The goal of this research project is to create a Mathcad template file capable of statistically modelling the effects of mean and standard deviation on a microparticle batch characterized by the log normal distribution model. Such a file can be applied during manufacturing to explore tolerances and increase cost and time effectiveness. Theoretical data for the time to 60% drug release and the slope and intercept of the log-log plot were collected and subjected to statistical analysis in JMP. Since the scope of this project focuses on microparticle surface degradation drug release with no drug diffusion, the characteristic variables relating to the slope (n = diffusional release exponent) and the intercept (k = kinetic constant) do not directly apply to the distribution model within the scope of the research. However, these variables are useful for analysis when the Mathcad template is applied to other types of drug release models.

Alginate microspheres have recently become increasingly popular in the realm of drug delivery for their biocompatibility, nontoxicity, inexpensiveness, among other factors. Recent strict regulations on microsphere size have drastically increased manufacturing cost and waste, even though the effect of size variance on drug delivery and subsequent performance is unclear. If sphere size variance does not significantly affect drug release profiles, it is possible that future ordinances may loosen tolerances in manufacturing to limit waste produced and expenditures. We use a mathematical model developed by Nickel et al. [12], to theoretically predict drug delivery profiles based on sphere size, and correlate the expected release with experimental data. This model considers diffusion as the key component for drug delivery, which is defined by Fick’s Laws of Diffusion. Alginate, chosen for its simple fabrication method and biocompatibility, was formed into microspheres with a modified extrusion technique and characterized by size. Size variance was introduced in batches and delivery patterns were compared to control groups of identical size. Release patterns for brilliant blue dye, the mock drug chosen, were examined for both groups via UV spectrometry. The absorbance values were then converted to concentration value using a calibration curve done prior to experimentation. The concentration values were then converted to mass values. These values then produced curves representing the mass of the drug released over time. Although the control and experimental values were statistically significantly different, the curves were rather similar to each other. However, when compared to the predicted release pattern, the curves were not the same. Unexpected degradation caused this dissimilarity between the curves. The predictive model was then adjusted to account for degradation by changing the diffusion coefficient in the code to a reciprocal first order exponent. The similarity between the control and experimental curves can insinuate the notion that size tolerances for microsphere production can be somewhat lenient, as a batch containing fifteen beads of the same size and one with three different sizes yields similar release patterns.