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Molecular modelling–driven formulation design for targeted pulmonary drug delivery

  • Karan Goel
  • , Thakur Gurjeet Singh
  • , Keshav Raj Paudel
  • , Ronan MacLoughlin
  • , Mohammad S. Islam
  • , Mangesh Pradeep Kulkarni
  • , Kamal Dua
  • , Somdutt Mujwar
  • Chitkara University
  • Western Sydney University
  • Aerogen
  • University of Technology Sydney

Research output: Contribution to journalReview articlepeer-review

Abstract

Molecular modelling an impactful and trending approach for rational design of pulmonary drug delivery systems. In particular, in silico techniques can screen candidates and optimise formulations early, reducing trial-and-error and improving the likelihood of clinical translation. Therefore, this review highlights the application of in silico methods in critical formulation decisions for achieving targeted delivery, controlled release, and enhanced therapeutic efficacy in the lungs. The application of molecular docking, quantum mechanics/molecular mechanics, and molecular dynamics simulations to predict drug–excipient and drug–polymer interactions to optimize particle engineering and improve stability of resulting formulations. Modelling of active pharmaceutical ingredients with carriers, surfactants, and nanocarriers such as liposomes, polymeric nanoparticles, and micelles was designed for deep lung delivery. The integration of molecular modelling approaches for predicting the physicochemical properties based on pharmacokinetic modelling for analysing their behaviour, regional lung deposition, and systemic exposure at the molecular level was explored. Challenges such as model validation, treatment of complex biological interfaces, and data–driven personalization are critically analysed. Overall, the article underscores molecular modelling as a crucial component of next-generation, data-based formulation development pipelines for targeted pulmonary drug delivery and outlines future opportunities for AI- and machine-learning–augmented design.

Original languageEnglish
Article number126873
JournalInternational Journal of Pharmaceutics
Volume697
DOIs
StatePublished - 20 May 2026
Externally publishedYes

Keywords

  • Computational Pharmacokinetics
  • In silico Formulation Design
  • Molecular Modelling
  • Nanocarriers
  • Pulmonary Drug Delivery

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