Discrete optimization of the implementation stages of pharmaceutical development for a spray treatment for oral diseases

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Аннотация

Introduction. All over the world more than 3.5 billion people suffer from oral diseases, which can lead to endogenous infectious diseases and create conditions for external infections. The growing antimicrobial resistance of bacterial strains is a global health threat. Oligoalkyleneguanidine polymers may be promising compounds to solve this problem. The spray form for the application of these substances is the most optimal.

The aim of the study is to apply discrete optimization to implement the stages of pharmaceutical development of a spray based on branched oligohexamethyleneguanidine for the treatment of oral diseases.

Material and methods. Experiments are carried out using various equipment and samples with different compositions have been developed. The implementation of the pharmaceutical development stages was carried out using a discrete optimization algorithm.

Results. When implementing discrete optimization in pharmaceutical development, it is necessary to prioritize criteria and limitations using the target quality profile of the drug being developed. As a result of the optimization cycles carried out, the optimal composition was selected, which corresponds to the target quality profile, including such parameters as pH, dynamic viscosity, sterilizing filtration, adhesion of the formulations to the oral mucosa and the spray torch. A discrete optimization was carried out, taking into account the wetting edge angle and particle size distribution. The optimal composition was sample No. 8, which has pseudoplastic properties, provides unhindered spraying and prevents the composition from draining from the mucous membrane of the oral cavity.

Conclusion. During the study, the optimal ratio of components was determined and the development of a spray based on oligohexamethyleneguanidine with the implementation of stages of pharmaceutical development for discrete optimization was proposed.

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Авторлар туралы

D. Shatalov

MIREA – Russian Technological University

Хат алмасуға жауапты Автор.
Email: shatalov_d@mirea.ru
ORCID iD: 0000-0003-4510-1721

Ph.D. (Pharm.)

Ресей, Moscow

S. Kedik

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0003-2610-8493

Dr.Sc. (Tech.), Professor

Ресей, Moscow

D. Akhmedova

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0002-0951-939X

Assistant

Ресей, Moscow

A. Gromakova

All-Russian Scientific Research Institute of Medicinal and Aromatic Plants

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0001-8984-0724

Dr.Sc. (Pharm), Chief Research Scientist

Ресей, Moscow

Yu. Koroleva

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0001-8092-1990

Student

Ресей, Moscow

A. Dolgovskaya

MIREA – Russian Technological University; Institute of Pharmaceutical Technologies

Email: shatalov_d@mirea.ru

Student

Ресей, Moscow; Moscow

S. Kharchenko

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru

Student

Ресей, Moscow

D. Kirillova

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0002-3055-1116

Student

Ресей, Moscow

D. Minenkov

Ishlinsky Institute for Problems in Mechanics of the Russian Academy of Sciences

Email: shatalov_d@mirea.ru
ORCID iD: 0000-0001-6432-8134

Senior Research Scientist

Ресей, Moscow

A. Nikulin

MIREA – Russian Technological University

Email: shatalov_d@mirea.ru
ORCID iD: 0009-0004-2755-2734

Associate Professor

Ресей, Moscow

Әдебиет тізімі

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  8. Shatalov D.O, Kedik S.A., Krupenchenkova N.V., et al. Acute Toxicity of the Pharmaceutical Substance Branched Oligohexamethyleneguanidine Hydrochloride at Mice and Rats after Intragastric Administration. American Journal of Biomedical Science & Research. 2019; 4(2): 76–77.
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Әрекет
1. JATS XML
2. Fig. 1. Algorithmic sequence of R&D implementation

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3. Fig. 2. Viscosity values of samples obtained from viscosity-velocity curves

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4. Fig. 3. Viscosity-velocity flow curves of the test samples (а–е)

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5. Fig. 4. A typical view of a drop of the studied compositions on test substrates of various nature

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6. Fig. 5. Static prints of spray torches of samples No. 6, No. 3 and No. 8, respectively

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7. Fig. 6. Differential distribution of sprayed spray particles of experimental samples (compositions) by size

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