Literature DB >> 25380027

Formulation pre-screening of inhalation powders using computational atom-atom systematic search method.

Vasuki Ramachandran1, Darragh Murnane, Robert B Hammond, Jonathan Pickering, Kevin J Roberts, Majeed Soufian, Ben Forbes, Sara Jaffari, Gary P Martin, Elizabeth Collins, Klimentina Pencheva.   

Abstract

The synthonic modeling approach provides a molecule-centered understanding of the surface properties of crystals. It has been applied extensively to understand crystallization processes. This study aimed to investigate the functional relevance of synthonic modeling to the formulation of inhalation powders by assessing cohesivity of three active pharmaceutical ingredients (APIs, fluticasone propionate (FP), budesonide (Bud), and salbutamol base (SB)) and the commonly used excipient, α-lactose monohydrate (LMH). It is found that FP (-11.5 kcal/mol) has a higher cohesive strength than Bud (-9.9 kcal/mol) or SB (-7.8 kcal/mol). The prediction correlated directly to cohesive strength measurements using laser diffraction, where the airflow pressure required for complete dispersion (CPP) was 3.5, 2.0, and 1.0 bar for FP, Bud, and SB, respectively. The highest cohesive strength was predicted for LMH (-15.9 kcal/mol), which did not correlate with the CPP value of 2.0 bar (i.e., ranking lower than FP). High FP-LMH adhesive forces (-11.7 kcal/mol) were predicted. However, aerosolization studies revealed that the FP-LMH blends consisted of agglomerated FP particles with a large median diameter (∼4-5 μm) that were not disrupted by LMH. Modeling of the crystal and surface chemistry of LMH identified high electrostatic and H-bond components of its cohesive energy due to the presence of water and hydroxyl groups in lactose, unlike the APIs. A direct comparison of the predicted and measured cohesive balance of LMH with APIs will require a more in-depth understanding of highly hydrogen-bonded systems with respect to the synthonic engineering modeling tool, as well as the influence of agglomerate structure on surface-surface contact geometry. Overall, this research has demonstrated the possible application and relevance of synthonic engineering tools for rapid pre-screening in drug formulation and design.

Entities:  

Keywords:  budesonide; de-agglomeration; fluticasone propionate; in silico formulation design; inhalation drug delivery; inter-particle interaction; laser diffraction; molecular and synthonic modeling; powder dispersion analysis; salbutamol; α-lactose monohydrate

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Substances:

Year:  2014        PMID: 25380027     DOI: 10.1021/mp500335w

Source DB:  PubMed          Journal:  Mol Pharm        ISSN: 1543-8384            Impact factor:   4.939


  5 in total

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Authors:  Eleonora Maretti; Luca Costantino; Francesca Buttini; Cecilia Rustichelli; Eliana Leo; Eleonora Truzzi; Valentina Iannuccelli
Journal:  Drug Deliv Transl Res       Date:  2019-02       Impact factor: 4.617

2.  A Digital Mechanistic Workflow for Predicting Solvent-Mediated Crystal Morphology: The α and β Forms of l-Glutamic Acid.

Authors:  Thomas D Turner; Neil Dawson; Martin Edwards; Jonathan H Pickering; Robert B Hammond; Robert Docherty; Kevin J Roberts
Journal:  Cryst Growth Des       Date:  2022-04-11       Impact factor: 4.010

3.  Relating Crystal Structure to Surface Properties: A Study on Quercetin Solid Forms.

Authors:  Panayiotis Klitou; Ian Rosbottom; Vikram Karde; Jerry Y Y Heng; Elena Simone
Journal:  Cryst Growth Des       Date:  2022-09-19       Impact factor: 4.010

4.  Molecular, Solid-State and Surface Structures of the Conformational Polymorphic Forms of Ritonavir in Relation to their Physicochemical Properties.

Authors:  Chang Wang; Ian Rosbottom; Thomas D Turner; Sydney Laing; Andrew G P Maloney; Ahmad Y Sheikh; Robert Docherty; Qiuxiang Yin; Kevin J Roberts
Journal:  Pharm Res       Date:  2021-05-19       Impact factor: 4.200

5.  Identification of Protein-Excipient Interaction Hotspots Using Computational Approaches.

Authors:  Teresa S Barata; Cheng Zhang; Paul A Dalby; Steve Brocchini; Mire Zloh
Journal:  Int J Mol Sci       Date:  2016-06-01       Impact factor: 5.923

  5 in total

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