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Tablets Development Based on Clover Meadow Grass Phytosubstance Using Design of the Experiment Method and QdD Tools

Authors: A. N. Golubev; Th. I. Nguen; V. V. Sorokin; I. E. Kauhova;

Tablets Development Based on Clover Meadow Grass Phytosubstance Using Design of the Experiment Method and QdD Tools

Abstract

Introduction. Quality, along with efficacy and safety, are the key characteristics of a drug. Therefore, it is important in frame of pharmaceutical development to lay the foundation for obtaining a quality product and achieving the desired product characteristics. One of the tools used for this is the «Quality by design» approach (QbD) - quality through development. The ICH Q8 «Pharmaceutical development» manual defines it as a systematic approach to development that starts with pre-defined goals and focuses on understanding the product and process, as well as managing the process based on reliable scientific data and quality risk management.Aim. The aim of the research is to develop the composition of tablets based on clover meadow grass phytosubstance using the QbD tool with application of mathematical model that links the composition of tablets (CMA) with its quality attributes (CQA).Materials and methods. The research was based on the concept of quality by design/quality through development. The main method for conducting the development process was design of experiments method/experiment planning with creating of individual design. The experiment planning was performed in the software package JMP Pro 14 (ver. 14. 3. 0), SAS Institute Inc., USA. The method of risk analysis-failure mode and effects analysis (FMEA)/analysis of the types and consequences of failures was used for risk assessment in research. As methods of analysis of the tablet mixture and the tablets were used the following the tests: disintegration of tablets, crushing strength of tablets, determination of hygroscopicity, determination of Carr's and Hausner index.Results and discussion. The composition of tablets based on the clover meadow grass phytosubstance obtained by direct pressing was developed. In order to develop the composition of tablets in accordance with the ICH Q8 guidelines, the first step was to create a quality target product profile. To ensure the properties specified in the quality target product profile, the component composition of the developed tablets was selected based on the selected production technology and key characteristics of both the tablet mixture and the finished product. The risk assessment for the product composition determined that the quantitative content of 4 excipients are considered as critical quality attributes of materials (CMA). CMAs affect the critical quality attributes (CQA) of the dosage form, which determine the effectiveness of the composition.Based on the initial data analysis, optimal content boundaries for each component were established. Potentially critical qualitative characteristics of the drug under development (CQA) were identified. A mathematical model linking critical quality parameters and tablet composition was obtained and analyzed.Conclusion. Based on a mathematical model, the optimal composition of tablet mixture and tablets obtained from it was determined. The tablets quality indicators corresponding to the selected composition were calculated, and the adequacy of the obtained model was evaluated by comparing calculated and real indicators. It is shown that the calculation error does not exceed 10 %, and the proposed optimization algorithm and the model derived from it can be successfully used to optimize the composition of tablets.

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Keywords

quality by design, design of experiment, HD9665-9675, drug development, Pharmaceutical industry

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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