Search

The use of methods at molecular scale for the discovery of new potential active ligands, as well as previously unknown binding sites for target proteins, is now an established reality. Literature offers many successful stories of active compounds developed starting from insights obtained in silico and approved by Food and Drug Administration (FDA). One of the most famous examples is raltegravir, a HIV integrase inhibitor, which was developed after the discovery of a previously unknown transient binding area thanks to molecular dynamics simulations. Molecular simulations have the potential to also improve the design and engineering of drug delivery devices, which are still largely based on fundamental conservation equations. Although they can highlight the dominant release mechanism and quantitatively link the release rate to design parameters (size, drug loading, et cetera), their spatial resolution does not allow to fully capture how phenomena at molecular scale influence system behavior. In this scenario, the “computational microscope” offered by simulations at atomic scale can shed light on the impact of molecular interactions on crucial parameters such as release rate and the response of the drug delivery device to external stimuli, providing insights that are difficult or impossible to obtain experimentally. Moreover, the new paradigm brought by nanomedicine further underlined the importance of such computational microscope to study the interactions between nanoparticles and biological components with an unprecedented level of detail. Such knowledge is a fundamental pillar to perform device engineering and to achieve efficient and safe formulations. After a brief theoretical background, this review aims at discussing the potential of molecular simulations for the rational design of drug delivery systems., Journal of Controlled Release, 332, ISSN:0168-3659, ISSN:1873-4995

In this work we present a method to investigate the fluid-dynamics of a 3D, real-scale spiral jet mill when caking is occurring. CFD simulations are employed to deeply study the pressure and the velocity fields of the gas phase when the nozzles inlet pressure and the chamber diameter are varied to mimic the condition generated by the aggregates formation during the micronizaton process. The computational model is built replicating the experimental observation consisting in the fact that most of the crusts form on the outer wall of the chamber. Simulations underline that caking causes the deterioration of the classification capabilities of the system if the gas mass flow rate is kept constant at nozzles, allowing larger particles for escaping the system. It is shown that it is possible to mitigate this phenomenon by gradually reducing the gas mass-flow rate to keep constant the nozzles absolute pressure. This keeps unchanged the fluid spin ratio and the classification characteristics when caking is advancing.

Computational techniques are now a complementary tool to experimental activity for a comprehensive characterization of biomedical devices for drug delivery. They allow achieving a mechanistic and fundamental understanding of the systems of interest and rationalizing experimental data. The acquired knowledge can be fruitfully employed to optimize the design of the device, which does not behave as a “black box” anymore, to obtain the desired performances. Starting from the seminal contribution of Prof. Takeru Higuchi with the well-known Higuchi equation in 1961, modeling of drug delivery devices has now embraced not only a wide range of systems but a likewise variety of computational techniques. This chapter aims at providing to the interested reader a brief overview of the available approaches employed in the literature, along with specific examples of applications on system of potential interest for spinal cord injury repair.

The advent of nanomedicine brought a new paradigm in the biomedical field, introducing novel health care solutions based on nanosized carriers. In particular, nanoparticles attracted a lot of interest as devices for drug and vaccine delivery, imaging and diagnostic purposes. By virtue of their size (which ranges from 1 to 1000 nm and thus comparable to molecules of biological interest, like proteins), such nanocarriers exhibit some peculiar features that make nanomedicine a unique discipline. Indeed, nanoparticles can spread all over the body (including cells and organelles) and when injected in body fluids they interact with biological components (such as proteins, carbohydrates, small molecules, etc.). This aspect cannot be underestimated, since it can lead to unpredictable toxic effects as well as substantial deviations from the expected cellular uptake. In addition, nanoparticles must be designed so that they mainly target the area of interest (e.g., cancer), avoiding accumulation and drug release in healthy organs. This chapter aims at answering the following question: how can first principles mathematical modeling deal with the new challenges and issues introduced by nanomedicine?

This chapter represents a brief introduction to the available approaches aimed at modeling the degradation of bioresorbable polymers. The mechanism behind degradation kinetics, which is due to hydrolysis, and the main factors affecting degradation rate are explained. Then, the computational methods offered by the literature to quantitatively describe the degradation of bioresorbable polymers are addressed.

A review is presented of the main types of bioresorbable or bioabsorbable materials used in medical applications such as drug delivery. Groups discussed include aliphatic polyesters, polyanhydrides, poly(ortho esters) (POE), polyphosphazenes, poly(amino acids) and ‘pseudo’ poly(amino acids), polyalkylcyanoacrylates, poly(propylene fumarate) (PPF), poloxamers, poly( p -dioxanone) (PPDO) and polyvinyl alcohol (PVA).

Established polymer processing techniques are reviewed and the particular challenges in applying them successfully to biopolymers are examined. Mixing, molding, shaping, calendering, coating, foaming and solvent casting processes are examined. Problem areas, such as electrospinning, are investigated.