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Multivariantno določanje kritičnih fizikalnih lastnosti sestavin pelet z vplivi na sproščanje modelne zdravilne učinkovine : enoviti magistrski študijski program Farmacija
ID Kotnik, Dejan (Author), ID Janković, Biljana (Mentor) More about this mentor... This link opens in a new window

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Abstract
Večenotni dostavni sistemi so v današnjem času vse pogostejša tematika raziskav razvojne in proizvodne farmacevtske tehnologije. Primer takšnih sistemov so pelete, ki s svojo majhnostjo in strukturno samostojnostjo delcev nudijo mnoge prednosti. Obstaja več tehnoloških postopkov za pripravo pelet. Pelete, ki smo jih obravnavali v našem delu izdelujemo s tehnologijo iztiskanja in krogličenja, večstopenjskim procesom, katerega kvaliteta produkta je odvisna od številnih procesnih in formulacijskih parametrov. Glavni cilj magistrske naloge je bila uporaba multivariatne metode kot statističnega orodja za doprinos k optimizaciji že uveljavljenega, komercialnega postopka izdelave pelet. V ta namen smo z metodo sedeče kapljice določili fizikalen parameter hitrosti pronicanja tekočega medija v trdno snov modelne zdravilne učinkovine, mikrokristalne celuloze in κ-karagenana, ki pod različnimi kontrolnimi številkami vstopajo v formulacijo pelet s takojšnjim sproščanjem. Eksperimentalne vrednosti smo skupaj s podatki predhodnih raziskav proizvodnih serij pelet, uporabili za izgradnjo multivariatnega modela, ki nam je omogočil prepoznavo procesnih in formulacijskih parametrov s potencialnim vplivom na hitrost sproščanja modelne zdravilne učinkovine iz pelet.Multivariatno obdelavo podatkov smo izvedli z regresijsko metodo delnih najmanjših kvadratov (PLSR – ang. partial least squares regression), kjer smo za matriko X neodvisnih spremenljivk izbrali vrednosti vseh 117 preučevanih procesnih in formulacijskih parametrov, hitrost sproščanja zdravilne učinkovine v 45. minuti pa je predstavljala naš opazovan odziv Y (odvisna spremenljivka). Iz rezultatov končnega modela, ki smo ga razvili z računalniškim programom SIMCA P+ 14.0, je bilo razvidno, da na hitrost sproščanja zdravilne učinkovine vpliva 5 procesnih in 4 formulacijski parametri. Njihov pozitiven oz. negativen vpliv na odziv smo interpretirati s pomočjo teoretičnih razlag iz strokovne literature. Vrednosti prileganja (R2) in napovedne sposobnosti (Q2) sta nakazovali na model zmerne napovedljivosti. Dodatne preiskave fizikalno-kemijskih lastnosti vhodnih surovin ter parametrov procesa izdelave bi lahko kakovost modela izboljšale. V sklopu sodobnega pristopa proizvodnje farmacevtskih izdelkov z vgrajeno kakovostjo (QbD – ang. Quality by Design) smo parametre iz rezultatov našega modela definirali kot kritične procesne parametre (CPP – ang. Critial Process Parameters) ter kritične lastnosti surovin (CMA – ang. Critical Material Attributes), ki potencialno vplivajo na kritično lastnost kakovosti produkta (CQA. – ang. Critical Quality Attributes), tj. sproščanje zdravilne učinkovine iz pelet.

Language:Slovenian
Keywords:pelete iztiskanje krogličenje multivariantna analiza podatkov dostavni sistem pomožne snovi
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FFA - Faculty of Pharmacy
Place of publishing:Ljubljana
Publisher:[D. Kotnik]
Year:2018
Number of pages:V, 48 f.
PID:20.500.12556/RUL-120258 This link opens in a new window
UDC:661.12(043.3)
COBISS.SI-ID:4640881 This link opens in a new window
Publication date in RUL:17.09.2020
Views:775
Downloads:114
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Secondary language

Language:English
Title:Multivariate determination of critical physical properties of pellets' components influencing dissolution rate of a model active ingredient
Abstract:
Multiple unit drug delivery systems are nowdays a very common research topic in pharmaceutical drug development and production technology. An example of such are pellets that offer many advantages with their small size and structural independence. There are many technological methods for preparing pellets. Pellets, which are discussed in our study, are manufactured by extrusion and spheronization, a multistage process whose product quality depends on a number of process and formulation parameters. The main goal of the diploma was the application of multivariate method as a statistical tool in Quality by Design (QbD) environment form determination of potential critical material and process parameters in commercial pellet production. For this purpose, a sessile drop method was used to determine the physical parameter of penetration rate of liquid medium into the solid substance of a model active ingredient, microcrystalline cellulose and κ-carrageenan that were entering under different batch numbers in the final dosage form, e.g. immediate release pellets. Experimental values were combined with the data from previous research in order to upgrade a multivariate model. This enabled us to identify potential critical process and formulation parameters with the impact on the pellets' dissolution rate of a model active ingredient. Multivariate data analysis was performed using a partial least squares regression method (PLSR), where all 117 studied process and formulation parameters were included in the X matrix of independent variables. Dissolution rate of the model active ingredient in 45th minute was our observed response Y (dependent variable). Results from the final model, developed by SIMCA P+ 14.0 computer program, showed that dissolution rate is influenced by 5 process and 4 formulation parameters. Their positive or negative impact on the response was interpreted with the help of theoretical explanations found in literature. Fitting (R2) and predictive ability (Q2) values indicated a model with a moderate quality. Further research on physicochemical properties of input materials and production process parameters could improve the quality of the model.As part of the QbD approach, the parameters identified from our model have been defined as Critical Process Parameters (CPP) and Critical Material Attributes (CMA) with a potential influence on Critical Quality Attributes (CQA), i.e. dissolution rate of pellets' active ingredient.

Keywords:pellets extrusion and spheronization multivariate data analysis

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