Recent Developments in Pharmaceutical Spray Drying: Modeling, Process Optimization, and Emerging Trends with Machine Learning
Waasif Wahab, Raya Alshamsi, Bouta Alharsousi, Manar Alnuaimi, Zaina Alhammadi, Belal Al-Zaitone, Kyriakos Kachrimanis · 2025
Read Recent Developments in Pharmaceutical Spray Drying: Modeling, Process Optimization, and Emerging Trends with Machine Learning by Waasif Wahab, Raya Alshamsi, Bouta Alharsousi, Manar Alnuaimi, Zaina Alhammadi, Belal Al-Zaitone, Kyriakos Kachrimanis (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12736995.txt.
Description
Wahab and colleagues published in twenty twenty-five a review of spray drying methods for making drug powders. Spray drying turns liquid feed into fine dry powder in one step. Powder traits depend heavily on process settings chosen by engineers. The review covers modeling advances and current challenges in the field. Fluid dynamics simulations are the standard modeling tool today. Those models cost much computing time and can misfit complex real conditions.
Machine learning models have recently joined the modeler's toolkit. They predict well but depend on high-quality training data. New formulations or settings can still trip them up. The authors discuss hybrids that merge learning with fluid simulations. Digital twins, transfer learning, and explainable methods also feature. They see machine assistance as the field's emerging direction.
Catalog record
| CREATOR | Waasif Wahab, Raya Alshamsi, Bouta Alharsousi, Manar Alnuaimi, Zaina Alhammadi, Belal Al-Zaitone, Kyriakos Kachrimanis |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 97 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |