D-Optimal mixture experimental design for stealth biodegradable crosslinked docetaxel-loaded poly-ε-caprolactone nanoparticles manufactured by dispersion polymerization

We report here our efforts on the development of stealth biodegradable crosslinked poly-epsilon-caprolactone nanoparticles by free radical dispersion polymerization suitable for the delivery of bioactive agents. The uniqueness of the dispersion polymerization technique is that it is surfactant free, thereby obviating the problems known to be associated with the use of surfactants in the fabrication of nanoparticles for biomedical applications. Aided by a statistical software for experimental design and analysis, we used D-optimal mixture statistical experimental design to generate thirty batches of nanoparticles prepared by varying the proportion of the components (poly-epsilon-caprolactone macromonomer, crosslinker, initiators and stabilizer) in acetone/water system. Morphology of the nanoparticles was examined using scanning electron microscopy (SEM). Particle size and zeta potential were measured by dynamic light scattering (DLS). Scheffe polynomial models were generated to predict particle size (nm) and particle surface zeta potential (mV) as functions of the proportion of the components. Solutions were returned from simultaneous optimization of the response variables for component combinations to (a) minimize nanoparticle size (small nanoparticles are internalized into disease organs easily, avoid reticuloendothelial clearance and lung filtration) and (b) maximization of the negative zeta potential values, as it is known that, following injection into the blood stream, nanoparticles with a positive zeta potential pose a threat of causing transient embolism and rapid clearance compared to negatively charged particles. In vitro availability isotherms show that the nanoparticles sustained the release of docetaxel for 72 to 120 hours depending on the formulation. The data show that nanotechnology platforms for controlled delivery of bioactive agents can be developed based on the nanoparticles.