Knowledge-bases prediction of multicomponent forms of nevirapine

Abstract

Nevirapine (NVP), an antiretroviral drug used in AIDS/HIV treatment [1], is a class II drug, according to the Biopharmaceutical Classification System (BCS) [2], presenting low solubility and high permeability. The low solubility leads to formulation difficulties and a considerable decrease in the bioavailability. A strategy to improve physicochemical properties, including the solubility, is the preparation of modified crystals of NVP. A crystalline modification frequently used is based on the inclusion of other molecules in the drug crystalline structure, forming multicomponent structures. NVP presents a rigid amide group and it is expected an NVP-co-former interaction in this point [3]. Among the possible multicomponent structures are the cocrystals, salts, solvates and eutectic systems. The process to obtain multicomponent crystalline forms of a drug could be an expensive and long-term process, since there is an infinity of possible co-former molecules [4]. So, it is necessary to optimize and to rationalize the co-formers selection using knowledge-based supramolecular chemistry. This work proposes a rational strategy in the design of the crystalline modifications based on the utilization of statistic tools developed by the Cambridge Crystallographic Data Centre (CCDC) [5], in order to predict the molecular complementarity between NVP and other molecular entities [6-8]. The prediction method validation is obtained through the preparation of multicomponent solids (solvates, cocrystals and eutectic systems) using a variety of crystallization techniques. The materials are characterized by X-ray diffraction, thermal analysis, optical microscope, Raman spectroscopy and, solid-state nuclear magnetic resonance spectroscopy