angling critical targets and CQAs from clinical real-world data by biosensors and informatics.

Using a material database and data fusion method to accelerate the process model development of high shear wet granulation.

High shear wet granulation (HSWG) has been wildly used in manufacturing of oral solid dosage (OSD) forms, and process modeling is vital to understanding and controlling this complex process. In this paper, data fusion and multivariate modeling technique were applied to develop a formulation-process-quality model for HSWG process. The HSWG experimental data from both literature and the authors' laboratory were fused into a single and formatted representation. A material database and material matching method were used to compensate the incomplete physical characterization of literature formulation materials, and dimensionless parameters were utilized to reconstruct process variables at different granulator scales. The exploratory study on input materials properties by principal component analysis (PCA) revealed that the formulation data collected from different articles generated a formulation library which was full of diversity. In prediction of the median granule size, the partial least squares (PLS) regression models derived from literature data only and a combination of literature data and laboratory data were compared. The results demonstrated that incorporating a small number of laboratory data into the multivariate calibration model could help significantly reduce the prediction error, especially at low level of liquid to solid ratio. The proposed data fusion methodology was beneficial to scientific development of HSWG formulation and process, with potential advantages of saving both experimental time and cost.