Search

We demonstrate a novel application of the time-temperature superposition (TTS) principle to predict solute diffusivity D in glassy polymers using atomistic molecular dynamics simulations. Our TTS approach incorporates the Debye-Waller factor ⟨ u 2 ⟩, a measure of solute caging, along with concepts from thermodynamic scaling methods, allowing us to balance contributions to the dynamics from temperature and ⟨ u 2 ⟩ using adjustable parameters. Our approach rescales the solute mean-squared displacement curves at several temperatures into a master curve that approximates the diffusive dynamics at a reference temperature, effectively extending the simulation time scale from nanoseconds to seconds and beyond. With a set of "universal" parameters, this TTS approach predicts D with reasonable accuracy in a broad range of polymer/solute systems. Using TTS greatly reduces the computational cost compared to standard MD simulations. Thus, our method offers a means to rapidly and routinely provide order-of-magnitude estimates of D using simulations.

Various public health concerns can arise from the unintended leaching of additives and impurities from polymeric medical devices or food packaging, which is directly related to each solute's diffusivity D . Both experimental and simulation methods can be used to quantify D , but slow diffusion at physiologic temperature in glassy polymers can render these approaches impractical. Here, we investigate a simulation approach with the potential to more rapidly calculate D . Specifically, we examine links between dynamic localization, characterized by the Debye-Waller factor, ⟨ u 2 ⟩, and D in a variety of polymer/solute systems using atomistic molecular dynamics (MD) simulations. Using short, high-temperature MD simulations to estimate D at physiologic temperature, we find that the relation ln D ∝ 1/⟨ u 2 ⟩ quantitatively predicts D for small solutes and produces an upper-bound estimate of D for larger solutes. Upper-bound estimates are useful in certain contexts, and we compare our results with another approach for determining upper bounds, the Piringer model, to show where each method may be useful. Then, we examine a modified relation where the Debye-Waller factor is rescaled by the mode coupling temperature T c , which can produce better estimates of D if T c is carefully chosen. Last, we compare our approach with several other models that relate temperature or localized dynamics with diffusivity. Although each of these approaches can be used to model D across wide temperature ranges using one or more adjustable parameters, none of them are truly predictive in glassy polymers. Further developments are needed to predict the optimal values of the adjustable parameters a priori .

Many cardiovascular device alloys contain nickel, which if released in sufficient quantities, can lead to adverse health effects. However, in-vivo nickel release from implanted devices and subsequent biodistribution of nickel ions to local tissues and systemic circulation are not well understood. To address this uncertainty, we have developed a multi-scale (material, tissue, and system) biokinetic model. The model links nickel release from an implanted cardiovascular device to concentrations in peri-implant tissue, as well as in serum and urine, which can be readily monitored. The model was parameterized for a specific cardiovascular implant, nitinol septal occluders, using in-vitro nickel release test results, studies of ex-vivo uptake into heart tissue, and in-vivo and clinical measurements from the literature. Our results show that the model accurately predicts nickel concentrations in peri-implant tissue in an animal model and in serum and urine of septal occluder patients. The congruity of the model with these data suggests it may provide useful insight to establish nickel exposure limits and interpret biomonitoring data. Finally, we use the model to predict local and systemic nickel exposure due to passive release from nitinol devices produced using a wide range of manufacturing processes, as well as general relationships between release rate and exposure. These relationships suggest that peri-implant tissue and serum levels of nickel will remain below 5 μg/g and 10 μg/l, respectively, in patients who have received implanted nitinol cardiovascular devices provided the rate of nickel release per device surface area does not exceed 0.074 μg/(cm 2  d) and is less than 32 μg/d in total., Statement of Significance: The uncertainty in whether in-vitro tests used to evaluate metal ion release from medical products are representative of clinical environments is one of the largest roadblocks to establishing the associated patient risk. We have developed and validated a multi-scale biokinetic model linking nickel release from cardiovascular devices in-vivo to both peri-implant and systemic levels. By providing clinically relevant exposure estimates, the model vastly improves the evaluation of risk posed to patients by the nickel contained within these devices. Our model is the first to address the potential for local and systemic metal ion exposure due to a medical device and can serve as a basis for future efforts aimed at other metal ions and biomedical products., (Published by Elsevier Ltd.)

We have devised a novel diffuse interface formulation to model the development of chemical and physical inhomogeneities, i.e. microstructure, during the process of casting drug-eluting coatings. These inhomogeneities, which depend on the coating constituents and manufacturing conditions, can have a profound affect on the rate and extent of drug release, and therefore the ability of coated medical devices to function successfully. By deriving the model equations in a time-dependent reference frame, we find that it is computationally viable to probe a wide, physically relevant range of material and process quantities. To illustrate the application of the model, we have evaluated the impact of manufacturing solvent, coating thickness and evaporation rate on microstructure development. Our results suggest that modifying these process conditions can have a strong and nearly discontinuous effect on coating microstructure, and therefore on drug release. Further, we demonstrate that the model can be applied to processes that involve the incremental application of the coating in layers or passes. This new model formulation, which can also be used to predict the kinetics of drug release, provides a tool to elucidate and quantify the relationships between process variables, microstructure and performance. Establishing these relationships can reduce empiricism in materials selection and process design, providing a facile and efficient means to tailor the underlying microstructure and achieve a desired drug-release behavior., (Published by Elsevier Ltd.)

In recent years, traditional rigid materials have been replaced with softer elastomers in intraocular lenses to minimize the size of the required surgical incision, thereby reducing patient recuperation time. However, water-filled cavities that may impact visual acuity are found in many of these new implants. We demonstrate that the cavitation observed in vivo can occur due to an osmotic pressure difference between the aqueous solution within the cavity and the external media in which the lens is immersed. By reducing the osmolarity of the external solution from 300 to 0mM, we observe an increase in cavity volume of almost a factor of 30. Further, we have developed a model for cavity growth assuming the controlling factor is diffusion of hydrophilic molecules from the polymer matrix into the cavity. We find that the experimental observations are consistent with the model and suggest that oligomeric species generated during polymerization are responsible for the observed cavitation., (Published by Elsevier Ltd.)

A common method of controlling drug release has been to incorporate the drug into a polymer matrix, thereby creating a diffusion barrier that slows the rate of drug release. It has been demonstrated that the internal microstructure of these drug-polymer composites can significantly impact the drug release rate. However, the effect of processing conditions during manufacture on the composite structure and the subsequent effects on release behavior are not well understood. We have developed a diffuse-interface theory for microstructure evolution that is based on interactions between drug, polymer and solvent species, all of which may be present in either crystalline or amorphous states. Because the theory can be applied to almost any specific combination of material species and over a wide range of environmental conditions, it can be used to elucidate and quantify the relationships between processing, microstructure and release response in controlled drug release systems. Calculations based on the theory have now demonstrated that, for a characteristic delivery system, variations in microstructure arising due to changes in either drug loading or processing time, i.e. evaporation rate, could have a significant impact on both the bulk release kinetics and the uniformity of release across the system. In fact, we observed that changes in process time alone can induce differences in bulk release of almost a factor of two and typical non-uniformities of +/-30% during the initial periods of release. Because these substantial variations may have deleterious clinical ramifications, it is critical that both the system microstructure and the control of that microstructure are considered to ensure the device will be both safe and effective in clinical use.

Hematopoietic stem cell (HSC) therapy can significantly lower instances of infection in chemotherapy patients by accelerating the recovery of white blood cells in the body. However, therapy requires that HSCs be stored at cryogenic temperatures to retain the cells' ability to proliferate. Currently, cells are stored in polymeric blood bags that are subject to fracture at the extremely low storage temperatures, which leads to cell contamination, thereby reducing their effectiveness. Therefore, we have developed an analytical model to predict the accumulation of stresses that ultimately lead to crack initiation and bag fracture during cryogenic storage. Our model gives explicit relationships between stress state in the container and thermoelastic properties of the container material, container geometry, and environmental factors that include temperature of the system and pressure induced by excess gas evolving from the stored medium. Predictions based on the model are consistent with experimental observations of bag failures that occurred during cryogenic storage applications. Finally, the model can provide guidance in material selection and bag design to fabricate bags that will be less susceptible to fracture.