(T1330-11-73) Investigating and Optimizing the Influence of Process Parameters on Development of Polymeric Microparticles: A Quality-by-Design Approach

Purpose: Quality-by-Design (QbD) is a mathematical approach of designing and optimizing the development process of a formulation rationally based on targeted final quality. QbD models help in achieving the optimized critical quality attributes (CQAs) systematically by evaluating critical process parameters (CPPs), qualitatively and quantitatively. This study employed QbD to develop polymeric microparticles loaded with hydrogen sulfide (H₂S) donor. Hydrogen sulfide (H₂S) is an endogenous gasotransmitter with reported cytoprotective effects. The unique pharmacological effects of H₂S allow several applications in neurodegenerative diseases like glaucoma. However, its clinical translation is limited by its toxicity, gaseous nature, and low effective therapeutic concentrations. Polymeric microparticles are effective in sustaining the release of H₂S while providing desired efficacy and safety. The performance of microparticles is attributed to several formulation variables and process parameters that need to be carefully optimized to maximize the product target quality. This study identifies as well as quantitatively establishes various formulation parameters and their primary and secondary interactions involved in developing a microparticle-based sustained release H₂S donors.

Methods: JMP Pro (16.1.0) was used to generate the QbD designs and run the analysis of the model. The CPPs identified for preparation of polymeric microparticles, capable of sustaining the release of H₂S in therapeutically relevant nM ranges for an extended period, were polymer drug ratio, polymer surfactant ratio, quantity and viscosity of dispersion medium, and sonication energy and time in the coacervation step; with dispersion medium viscosity and sonication energy being nominal variables, and others being continuous variables. Four key CQAs for microparticles were size, size distribution, encapsulation efficiency, and release profile. A Main Effects screening (MES) QbD model was developed to identify the CPPs significant in determining CQAs. Microparticles were prepared using a solvent-evaporation coacervation process based on MES design (Fig 1). The particle size and distribution were evaluated using Malvern Mastersizer 2000, and the encapsulation and release were studied using a H₂S specific electrochemical method (WPI ISO-H₂S-100 electrode). A p-value ≤ 0.05 associated with any parameter was considered significantly effective in providing CQA in the microparticles loaded with H₂S donor. Thereafter, a Response Surface design (RSD) based Box Behnken design (BBD) was developed to quantitatively establish the relationship between significant CPPs and CQAs.

Results: The MES design recommended 12 formulation designs with variable values of CPPs. From the characterization of 12 formulations and analysis of the model using least square method, it was found that the polymer to drug ratio (p < 0.01), dispersion medium quantity (p < 0.01), sonication time (p < 0.01), and sonication energy (p < 0.05) were significant continuous CPPs, dispersion medium viscosity (p < 0.05) was significant categorical CPP, while polymer surfactant ratio was critical but not statistically significant (p >0.05) in determining the CQAs. The four significant continuous CPPs (polymer drug ratio, dispersion medium quantity, sonication time, and sonication energy) were used to further develop the RSD. 27 formulations were developed based on recommendation of the RSD. From the characterization of 27 formulations and analysis of the model using least squares method, polymer to drug ratio (p < 0.05), sonication energy (p < 0.05), and sonication time (p < 0.05) were found to significantly affect the CQAs. Moreover, polymer drug ratio and dispersion medium quantity also exhibited significant secondary interaction (p < 0.001), indicating a non-linear higher degree effect on the CQAs. The optimum set of values for CPPs were identified by maximizing desirability (particle size < 159µm for synringeability, maximum encapsulation efficiency and maximum drug release, minimum size distribution) (Fig 2). Using the RSD model predicted CPP values, formulations were prepared and validated experimentally (Table 1).

Conclusion: For microparticles loaded with H₂S donor, MES model identified polymer drug ratio and dispersion medium quantity as significant CPPs among others, while the RSD model established their quantitative relationship. The QbD approach helped in achieving desired microparticle characteristics with lesser number of trials and provided a mathematical relationship between the CPPs and the CQAs.

Acknowledgements: Financial support from School of Pharmacy and Health Professions, Creighton University.

Funding: This study was funded by NIH NEI 1R15EY032275-01A1. Conflict of Interest Statements: We confirm that there are no conflicts of interest associated with this work and there has been no significant financial support for this work that could have influenced its outcome.

Figure 1. Schematic procedure for preparation of H2S donor based polymeric microparticles

Figure 2. Prediction profiler for dynamic quantitative effect of significant CPPs on CQAs based on the RSD model

Table 1. Experimental validation of the RSD predicted outcomes of CQAs using optimized CPPs