NMR cryoporometry characterisation studies of the relation between drug release profile and pore structural evolution of polymeric nanoparticles.
Bottom Line: PLGA/PLA polymeric nanoparticles could potentially enhance the effectiveness of convective delivery of drugs, such as carboplatin, to the brain, by enabling a more sustained dosage over a longer time than otherwise possible.For a core-coat nanoparticle formulation, the development of smaller nanopores, following an extended induction period with no structural change, was associated with the onset of substantial drug release.Hence, the specific reasons for the effectiveness of the synthesis route, for obtaining core-coat nanoparticles with delayed release, have been elucidated.
Affiliation: Department of Chemical and Environmental Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK.Show MeSH
Mentions: Batch E comprised spherical nanoparticles (Fig. 8) that were ≥100 nm in size. As can be seen from the drug release profile given in Fig. 9, it was observed that nanoparticles from batch E provided a very small initial burst, and then very little drug release during the next 24 h. Thereafter there was a period of significant sustained drug release lasting ∼2 days, before the release finally tailed off and reached a plateau. From a consideration of the cryoporometry melting curves for nanoparticles from batch E (Fig. 9), it was found that that the melting curves remained very similar over the period of ∼2.5 h to 1 day, with, maybe, a very slight rise in nanopore volume. However, between 1 day and 2 days, when there was a significant change in amount of drug released (∼24%), there was also a significant shift in the melting curve (Fig. 9). The shapes of the melting curves suggest that the volume of pores of sizes ∼1–2 nm (corresponding to ∼230–248 K) increased by about five times between 1 and 2 days. Following this period of change, the melting curves obtained over ∼2, ∼3 and ∼4 days were very similar. The drug release profile after 24 h was fitted to an exponential growth phenomenological mathematical model. The model fitted the data reasonably well (the coefficient of determination of the fit was 0.972) and the time constant for the function was 0.05 h−1.
Affiliation: Department of Chemical and Environmental Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, UK.