(M1030-02-08) Mechanistic Mathematical Modeling of In Vitro Drug Release from PLGA-Based Dexamethasone Solid Implants

Purpose: We present a mechanistic mathematical model of polymer-based biodegradable injectables and implant formulations, available within the Simcyp Simulator version 23. We describe the verification of that model using dexamethasone solid implants in vitro release data. The model parameterization requires characterizing data such as implant dimensions, polymer-specific information etc. The model can be used to understand which critical formulation parameters affect drug release i.e., the crucial quality attributes.

Methods: The simulations were conducted in version 23 of Simcyp Simulator using the Simcyp R package, which facilitates running multiple simulations, using the Mechanistic Polymer-Based Biodegradable Injectables and Implants model. The model accounts for the wetting of the implant, degradation of poly lactide-glycolide by hydrolysis and autocatalysis, and dissolution of active pharmaceutical ingredients (API) and oligomers in the pore network of the polymer matrix. The model was initially parameterized using literature-reported data. In the absence of such data, some of the model parameters were assumed based on our prior understanding of drug release. Three model parameters, ionization proportionality constant, deionization constant, and immediately releasable fraction were optimized to recover the observed data. We used drug release data on reverse-engineered formulations reported for Ozurdex by Costello et al. (2023). The same study also reports the characterization of those implants for qualitative, quantitative, and structural (Q1, Q2 and Q3) parameters. The model was first parameterized using Ozurdex implant release data and then verified using reported in vitro release data by Bhagat et al. (2014) and reverse-engineered implant release data from the Costello et al. study (2023).

Results: The model was parameterized using Ozurdex data in saline media, and initial simulations suggested that the default model parameter values were not sufficient to describe the observed Ozurdex release data. The parameters namely ionization proportionality constant, deionization rare constants and immediately releasable fractions were optimized to recover the observed data. The former two parameters influence H⁺ ions concentration within the implants and thereby modulate the autocatalytic degradation. The predicted vs observed data for drug release is shown in Figures 1A-C and the predicted to observed (P/O) ratios are presented in Figure 1D. With the exception of two time points the P/O ratios are within 2-fold of error limits. Additionally for reverse-engineered implants, molecular weight and solvent pH vs time profile were available in the Costello et al study. Figures 1E-F show the comparison of observed and predicted profiles for this study.

Conclusion: The objective of the study was to verify the mechanistic mathematical polymer-based biodegradable injectables and implants model using a literature-reported case example. To model the drug release, the implant characterization data and release testing conditions were integrated into the model. First, the model parameters were fixed using the Ozurdex in vitro release study results by Costello et al, then the model was verified using literature reported in vitro release profile of Ozurdex by Bhagat et al followed by the prediction of release profile from reverse-engineered samples assuming there are no unknown formulation variables that might influence the dynamics during release experiments. The model predictions are reasonably well for the molecular weight vs time profile and pH vs time profile. However, there is scope for improving the prediction accuracy of these profiles. Future work focuses on expanding the model to account for additional features/phenomena in the release process of solid implants.

References: Bhagat, R., Zhang, J., Farooq, S., & Li, X. Y. (2014). Comparison of the release profile and pharmacokinetics of intact and fragmented dexamethasone intravitreal implants in rabbit eyes. J Ocul Pharmacol Ther, 30(10), 854-858. https://doi.org/10.1089/jop.2014.0082
Costello, M. A., Liu, J., Chen, B., Wang, Y., Qin, B., Xu, X., Li, Q., Lynd, N. A., & Zhang, F. (2023). Drug release mechanisms of high-drug-load, melt-extruded dexamethasone intravitreal implants. Eur J Pharm Biopharm, 187, 46-56. https://doi.org/10.1016/j.ejpb.2023.04.003

Acknowledgements: All the authors are employees of Certara.


Figure 1: Model predictions vs observations for the dexamethasone solid implants; (A) Ozudex implants release data from Costello et al. used for fitting the model parameters, (B) Ozurdex implants release data from Bhagat et al. used for the model validation (extrapolation),(C) reverse engineered implants release data from Costello et al. (D) predicted to observed ratio vs time for above profiles (A-C),(E) reverse engineered implants-Molecular weight vs time profile and (C) reverse engineered- implants pH of the solvent vs time profile