Utilization of advanced machine learning models for analysis of pharmaceutical cocrystals by prediction of solubility parameters using Dragonfly algorithm optimization.

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Bibliographic Details
Title: Utilization of advanced machine learning models for analysis of pharmaceutical cocrystals by prediction of solubility parameters using Dragonfly algorithm optimization.
Authors: Alotaibi HF; Department of Pharmaceutical Sciences, College of Pharmacy, Princess Nourah Bint AbdulRahman University, 11671, Riyadh, Saudi Arabia. Hfalotaibi@pnu.edu.sa., AlRamadneh TN; Faculty of Allied Medical Sciences, Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, Jordan., Heera MS; Department of Computer Science and Application, Faculty of Computer Science and Application, Gokul Global University, Sidhpur, Gujarat, India., Yadav A; Department of Computer Engineering and Application, GLA University Mathura, Bharthia, 281406, India., Shakir AK; Computer Technical Engineering, College of Technical Engineering, The Islamic university, Najaf, Iraq., Ramachandran T; Department of Mechanical Engineering, School of Engineering and Technology, JAIN (Deemed to be University), Bangalore, Karnataka, India., Mishra S; Department of Pharmacology, IMS and SUM Hospital, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, 751003, India., Tailor NK; University Institute of Pharma Sciences, Chandigarh University, Mohali, Punjab, India., Singhal D; Centre for Research Impact and Outcome, Chitkara University, Rajpura, Punjab, India.; Sharda School of Bio-Science and Technology, Sharda University, Greater Noida, India.
Source: Scientific reports [Sci Rep] 2026 Jun 19. Date of Electronic Publication: 2026 Jun 19.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2045-2322
DOI:10.1038/s41598-026-58509-8