Zobrazeno 1 - 10
of 289
pro vyhledávání: '"Alastair J, Florence"'
Autor:
Weiwei Tang, Taimin Yang, Cristian A. Morales-Rivera, Xi Geng, Vijay K. Srirambhatla, Xiang Kang, Vraj P. Chauhan, Sungil Hong, Qing Tu, Alastair J. Florence, Huaping Mo, Hector A. Calderon, Christian Kisielowski, Francisco C. Robles Hernandez, Xiaodong Zou, Giannis Mpourmpakis, Jeffrey D. Rimer
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-13 (2023)
Modifiers of diverse materials exhibit structures or compositions that differ from a solute molecule but often contain similar functional motifs that facilitate molecular recognition for modifier binding to crystal surfaces. Here the authors examine
Externí odkaz:
https://doaj.org/article/df69d89fd0da487e9c6e2e319ccd24c3
Autor:
Naomi E. B. Briggs, John McGinty, Callum McCabe, Vishal Raval, Jan Sefcik, Alastair J. Florence
Publikováno v:
ACS Omega, Vol 6, Iss 28, Pp 18352-18363 (2021)
Externí odkaz:
https://doaj.org/article/a412277e466547b39e2bef22b41e98b9
Autor:
Stephanie Yerdelen, Yihui Yang, Justin L. Quon, Charles D. Papageorgiou, Chris Mitchell, Ian Houson, Jan Sefcik, Joop H. ter Horst, Alastair J Florence, Cameron J. Brown
Publikováno v:
Crystal Growth & Design. 23:681-693
Autor:
Matthew R. Wilkinson, Laura Pereira Diaz, Antony D. Vassileiou, John A. Armstrong, Cameron J. Brown, Bernardo Castro-Dominguez, Alastair J. Florence
Publikováno v:
Digital Discovery. 2:459-470
We present deep learning to predict the flowability of pharmaceuticals from microscopy images. This enables flowability assessments with smaller API quantities, saving experiment time and costs when material is limited during early drug development.
Autor:
Antony D. Vassileiou, Murray N. Robertson, Bruce G. Wareham, Mithushan Soundaranathan, Sara Ottoboni, Alastair J. Florence, Thoralf Hartwig, Blair F. Johnston
Publikováno v:
Digital Discovery. 2:356-367
A generic framework for enhancing an initial solubility prediction with ML, even with simple methods and a modestly sized, sparse dataset. We dissect the setup to show the model “locking on” to the target system as more data are made available.
Publikováno v:
International Journal of Pharmaceutics: X, Vol 2, Iss , Pp 100041- (2020)
The application of X-ray microtomography for quantitative structural analysis of pharmaceutical multi-particulate systems was demonstrated for commercial capsules, each containing approximately 300 formulated ibuprofen pellets. The implementation of
Externí odkaz:
https://doaj.org/article/45ce2643acb14cd9a10a403f8946cca5
Autor:
Siya Nakapraves, Monika Warzecha, Chantal L. Mustoe, Vijay Srirambhatla, Alastair J. Florence
Publikováno v:
Pharmaceutical Research. 39:3099-3111
Objective Particle shape can have a significant impact on the bulk properties of materials. This study describes the development and application of machine-learning models to predict the crystal shape of mefenamic acid recrystallized from organic sol
Publikováno v:
Crystals, Vol 11, Iss 7, p 738 (2021)
One of the most consequential assumptions of the classical theories of crystal nucleation and growth is the Szilard postulate, which states that molecules from a supersaturated phase join a nucleus or a growing crystal individually. In the last 20 ye
Externí odkaz:
https://doaj.org/article/4dadaf865b1d4b88aee423215d9a8308
Publikováno v:
Crystal Growth & Design. 22:2105-2116
Small-scale crystallization experiments (1-8 mL) are widely used during early-stage crystallization process development to obtain initial information on solubility, metastable zone width, as well as attainable nucleation and/or growth kinetics in a m
Publikováno v:
Acta Crystallographica Section E: Crystallographic Communications, Vol 72, Iss 1, Pp 53-55 (2016)
The title 1:1 co-crystal, C11H14O3·C6H6N2O [systematic name: butyl 4-hydroxybenzoate–isonicotinamide (1/1)], crystallizes with one molecule of butylparaben (BPN) and one molecule of isonicotinamide (ISN) in the asymmetric unit. In the crystal, BPN
Externí odkaz:
https://doaj.org/article/85f628bfb15d4ee4927cb79f7a714c83