Research Data Leeds Repository

Citation

Moldovan, Alexandru A. and Penchev, Radoslav and Hardcastle, Thomas and Janowiak, Jakub and Hammond, Robert and Maloney, Andrew and Connell, Simon D. (2021) Data associated with "Automated In Silico Energy Mapping of Facet-Specific Interparticle Interactions". University of Leeds. [Dataset] https://doi.org/10.5518/1045

Dataset description

Dataset for paracetamol-paracetamol surface intereactions including morphological data. Particle–particle interactions impact the processability and performance of drug products. Faceted particulates exhibit distinct surface chemistries that affect their adhesion, causing downstream processing challenges such as poor flow, punch sticking, and compaction. Currently, there is a lack of tools to assist formulators in predicting these challenges based on particle properties. Here, we present a methodology for navigating the energy landscape of interparticle interactions. We used molecular mechanics to calculate the interactions between slabs of molecules representing distinct facets. The workflow enables a rapid assessment of the total energy landscape between interacting particles, providing insight into the effects of different surface chemistries and molecular topologies. Previously, the strongest interaction (lowest energy) was used to calculate the propensity to adhere, but we demonstrate that this does not always predict an accurate description of the likely surface interactions. We chose paracetamol to demonstrate the application of this methodology. The most cohesive facets were (101) and (10-1). Comparing surface interactions between particles allows a ranking of the most energetically compatible surfaces. The significance of this ranking and understanding how surface chemistry can impact interparticle interactions is a step toward assisting formulation decisions and improvements in product performance.

Keywords:	Surface, particles, adhesion, energy, surface interactions, paracetamol
Subjects:	H000 - Engineering > H800 - Chemical, process & energy engineering > H830 - Chemical process engineering F000 - Physical sciences > F300 - Physics
Divisions:	Faculty of Engineering and Physical Sciences > School of Chemical and Process Engineering Faculty of Engineering and Physical Sciences > School of Physics and Astronomy
Related resources:	Location Type https://doi.org/10.1021/acs.cgd.1c00674 Publication https://eprints.whiterose.ac.uk/194226/ Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	01 Sep 2022 12:37
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1015
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Moldovan, Alexandru A. https://orcid.org/0000-0003-2776-3879 University of Leeds https://ror.org/024mrxd33 ror Cambridge Crystallographic Data Centre https://ror.org/00zbfm828 ror Penchev, Radoslav Pfizer https://ror.org/04x4v8p40 ror Hardcastle, Thomas University of Leeds https://ror.org/024mrxd33 ror Cambridge Crystallographic Data Centre https://ror.org/00zbfm828 ror Janowiak, Jakub University of Leeds https://ror.org/024mrxd33 ror Hammond, Robert https://orcid.org/0000-0003-0691-7779 University of Leeds https://ror.org/024mrxd33 ror Maloney, Andrew https://orcid.org/0000-0002-2578-9293 Cambridge Crystallographic Data Centre https://ror.org/00zbfm828 ror Connell, Simon D. https://orcid.org/0000-0003-2500-5724 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: EPSRC Grant numbers: EP/L015285/1 Publication date: 2021 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: amoldovan@ccdc.cam.ac.uk Last Modified: 03 Sep 2024 10:49

Files

Documentation

ReadMe [1kB] ReadMe [1kB] ReadMe [1kB] Security: Anyone File name: ReadMe.md Content type: Documentation Description: Instructions on the dataset content, associated figures and how to access the files License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 1kB

Data

Convergence [3MB] Convergence [3MB] Convergence [3MB] Security: Anyone File name: Convergence_Data.zip Content type: Data Description: Stores the Convergence data for developing the model Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 3MB

Paracetamol Morphology [97kB] Paracetamol Morphology [97kB] Paracetamol Morphology [97kB] Security: Anyone File name: Para_Morphology.zip Content type: Data Description: Containts the data required to construct a particle morphology of paracetamol Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 97kB

Paracetamol vs Paracetamol Surface Interaction [4MB] Paracetamol vs Paracetamol Surface Interaction [4MB] Paracetamol vs Paracetamol Surface Interaction [4MB] Security: Anyone File name: Para_Para_Surface_Data.zip Content type: Data Description: Contains the data calculated for surface-surface interaction of paracetamol Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 4MB