Controlled-release drug delivery is a promising method of safely and efficiently delivering biotherapeutics, which typically require frequent injections due to poor oral bioavailability and short in vivo halflives. Biodegradable polymeric microspheres, in particular, offer several advantages over conventional drug delivery vehicles, including better control of pharmacokinetics with concomitant reduction in side effects, enhanced patient compliance due to reduced frequency, and versatility in duration of drug delivery and potential routes of administration. Realizing the full potential of this promising technology will require better methods for design of microsphere systems based on understanding of the mechanisms controlling polymer degradation/erosion, drug release rates and drug stability.

The modeling of drug release from microspheres is important for designing delivery systems. When typical bulk-eroding polymer microspheres (such as those composed of PLGA) are exposed to aqueous media, water penetrates the polymer matrix, cleaving the ester bonds (degradation) and ultimately generating oligomers and monomers that can diffuse out of the microsphere resulting in loss of mass (erosion). Erosion leads to the growth and generation of an aqueous-filled pore network through which water-soluble drugs such as proteins diffuse and are released. In addition, accumulation of acidic degradation products can lead to autocatalytic degradation and, thus, faster erosion, pore formation, and potentially drug release as particle size increases. Few models have accounted for the autocatalytic effect and its size dependence on polymer erosion and drug diffusion rates.

We have developed a Monte Carlo code that efficiently predicts drug release profiles as a function of particle size, drug solubility/diffusivity, and polymer erosion rates. In its present form, the model relies on input of erosion and pore formation data, for example obtained by quantifying the evolution of internal particle architecture by quantitative analysis of scanning electron micrographs. By combining the degradation/erosion processes with diffusion, using mass transfer coefficients, we can investigate the competing physical phenomena that control drug release. We show how the relevant diffusion and erosion time scales determine the primary mechanism controlling release for a variety of particle sizes, polymer molecular weights and drug diffusion rates. In addition, the model is validated by showing its capability of fitting various types of experimental drug release data.