Controlled drug delivery has been attracting a great deal of attention in the medical community for years as an efficient way of providing treatment for a wide class of diseases. The common principle on which various drug delivery devices are based is mass transfer of the given drug toward particular organs, in which either the mass transfer rate, or place, or both are prescribed according to certain medical protocols. Much progress has been achieved in the design and development of various controlled drug delivery systems, and many people routinely take medicine designed for controlled release. Mathematical modeling of drug delivery systems is very important because a successful model can provide a better understanding and a quantitative description of the physical, chemical and biological processes governing the performance of the systems. On the basis of this description, better controlled drug delivery systems can be designed. We hope that this collection of papers will result in an increased attention of applied mathematicians to this class of important mass transfer and control problems. We also hope that practitioners will become more aware of the mathematical results that can be useful. The papers differ in mathematical sophistication, ranging from models described by systems of ODEs to quite complex PDE problems. They consider quite a few different aspects of drug delivery thus introducing a significant portion of the field. Each paper has an extensive introduction that should make the paper understandable to an applied mathematician who is not an expert in drug delivery. A discussion of controlled drug delivery in cancer immunotherapy is presented in “Controlled Drug Delivery in Cancer Immunotherapy: Stability, Optimization, and Monte Carlo Analysis" by Minelli, Topputo, and Bernelli-Zazzera, who formulate and solve an optimal control problem and show that the control policy is effective even when the patient's initial conditions are uncertain. A hybrid model of cell population dynamics, where cells are discrete elements whose dynamics depend on continuous intracellular and extracellular processes, is developed in “Hybrid Model of Erythropoiesis and Leukemia Treatment with Cytosine Arabinoside" by Kurbatova, Bernard, Bessonov, Crauste, Demin, Dumontet, Fischer, and Volpert, to simulate the evolution of immature red blood cells in the bone marrow. The model is used to study normal and leukemic red blood cell production and treatment of leukemia. In “Quadratic Models to Fit Experimental Data of Paclitaxel Release Kinetics from Biodegradable Polymers," Blanchet, Delfour, and Garon validate three ODE models against experimental data in order to better understand drug release kinetics. A model for drug diffusion from a spherical polymeric drug delivery device is considered in “Asymptotic and Numerical Results for a Model of Solvent-Dependent Drug Diffusion through Polymeric Spheres" by McCue, Hsieh, Moroney, and Nelson. Here the solvent diffuses into the polymer, which transitions from a glassy to a rubbery state, thus resulting in a moving boundary problem. In “Model Reduction Strategies Enable Computational Analysis of Controlled Drug Release from Cardiovascular Stents," D'Angelo, Zunino, Porpora, Morlacchi, and Migliavacca deal with drug-eluting stents and consider a hierarchy of mathematical models ranging from a lumped ODE model to fully three-dimensional models for drug transfer in the artery. A gene delivery of nucleic acid to the cell nucleus problem is discussed in “Modeling the Early Steps of Cytoplasmic Trafficking in Viral Infection and Gene Delivery," in which Amoruso, Lagache, and Holcman focus on plasmid DNA and virus cytoplasmic trafficking. The editors thank all the authors and reviewers for their contributions to this collection.