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Computational modeling for formulation design. | LitMetric

Computational modeling for formulation design.

Drug Discov Today

Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India. Electronic address:

Published: March 2019

AI Article Synopsis

  • Formulation design is a critical phase in drug development, involving extensive experimental work to select excipients and predict factors like solubility and drug release.
  • Key steps include assessing encapsulation efficiency and drug absorption, alongside understanding nanoparticle formation.
  • Utilizing advanced computational tools like QSARs and PBPK modeling can streamline the process, helping identify product issues and enhance understanding of complex formulations efficiently and cost-effectively.

Article Abstract

Formulation design is an important phase in the drug development process. However, this process at an experimental level requires exhaustive experimental work. Excipient selection, prediction of solubility, encapsulation efficiency, release patterns, drug absorption, stability, and mechanism of nanoparticle formation are some of the essential steps in formulation design. The use of various computational tools, including quantitative structure-activity relationships (QSARs), molecular modeling, molecular mechanics, discrete element modeling, finite element method, computational fluid dynamics, and physiologically based pharmacokinetics (PBPK) modeling, help in the identification of drug product inadequacies and to recommend avenues for understanding complex formulation design in less time with lower investment. Here, we focus on computational modeling tools used in formulation design and its applications.

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Source
http://dx.doi.org/10.1016/j.drudis.2018.11.018DOI Listing

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