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Advanced Drug Delivery Reviews (v.58, #12-13)
Mathematical modeling and simulation of drug release from microspheres: Implications to drug delivery systems by Davis Yohanes Arifin; Lai Yeng Lee; Chi-Hwa Wang (pp. 1274-1325).
This article aims to provide a comprehensive review of existing mathematical models and simulations of drug release from polymeric microspheres and of drug transport in adjacent tissues. In drug delivery systems, mathematical modeling plays an important role in elucidating the important drug release mechanisms, thus facilitating the development of new pharmaceutical products by a systematic, rather than trial-and-error, approach. The mathematical models correspond to the known release mechanisms, which are classified as diffusion-, swelling-, and erosion-controlled systems. Various practical applications of these models which explain experimental data are illustrated. The effect of γ-irradiation sterilization on drug release mechanism from erosion-controlled systems will be discussed. The application of existing models to nanoscale drug delivery systems specifically for hydrophobic and hydrophilic molecules is evaluated. The current development of drug transport modeling in tissues utilizing computational fluid dynamics (CFD) will also be described.
Keywords: Release mechanism; Polymeric system; Diffusion; Swelling; Erosion; Irradiation; Transport; Tissue; Brain; Computational fluid dynamics
Quantitative structure–pharmacokinetic/pharmacodynamic relationships by Donald E. Mager (pp. 1326-1356).
Quantitative structure–activity relationships have long been considered a vital component of drug discovery and development, providing insight into the role of molecular properties in the biological activity of similar and unrelated compounds. Recognition that in vitro bioassay and/or pre-clinical activity are insufficient for anticipating which compounds are suitable leads for further development has shifted the focus toward integrated pharmacokinetic (PK) and pharmacodynamic (PD) processes. Over the last decade, considerable progress has been made in constructing empirical and mechanistic quantitative structure–PK relationships (QSPKR), as well as diverse mechanism-based pharmacodynamic models of drug effects. In this review, traditional and contemporary approaches to developing QSPKR models are discussed, along with selected examples of attempts to couple QSPKR and pharmacodynamic models to anticipate the intensity and time-course of the pharmacological effects of new or related compounds, or quantitative structure–pharmacodynamic relationships modeling. Such models are in accordance with the goals of systems biology and the ideal of designing drugs and delivery systems from first principles.
Keywords: Absorption; Distribution; Metabolism; Excretion; Protein binding; Pharmacokinetic/pharmacodynamic modeling; QSAR; QSPR; Molecular modeling
Liposomal drug transport: A molecular perspective from molecular dynamics simulations in lipid bilayers by Tian-Xiang Xiang; Bradley D. Anderson (pp. 1357-1378).
Computational methods to predict drug permeability across biomembranes prior to synthesis are increasingly desirable to minimize the investment in drug design and development. Significant progress in molecular dynamics (MD) simulation methodologies applied to lipid bilayer membranes, for example, is making it possible to move beyond characterization of the membranes themselves to explore various thermodynamic and kinetic processes governing membrane binding and transport. Such methods are also likely to be directly applicable to the design and optimization of liposomal delivery systems. MD simulations are particularly valuable in addressing issues that are difficult to explore in laboratory experiments due to the heterogeneity of lipid bilayer membranes at the molecular level. Insights emerging from MD simulations are contributing to an understanding of which regions within bilayers are most and least favored by solutes at equilibrium as the solute structure is varied, local diffusivities of permeants, and the origin of the amplified selectivity to permeant size imposed by lipid bilayer membranes, particularly as changes in composition increase acyl chain ordering.
Keywords: Membrane transport; Drug permeability; Diffusion; Partition coefficients; Computer simulations; Membrane binding
Hydrogels in controlled release formulations: Network design and mathematical modeling by Chien-Chi Lin; Andrew T. Metters (pp. 1379-1408).
Over the past few decades, advances in hydrogel technologies have spurred development in many biomedical applications including controlled drug delivery. Many novel hydrogel-based delivery matrices have been designed and fabricated to fulfill the ever-increasing needs of the pharmaceutical and medical fields. Mathematical modeling plays an important role in facilitating hydrogel network design by identifying key parameters and molecule release mechanisms. The objective of this article is to review the fundamentals and recent advances in hydrogel network design as well as mathematical modeling approaches related to controlled molecule release from hydrogels. In the first section, the niche roles of hydrogels in controlled release, molecule release mechanisms, and hydrogel design criteria for controlled release applications are discussed. Novel hydrogel systems for drug delivery including biodegradable, smart, and biomimetic hydrogels are reviewed in the second section. Several mechanisms have been elucidated to describe molecule release from polymer hydrogel systems including diffusion, swelling, and chemically-controlled release. The focus of the final part of this article is discussion of emerging hydrogel delivery systems and challenges associated with modeling the performance of these devices.
Keywords: Hydrogel; Drug delivery; Modeling; Controlled release; Diffusion; Degradation
Application of data mining approaches to drug delivery by Sean Ekins; Jun Shimada; Cheng Chang (pp. 1409-1430).
Computational approaches play a key role in all areas of the pharmaceutical industry from data mining, experimental and clinical data capture to pharmacoeconomics and adverse events monitoring. They will likely continue to be indispensable assets along with a growing library of software applications. This is primarily due to the increasingly massive amount of biology, chemistry and clinical data, which is now entering the public domain mainly as a result of NIH and commercially funded projects. We are therefore in need of new methods for mining this mountain of data in order to enable new hypothesis generation. The computational approaches include, but are not limited to, database compilation, quantitative structure activity relationships (QSAR), pharmacophores, network visualization models, decision trees, machine learning algorithms and multidimensional data visualization software that could be used to improve drug delivery after mining public and/or proprietary data. We will discuss some areas of unmet needs in the area of data mining for drug delivery that can be addressed with new software tools or databases of relevance to future pharmaceutical projects.
Keywords: Data mining; Drug delivery; QSAR; Pharmacophore; Networks; Transporters; Modeling; Predictions; Systems biology; Databases
Pharmacophore-based discovery of ligands for drug transporters by Cheng Chang; Sean Ekins; Praveen Bahadduri; Peter W. Swaan (pp. 1431-1450).
The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and the challenges encountered with current approaches are discussed.
Keywords: Pharmacophore; QSAR; Transporter; Ligand; Substrate; Inhibitor; Database screening; ADME