Design of particle size distribution for custom dissolution profiles by solving the inverse problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F22%3A43924685" target="_blank" >RIV/60461373:22340/22:43924685 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1016/j.powtec.2021.10.023" target="_blank" >https://doi.org/10.1016/j.powtec.2021.10.023</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.powtec.2021.10.023" target="_blank" >10.1016/j.powtec.2021.10.023</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Design of particle size distribution for custom dissolution profiles by solving the inverse problem

Popis výsledku v původním jazyce

Dissolution testing is widely used to measure the rate of drug release and predict its in-vivo behavior. The release rate can be controlled by adjusting the particle size distribution (PSD). However, experimental investigation of various particle sizes requires many time-consuming experiments. To reduce the need for them, we propose an optimization framework to solve the inverse problem, i.e., design a PSD that results in a prescribed dissolution profile. The framework&apos;s computational core predicts a dissolution profile using a population balance model coupled with a mass balance equation, while the optimization algorithm obtains the inverse solution. The model was validated using mono- and multimodal particle populations of a reference compound (KCl). The validation resulted in a good agreement between the simulated and experimental data. This suggests that the usage of the framework can provide a fast determination of the required PSD, reducing the number of experiments needed. © 2021 Elsevier B.V.

Název v anglickém jazyce

Design of particle size distribution for custom dissolution profiles by solving the inverse problem

Popis výsledku anglicky

Dissolution testing is widely used to measure the rate of drug release and predict its in-vivo behavior. The release rate can be controlled by adjusting the particle size distribution (PSD). However, experimental investigation of various particle sizes requires many time-consuming experiments. To reduce the need for them, we propose an optimization framework to solve the inverse problem, i.e., design a PSD that results in a prescribed dissolution profile. The framework&apos;s computational core predicts a dissolution profile using a population balance model coupled with a mass balance equation, while the optimization algorithm obtains the inverse solution. The model was validated using mono- and multimodal particle populations of a reference compound (KCl). The validation resulted in a good agreement between the simulated and experimental data. This suggests that the usage of the framework can provide a fast determination of the required PSD, reducing the number of experiments needed. © 2021 Elsevier B.V.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20402 - Chemical process engineering

Projekt

<a href="/cs/project/GX19-26127X" target="_blank" >GX19-26127X: Robotický nano-lékárník: Výrobní procesy budoucnosti pro personalisovaná terapeutika</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Powder Technology

ISSN

0032-5910

e-ISSN

1873-328X

Svazek periodika

395

Číslo periodika v rámci svazku

JAN 2022

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

743-757

Kód UT WoS článku

000718001100006

EID výsledku v databázi Scopus

2-s2.0-85117773563