Novel Coating Uniformity Models for Tablet Pan Coaters

Choi, Michael; Porter, Stuart C.; Macht, Betsy; Meisen, Axel

doi:10.1208/s12249-020-01857-z

Cited by 8 publications

(6 citation statements)

References 19 publications

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“…This can be achieved by using literature models predicting CV. In this work, the analytical model developed by Choi et al [7,8] is used since it has shown good agreement with literature data [4,19,20] and correlations [12,13]. The Choi model gives CV as a function of tablet diameter (d p ), tablet shape (ψ), bed porosity (ε), pan speed ( .…”

Section: Factors Affecting Precision (Cv)mentioning

confidence: 77%

“…If the process capability of X is outside the 98.5-101.5% range but within 95-105%, CV must be controlled to no higher than 4% for T ≤ 101.5% to meet the acceptance criterion for AV. One way of improving the CV from 6% to 4% is to increase the coating time (e.g., by decreasing the spray rate or solid's concentration in the coating solution), but this can be costly from an operational perspective-i.e., to decrease CV from 6 to 4% requires the coating time to be more than doubled based on the inverse square root relationship between CV and coating time [4,7,12,13]. Increasing n s to 30 can increase CV, but this increases the cost of testing.…”

Section: Resultsmentioning

confidence: 99%

“…An important challenge with pan-coating technology, including its use to produce DCT, is its compliance with the content uniformity criteria, specifically the acceptance value. In this paper, recent tablet coating models [7,8] are used to show that it is possible to meet the criteria by a judicious choice of design and operating parameters.…”

Section: Introductionmentioning

confidence: 99%

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Application of Mathematical Models to Determine the Feasibility of Amorphous Drug Layering in Pan Coaters

Choi¹,

Porter

Meisen

2022

Pharmaceutics

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Oral solid dosage forms that contain APIs in the amorphous state have become commonplace because of many drug substances exhibiting poor water solubility, which negatively impacts their absorption in the human GI tract. While micronization, solvent spray-drying, and hot-melt extrusion can address solubility issues, spray coating of the APIs onto beads and tablets offers another option for producing amorphous drug products. High-level comparisons between bead and tablet coating technologies have the potential for simpler equipment and operation that can reduce the cost of development and manufacturing. However, spray coating directly onto tablets is not without challenges, especially with respect to meeting uniformity acceptance value (AV) criteria, comprising accuracy (mean) and precision (variance) objectives. The feasibility of meeting AV criteria is examined, based on mathematical models for accuracy and precision. The results indicate that the main difficulty in manufacturing satisfactory drug-layered tablets by spray coating is caused by the practical limitations of achieving the necessary coating precision. Despite this limitation, it is shown that AV criteria can be consistently met by appropriate materials monitoring and control as well as processing equipment setup, operation, and maintenance.

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Section: Factors Affecting Precision (Cv)mentioning

confidence: 77%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Application of Mathematical Models to Determine the Feasibility of Amorphous Drug Layering in Pan Coaters

Choi¹,

Porter

Meisen

2022

Pharmaceutics

Self Cite

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“…where f i is the predicted value, y i refers to the real value, and y represents the average value; thus, Table 2 Mathematical Problems in Engineering dispersion [44][45][46]. By calculating and comparing the coefficient of variation of the machine learning prediction models in this paper, the performance of the prediction model is analyzed.…”

Section: Prediction Performance Evaluationmentioning

confidence: 99%

Crack Prediction Based on Wavelet Correlation Analysis Least Squares Support Vector Machine for Stone Cultural Relics

Liu

et al. 2021

Mathematical Problems in Engineering

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Preventive protection of cultural relics is to make use of all the science and technology beneficial to the research and protection of archaeological heritage to predict the disease of cultural relics. The existing preventive cultural relics protection system has made some achievements in environmental monitoring, but the analysis and utilization of large data of cultural relics are still insufficient. In this paper, under the idea of multisource information fusion, a least squares support vector machine regression method based on multivariate time series wavelet correlation analysis is proposed to achieve accurate crack prediction of stone cultural relics. Firstly, the correlation of multivariate time series of stone cultural relics are quantitatively analyzed and the validity of characteristic variables of the crack is discriminated by wavelet correlation analysis; then, a least squares support vector machine prediction model is constructed based on the correlation obtained from the analysis; finally, the good performance of the method is verified by using the environmental monitoring data of the rock mass fracture in the North Qianfo Cliff of Dafo Temple in Binzhou City of Shaanxi Province. The experimental results show that the proposed method is more effective than the traditional backpropagation neural network, support vector machine, and relevance vector machine regression methods. This method is universal and easy to implement for multisource data prediction of nonmovable cultural relics diseases. It provides a scientific theoretical reference for the preventive protection of cultural relics.

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“…Coating of granular materials is widely applied in industrial processes, including pharmaceutical and food. − In the pharmaceutical industry, medicines are usually spray-coated for cosmetic or functional reasons. − The cosmetic coating can modify the appearance of the drug, mask the drug odor, improve the taste, and others. As for the functional coating, it can be used to modify the release rate of the active pharmaceutical ingredient (API) and achieve the controlled release application.…”

Section: Introductionmentioning

confidence: 99%

DEM-DDM Investigation of the Tablet Coating Process Using Different Particle Shape Models

Liu

Zhou

et al. 2022

Ind. Eng. Chem. Res.

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Tablets are usually spray-coated in the pharmaceutical industry, and coating uniformity is important for the coating process. In this study, discrete element method-discrete droplet method (DEM-DDM) is applied for the investigation of the coating process, tablets are described by different particle shape models, and the influence of different particle shape models on inter-tablet coating uniformity is investigated. Multi-sphere approach with two accuracies, multi-super-ellipsoid approach, and polyhedron approach are applied to describe the biconvex cylinder tablet. The proposed model is verified by a lab-scale coating experiment within a coating pan first. And then, the coating process in a coating drum with baffles is investigated. It can be found that inter-tablet coating uniformity is almost the same for the polyhedron and multi-super-ellipsoid approaches, and the inter-tablet coating uniformity obtained by the multi-sphere approach is lower than both of them. The influence of different parameters on inter-tablet coating uniformity is also studied, including the droplet diameter, the drum rotation speed, the spray range angle, and the nozzle number, which can provide guidance for the tablet coating process.

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Novel Coating Uniformity Models for Tablet Pan Coaters

Cited by 8 publications

References 19 publications

Application of Mathematical Models to Determine the Feasibility of Amorphous Drug Layering in Pan Coaters

Application of Mathematical Models to Determine the Feasibility of Amorphous Drug Layering in Pan Coaters

Crack Prediction Based on Wavelet Correlation Analysis Least Squares Support Vector Machine for Stone Cultural Relics

DEM-DDM Investigation of the Tablet Coating Process Using Different Particle Shape Models

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