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Modeling and Prediction of Amorphous Solid Dispersion Formation Using a Molecular Descriptor

Abstract

dc:description.abstract

<p>Poor aqueous solubility of an active pharmaceutical ingredient (API) is a significant hurdle during drug development. Delivering a drug in its amorphous solid-state is a potential method to overcome this issue, since the amorphous form has increased apparent aqueous solubility. However, the amorphous state is only metastable, and is thermodynamically driven to recrystallize. As a result, pure amorphous drugs are seldom used in marketed products. Intimately mixing a drug in its amorphous form with a polymer, known as an amorphous solid dispersion (ASD), has the potential to significantly extend the physical stability of the amorphous form, while maintaining the benefit of increased apparent solubility. However, ASDs remain poorly understood. As a result, ASDs are primarily developed using a trial and error approach, resulting in increased costs and extended time to market. A method for predicting the probability of successful formation of intimate mixtures of drug and polymer without recrystallization (a.k.a. dispersability) has the potential to reduce costs, shorten development time, and advance scientific understanding of ASDs.</p> <p>The central hypothesis of this work is that there exists a combination of materials properties that correlates with the probability that an ASD will form in PVPva. Since molecular descriptors are mathematical representations of properties of a molecule, it is hypothesized that they can be successfully applied to predict the formation of amorphous solid dispersions. Specifically, the molecular descriptor R3m was investigated as a tool for the prediction of ASD formation. The work presented herein addresses 3 primary aims: (1) investigating the statistical validity of the model by expanding the model to include 2 preparation methods and 2 concentrations, (2) advancing the understanding of the physicochemical meaning of the R3m descriptor to improve the interpretability of the descriptor, and (3) investigating the relationship between R3m and solubility.</p>

Degree

thesis:*
Name thesis:degree_name
PhD
Level thesis:degree_level
One-year Embargo
Discipline thesis:degree_discipline
Pharmaceutics
Year dc:date.available
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • DeBoyace, Kevin
Contributors dc:contributor
  • Peter L.D. Wildfong
  • Ira Buckner
  • Carl Anderson
  • Kenneth Morris
  • Tonglei Li

Subjects

dc:subject × 4

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Repository record dc:identifier
https://dsc.duq.edu/etd/1783
OAI identifier oai:identifier
oai:dsc.duq.edu:etd-2796

Chain of custody

source
Harvested from
Duquesne
Base URL
dsc.duq.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

DeBoyace, Kevin. Modeling and Prediction of Amorphous Solid Dispersion Formation Using a Molecular Descriptor. One-year Embargo thesis, 2019. https://dsc.duq.edu/etd/1783