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A computationally informed framework for lipid-based formulation developability: Integrating predictive models with

Callum D Ryan1, Joseph P O'Shea2, Brendan T Griffin1

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Summary
This summary is machine-generated.

This study developed a computational framework to optimize lipid-based formulations (LBFs) for poorly water-soluble drugs (PWSDs). It uses predictive models to guide formulation selection, reducing trial-and-error and accelerating drug development.

Keywords:
Computational predictionsDecision treesLipid-based formulationsPoorly soluble drugs

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Area of Science:

  • Pharmaceutical Sciences
  • Drug Delivery
  • Computational Chemistry

Background:

  • Poorly water-soluble drugs (PWSDs) present significant formulation challenges.
  • Traditional methods for selecting lipid-based formulations (LBFs) are empirical and time-consuming.
  • Efficient bio-enabling strategies are crucial for advancing PWSD development.

Purpose of the Study:

  • To introduce a computationally informed framework for streamlining LBF development.
  • To integrate predictive in silico tools for assessing LBF suitability.
  • To guide formulation decisions for PWSDs using a data-driven approach.

Main Methods:

  • Developed a framework combining in silico tools (food effect, lipid solubility, biopharmaceutical dose number predictions).
  • Screened a database of >200 FDA-approved oral drugs (2010-2023) using the computational framework.
  • Applied tailored strategies like lipophilic salt synthesis for challenging molecules.

Main Results:

  • The framework successfully classified drug candidates based on formulation risk.
  • Identified suitable LBF types (Type-I, Type-IIIa) for low- and medium-risk molecules.
  • Demonstrated the effectiveness of lipophilic salts for high-risk drugs with dose-loading and dose number limitations.

Conclusions:

  • The computational framework enables rapid, data-driven formulation decisions for PWSDs.
  • Reduces reliance on empirical methods, improving R&D efficiency.
  • Offers a practical roadmap for accelerating LBF adoption in early-stage drug development.