TY - JOUR
T1 - Pregabalin solubility in supercritical green solvent
T2 - A comprehensive experimental and theoretical-intelligent assessment
AU - Gahtani, Reem M.
AU - Talath, Sirajunisa
AU - Hani, Umme
AU - Rahamathulla, Mohamed
AU - Khalid, Awais
N1 - Publisher Copyright:
© 2024
PY - 2024/8/15
Y1 - 2024/8/15
N2 - To find an effective formulation of active pharmaceutical ingredients through supercritical fluid (SCF) technology, it is essential to measure the solubility of API. The solubility of Pregabalin, a widely recognized anticonvulsant, in scCO2 was examined (T = 308 to 338 K and P = 120 to 300 bar). The mole fractions and solubility were determined within the range of 0.3 × 10-4 to 5.1 × 10-4 and 0.04 to 1.49 kg.m−3. Furthermore, the theoretical analysis of this process involved the application of diverse empirical models, a regular solution model, and an intelligent technique. All the models had satisfactory outcome, and the deviation is acceptable. The Jafari Nejad as an empirical model demonstrates superior accuracy (AARD% = 4.361 and Radj = 0.996). This research also investigated two crucial strengths of the empirical models; the ability to calculate the thermal enthalpies of the Pregabalin-scCO2 mixture and their extrapolation capability. The regular solution (AARD% = 10.34) and the artificial intelligence paradigms-based machine learning (mean AARD% = 1.17) exhibited the acceptable and highest accuracy, respectively.
AB - To find an effective formulation of active pharmaceutical ingredients through supercritical fluid (SCF) technology, it is essential to measure the solubility of API. The solubility of Pregabalin, a widely recognized anticonvulsant, in scCO2 was examined (T = 308 to 338 K and P = 120 to 300 bar). The mole fractions and solubility were determined within the range of 0.3 × 10-4 to 5.1 × 10-4 and 0.04 to 1.49 kg.m−3. Furthermore, the theoretical analysis of this process involved the application of diverse empirical models, a regular solution model, and an intelligent technique. All the models had satisfactory outcome, and the deviation is acceptable. The Jafari Nejad as an empirical model demonstrates superior accuracy (AARD% = 4.361 and Radj = 0.996). This research also investigated two crucial strengths of the empirical models; the ability to calculate the thermal enthalpies of the Pregabalin-scCO2 mixture and their extrapolation capability. The regular solution (AARD% = 10.34) and the artificial intelligence paradigms-based machine learning (mean AARD% = 1.17) exhibited the acceptable and highest accuracy, respectively.
KW - Drug delivery system
KW - Intelligent technique
KW - Pregabalin
KW - Regular solution model
KW - Solubility
KW - Supercritical solvent
UR - http://www.scopus.com/inward/record.url?scp=85197272255&partnerID=8YFLogxK
U2 - 10.1016/j.molliq.2024.125339
DO - 10.1016/j.molliq.2024.125339
M3 - Article
AN - SCOPUS:85197272255
SN - 0167-7322
VL - 408
JO - Journal of Molecular Liquids
JF - Journal of Molecular Liquids
M1 - 125339
ER -