Selecting Counterions to Improve Ionized Hydrophilic Drug Encapsulation in Polymeric Nanoparticles.

Abstract

Hydrophobic ion pairing (HIP) can successfully increase the drug loading and control the release kinetics of ionizable hydrophilic drugs, addressing challenges that prevent these molecules from reaching the clinic. Nevertheless, polymeric nanoparticle (PNP) formulation development requires trial-and-error experimentation to meet the target product profile, which is laborious and costly. Herein, we design a preformulation framework (solid-state screening, computational approach, and solubility in PNP-forming emulsion) to understand counterion-drug-polymer interactions and accelerate the PNP formulation development for HIP systems. The HIP interactions between a small hydrophilic molecule, AZD2811, and counterions with different molecular structures were investigated. Cyclic counterions formed amorphous ion pairs with AZD2811; the 0.7 pamoic acid/1.0 AZD2811 complex had the highest glass transition temperature (Tg; 162 °C) and the greatest drug loading (22%) and remained as phase-separated amorphous nanosized domains inside the polymer matrix. Palmitic acid (linear counterion) showed negligible interactions with AZD2811 (crystalline-free drug/counterion forms), leading to a significantly lower drug loading despite having similar log P and pKa with pamoic acid. Computational calculations illustrated that cyclic counterions interact more strongly with AZD2811 than linear counterions through dispersive interactions (offset π-π interactions). Solubility data indicated that the pamoic acid/AZD2811 complex has a lower organic phase solubility than AZD2811-free base; hence, it may be expected to precipitate more rapidly in the nanodroplets, thus increasing drug loading. Our work provides a generalizable preformulation framework, complementing traditional performance-indicating parameters, to identify optimal counterions rapidly and accelerate the development of hydrophilic drug PNP formulations while achieving high drug loading without laborious trial-and-error experimentation.