Random copolymers (RCPs) are macromolecules composed of two or more monomers with desirable functionalities randomly distributed along the polymer backbone. These compounds are instrumental to applications such as the oral delivery of poorly water-soluble drugs , where polymer-drug interplay governs the storage and delivery of active pharmaceutical ingredients. Although binary RCP systems have been studied extensively , there is currently very little guidance on understanding the kinetics of multicomponent copolymers , which are playing an ever-increasing role in imparting more unique physical properties. Herein , we demonstrate a systematic approach for simultaneously targeting exact molecular weights and chemical compositions of multimonomeric RCPs using reversible addition-fragmentation chain transfer free-radical (RAFT) polymerization. An illustrative system to showcase this procedure was studied and compared to a well-known macromolecule utilized in oral drug delivery (HPMCAS , or hydroxypropyl methyl cellulose acetate succinate. The relative reactivities at 70°C between monomer pairs were measured and employed to predict the feed ratio necessary for synthesizing well-defined compositions based on the Walling-Briggs model. Application of the Skeist equations addressed compositional drift and anticipated the general monomer incorporation distribution as a function of conversion , which was verified experimentally. This simple “controlled statistics” paradigm provides complementary synthetic and predictive tools for designing macromolecular chemical architectures with hierarchical control over spatially-dependent structure-property relationships for complex applications such as oral drug delivery.
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