The role of multiscale computational approaches for rational design of conventional and nanoparticle oral drug delivery systems

Abstract

Multiscale computational modeling of drug delivery systems (DDS) is poised to provide predictive capabilities for the rational design of targeted drug delivery systems, including multi-functional nanoparticles. Realistic, mechanistic models can provide a framework for understanding the fundamental physico-chemical interactions between drug, delivery system, and patient. Multiscale computational modeling, however, is in its infancy even for conventional drug delivery. The wide range of emerging nanotechnology systems for targeted delivery further increases the need for reliable in silico predictions. This review will present existing computational approaches at different scales in the design of traditional oral drug delivery systems. Subsequently, a multiscale framework for integrating continuum, stochastic, and computational chemistry models will be proposed and a case study will be presented for conventional DDS. The extension of this framework to emerging nanotechnology delivery systems will be discussed along with future directions. While oral delivery is the focus of the review, the outlined computational approaches can be applied to other drug delivery systems as well.

Figure 1

The drug delivery process as is spans across multiple spatial scales.

Figure 2

A framework for multiscale modeling of entire drug delivery systems using information from drug and vehicle properties, disease pathology, and patient characteristics.

Figure 3

Classification of computational approaches of polymeric drug delivery systems.

Figure 4

An illustration of receptor mediated endocytosis process of particle uptake as modeled by Gao and co-workers (Gao et al 2005) (a) Ligands on the particle bind to receptors on initially uniformly distributed receptors on the membrane causing diffusive movement of the mobile receptors (b) The receptor density distribution, ξ(s,t), in the membrane becomes nonuniform upon ligand-receptor binding; the receptor density is depleted in the near vicinity of the binding area and induces diffusion of receptors toward the binding site. 2*a(t) is the contact area between the particle and the membrane. Gao H, Shi W, Freund LB. 2005. Mechanics of receptor-mediated endocytosis. PNAS 102: 9469–74. Copyright © 2005 National Academy of Sciences, USA.

Figure 5

Simulation of the polymeric coating (EudraGI tract^® S-100) of Asacol^® (a) enlarged section of the interface between the drug core and coating at t = 0 h; (b) after 2 h in the stomach fluid at pH = 1.2; (c) after 1 h in the intestinal fluid I (proximal) at pH = 6.8; (d) after 15 min in the intestinal fluid II (distal) at pH = 7.2; (e) Coating thickness dissolution in pH 1.2, 6.8 and 7.2 gastrointestinal buffers.

Figure 6

(a) The average drug release in the distal intestine versus the distal transit time for subjects with UC. Each data point is the average of the cumulative drug release of all the pH values randomly sampled at the end of the gastric and intestinal residence time. (b) The average drug release versus pH in the distal intestine for UC patients. The error bars represent the 95% confidence interval with respect to the pH and intestinal transit time variability, respectively.