Nanotech 2010

Harnessing Molecular Modeling to Predict Drug Miscibility in Nanoparticles and Solvents

J. DeJoannis, L. Subramanian
Accelrys Inc., US

Keywords: solubility, drugs, excipients, modeling, simulation


Optimizing the functionalization of polymers for nanoparticles and other drug delivery systems is time consuming and costly, but has the potential to open the pipeline to poorly soluble compounds. One option is to leverage molecular modeling as a screening aid by employing one of the oldest and simplest ideas in formulation science: the Hildebrand solubility parameter. Creating successful mixtures requires the disruption of the cohesive forces that bind pure components together and is best attained when the constituents have similar cohesive properties. Hansen and others have taken the solubility parameter into a multidimensional space to more fully account for the different origins of cohesive forces such as hydrogen bonding, charge interactions and polarity. Molecular modeling is ideally suited to this task as decomposition of the energies is straightforward. We have simulated several typical polymer excipients, drug compounds and solvents using medium and high quality forcefields. Our results indicate methods for screening common processing solvents and polymers with respect to miscibility of a given API. In particular, we show how multidimensional solubility parameters can be used to suggest optimal functional groups and copolymer architectures as well as to create solvent mixtures that are suitable for industrial processing.
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