The purpose of this study was to develop a predictive model of the amorphous stability of drugs with particular relevance for poorly water-soluble compounds. Twenty-five representative neutral poorly soluble compounds with a diverse range of physicochemical properties and chemical structures were systematically selected from an extensive library of marketed drug products. The physical stability of the amorphous form, measured over a 6 month period by the onset of crystallization of amorphous films prepared by melting and quench-cooling, was assessed using polarized light microscopy. The data were used as a response variable in a statistical model with calculated/predicted or measured molecular, thermodynamic, and kinetic parameters as explanatory variables. Several multiple linear regression models were derived, with varying balance between calculated/predicted and measured parameters. It was shown that inclusion of measured parameters significantly improves the predictive ability of the model. The best model demonstrated a prediction accuracy of 82% and included the following as parameters: melting and glass transition temperatures, enthalpy of fusion, configurational free energy, relaxation time, number of hydrogen bond donors, lipophilicity, and the ratio of carbon to heteroatoms. Good predictions were also obtained with a simpler model, which was comprised of easily acquired quantities: molecular weight and enthalpy of fusion. Statistical models are proposed to predict long-term amorphous drug stability. The models include readily accessible parameters, which are potentially the key factors influencing amorphous stability. The derived models can support faster decision making in drug formulation development.

Oligo(ε-caprolactone) and oligolactide were synthesized via ring-opening polymerization of cyclic esters in the presence of creatinine as initiators. Thus obtained oligomers were successfully used in the synthesis of novel polyurethane conjugates of norfloxacin. The structures of the polymers and conjugates were elucidated by means of MALDI-TOF MS, NMR and IR studies.

The objective of this study was to gain a quantitative understanding of the link between physicochemical properties and long-term and time-censored amorphous stability of poorly water-soluble drugs using parametric time-to-event modeling. Previously published data on amorphous stability and physicochemical properties of 25 structurally diverse neutral, poorly soluble compounds were used. To describe the general shape of the survival curve (probability of event at time >t), Constant, Gompertz, and Weibull hazard functions and their linear combinations were tested. For a selected Weibull hazard base model, the effect of each physicochemical covariate was investigated, with combined influence of enthalpy of fusion (Hf) and molecular weight (Mr) showing the highest statistical significance. The covariate model was used to simulate survival curves and calculate the median survival time for different values of Hf and Mr. It was found that a decrease in Hf or an increase in Mr contribute to longer survival times. The derived model equation was validated against external data sets consisting of 11 compounds. It showed better predictive ability than a previously published multiple linear regression model incorporating Hf and Mr. The proposed Weibull covariate model may assist in faster and more cost-effective decision making in the pre-formulation phase of drug development, where compound properties and appropriate drug formulation strategies are investigated.

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