Sam N. Rothstein

A unified mathematical model for the prediction of controlled release from surface and bulk eroding polymer matrices.

A unified model has been developed to predict release not only from bulk eroding and surface eroding systems but also from matrices that transition from surface eroding to bulk eroding behavior during the course of degradation. This broad applicability is afforded by fundamental diffusion/reaction equations that can describe a wide variety of scenarios including hydration of and mass loss from a hydrolysable polymer matrix. Together, these equations naturally account for spatial distributions of polymer degradation rate. In this model paradigm, the theoretical minimal size required for a matrix to exhibit degradation under surface eroding conditions was calculated for various polymer types and then verified by empirical data from the literature. An additional set of equations accounts for dissolution- and/or degradation-based release, which are dependent upon hydration of the matrix and erosion of the polymer. To test the models accuracy, predictions for agent egress were compared to experimental data from polyanhydride and polyorthoester implants that were postulated to undergo either dissolution-limited or degradation-controlled release. Because these predictions are calculated solely from readily attainable design parameters, it seems likely that this model could be used to guide the design controlled release formulations that produce a broad array of custom release profiles.

The Effect of Monomer Order on the Hydrolysis of Biodegradable Poly(lactic-co-glycolic acid) Repeating Sequence Copolymers

The effect of sequence on copolymer properties is rarely studied despite the precedent from Nature that monomer order can create materials of significant diversity. Poly(lactic-co-glycolic acid) (PLGA), one of the most important biodegradable copolymers, is widely used in an unsequenced, random form for both drug delivery microparticles and tissue engineering matrices. Sequenced PLGA copolymers have been synthesized and fabricated into microparticles to study how their hydrolysis rates compare to those of random copolymers. Sequenced PLGA microparticles were found to degrade at slower, and often more constant, rates than random copolymers with the same lactic to glycolic acid ratios as demonstrated by molecular weight decrease, lactic acid release, and thermal property analyses. The impact of copolymer sequence on in vitro release was studied using PLGA microparticles loaded with model agent rhodamine-B. These assays established that copolymer sequence affects the rate of release and that a more gradual burst release can be achieved using sequenced copolymers compared to a random control.

A simple model framework for the prediction of controlled release from bulk eroding polymer matrices

A broadly applicable model for predicting controlled release could eliminate the need for exploratory, in vitro experiments during the design of new biodegradable matrix-based therapeutics. We have developed a simple mathematical model that can predict the release of many different types of agents from bulk eroding polymer matrices without regression. New methods for deterministically calculating the magnitude of the initial burst and the duration of the lag phase (time before Fickian release) were developed to enable the models broad applicability. To complete the models development, such that predictions can be made from easily measured or commonly known parameters, two correlations were developed by fitting the fundamental equations to published controlled release data. To test the model, predictions were made for several different biodegradable matrix systems. In addition, varying the readily attainable parameters over rational bounds shows that the model predicts a wide range of therapeutically relevant release behaviors.

A “tool box” for rational design of degradable controlled release formulations

Controlled release technology could provide a universal solution to the problems of patient compliance and sub-optimal dosing that often plague modern pharmaceuticals. Yet, harnessing this potential requires the ability to design drug delivery formulations which satisfy specific dosing schedules. This review intends to portray how material properties, processing methods and mathematical models can serve as effective tools for rationally tuning the duration and rate of drug release from biodegradable polymer matrices.

In Vitro Characterization of a Sustained-Release Formulation for Enfuvirtide

ABSTRACT Although approved by the U.S. Food and Drug Administration, enfuvirtide is rarely used in combination antiretroviral therapies (cART) to treat HIV-1 infection, primarily because of its intense dosing schedule that requires twice-daily subcutaneous injection. Here, we describe the development of enfuvirtide-loaded, degradable poly(lactic-co-glycolic) acid microparticles that provide linear in vitro release of the drug over an 18-day period. This sustained-release formulation could make enfuvirtide more attractive for use in cART.

A retrospective mathematical analysis of controlled release design and experimentation.

The development and performance evaluation of new biodegradable polymer controlled release formulations relies on successful interpretation and evaluation of in vitro release data. However, depending upon the extent of empirical characterization, release data may be open to more than one qualitative interpretation. In this work, a predictive model for release from degradable polymer matrices was applied to a number of published release data in order to extend the characterization of release behavior. Where possible, the model was also used to interpolate and extrapolate upon collected released data to clarify the overall duration of release and also kinetics of release between widely spaced data points. In each case examined, mathematical predictions of release coincide well with experimental results, offering a more definitive description of each formulations performance than was previously available. This information may prove particularly helpful in the design of future studies, such as when calculating proper dosing levels or determining experimental end points in order to more comprehensively evaluate a controlled release systems performance.