Effect of Copolymer Properties on the Phase Behavior of Ibuprofen–PLA/PLGA Mixtures

Abstract

Prediction of compatibility of the active pharmaceutical ingredient (API) with the polymeric carrier plays an essential role in designing drug delivery systems and estimating their long-term physical stability. A key element in deducing API–polymer compatibility is knowledge of a complete phase diagram, i.e., the solubility of crystalline API in polymer and mutual miscibility of API and polymer. In this work, the phase behavior of ibuprofen (IBU) with different grades of poly(D,L-lactide-co-glycolide) (PLGA) and polylactide (PLA), varying in composition of PLGA and molecular weight of PLGA and PLA, was investigated experimentally using calorimetry and computationally by the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state (EOS). The phase diagrams constructed based on a PC-SAFT EOS modeling optimized using the solubility data demonstrated low solubility at typical storage temperature (25 °C) and limited miscibility (i.e., presence of the amorphous–amorphous phase separation region) of IBU with all polymers studied. The ability of PC-SAFT EOS to capture the experimentally observed trends in the phase behavior of IBU–PLA/PLGA systems with respect to copolymer composition and molecular weight was thoroughly investigated and evaluated.

Can Pure Predictions of Activity Coefficients from PC-SAFT Assist Drug–Polymer Compatibility Screening?

“…This performance is opposite to that observed in this work for API–polymer systems. In the case of IBP–PLGA combinations, it appears that the large errors (which are not seen for the other API–PLGA systems) are due to the fact that PC-SAFT, irrespective of the specific API parametrization, is unable to capture the low experimental compatibility that is enhanced even by the experimentally observed AAPS. ,, However, for IBP–PLGA systems, PC-SAFT with REF qualitatively correctly predicted a narrow AAPS region at high w IBP values close to unity, which would serve as a qualitative indicator of limited compatibility.…”

“…This is not an abnormal situation, since it appears that none of the available models provides numerically accurate and reliable pure predictions of the API solubility, including even the most progressive tools. ,, However, the question is how much (in)­accurate the PC-SAFT pure predictions are and whether they can be used at least for qualitative relative estimates, consisting of ranking polymers based on the predicted solubility and miscibility values. Since the pure k ij -free predictions for ASD have so far been rarely reported (e.g., in ref or in our previous studies − , ), it remains to address these questions in the current study.…”

“…12,28,43 However, the question is how much (in)accurate the PC-SAFT pure predictions are and whether they can be used at least for qualitative relative estimates, consisting of ranking polymers based on the predicted solubility and miscibility values. Since the pure k ij -free predictions for ASD have so far been rarely reported (e.g., in ref 32 or in our previous studies [36][37][38][39]44 ), it remains to address these questions in the current study.…”

Glass Transition and Structure of Organic Polymers from All-Atom Molecular Simulations

“…The motivation of this paper is to validate the computational setup for molecular-dynamics models of the glass transition temperatures and related structural properties for biocompatible polymers, especially relevant in the context of the design of amorphous drug formulations. − Knowledge on the glass transition temperature is one of the key prerequisites for constructing complete drug–polymer phase diagrams, which enable the identification of optimal polymeric carriers for a given drug . MD-powered estimation of the glass transition of such materials would thus represent an important element in fully in silico predictions of the phase behavior of drug–polymer systems.…”

“…23−25 Knowledge on the glass transition temperature is one of the key prerequisites for constructing complete drug−polymer phase diagrams, which enable the identification of optimal polymeric carriers for a given drug. 24 MD-powered estimation of the glass transition of such materials would thus represent an important element in fully in silico predictions of the phase behavior of drug− polymer systems. We also demonstrate the potential adverse effects of unsuitable simulation setups of molecular dynamics simulations and point the reader's attention to the computational uncertainties that should be expected upon performing such predictive simulations.…”