A NEW MOLECULAR DESCRIPTOR FOR EVALUATING COMPONENT COMPATIBILITY OF PHARMACEUTICAL FORMS

Abstract

Abstract: The chemical diversity of the components of modern dosage forms, the intensity of their pharmacological study and the development of methods for predicting the optimal composition bring to the fore the task of developing new effective molecular descriptors that most fully reflect the physicochemical properties of molecules. At the same time, their creation should not be accompanied by laborious experiments or expensive complex calculations. Based on the analysis of the electronic structure of the model group of excipients, we made an attempt to theoretically substantiate the new molecular descriptor. For this, we set the task of calculating known and introducing new descriptors that characterize the structural features of excipients and allow combining chemically different molecules within a single predictive model. Only this approach can provide a reliable explanation of the phenomenon of technological isosteria (different structures - the same properties) and will allow identifying molecular descriptors, the change of which affects the change in the properties of the dosage form in the required direction. An accurate assessment of the hydrophilicity of molecules is the key to describing their behavior in combined heterogeneous media - the intestinal and gastric walls. Traditional methods of assessment (solubility in the "water-octanol" system) are laborious and, in the case of several tens of compounds, involve a separate expensive practical task, often giving results that are difficult to reproduce. Evaluation of the hydrophilicity of materials of polymer nature by this method is impossible. At the same time, the main components of the DF are these polymer structures of varying degrees of complexity. Therefore, the tasks of evaluative forecasting of the mutual influence of polymers - the components of the DF - and selecting of a cost-effective method for determining their optimal composition have a high degree of relevance.