@book{scholars15598,
            note = {cited By 14},
            year = {2021},
             doi = {10.1007/978-981-16-4365-1{$_8$}},
       publisher = {Springer Nature},
         journal = {Application of Ionic Liquids in Drug Delivery},
           title = {Design and Selection of Ionic Liquids Via COSMO for Pharmaceuticals and Medicine},
           pages = {137--164},
        abstract = {Ionic liquids (ILs) have been used significantly in pharmaceutics and medicine because of their exceptional {\^a}??green{\^a}?? properties and tailor-made physicochemical and biological properties. ILs can dissolve many important drug molecules at ambient conditions, which are sparingly soluble in water and other conventional organic solvents. However, the selection of potential ILs from thousands of anion-cation combinations is quite challenging. To address this limitation, various computation methods have been used to screen appropriate ILs for solubility and applications of a specific drug molecule. Among those methods, the conductor-like screening model (COSMO)-a continuum solvation model based on quantum chemistry-is found remarkably effective in screening suitable ILs for pharmaceutical applications due to its excellent capability in predicting physical and chemical properties. The advantage of these optimizing tools is that only the molecular structure is enough for prior predictions. Solubility, activity coefficient, selectivity, free energies, partition coefficient, and octanol-water coefficient are few properties that can be easily predicted. This chapter presents a detailed discussion on the COSMO screening of cations and anions of ILs for various applications and highlighting the advantages of this predictive tool. {\^A}{\copyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121967043&doi=10.1007\%2f978-981-16-4365-1\%5f8&partnerID=40&md5=527da2e9a153cb4494ecc9c9094aa909},
            isbn = {9789811643651; 9789811643644},
          author = {Khan, H. W. and Elgharbawy, A. A. M. and Bustam, A. and Moniruzzaman, M.}
}