(T1230-04-23) First-in-Class 3D Printing Technology to Fabricate 6-Thioguanine-Loaded Microparticles for Potential COVID-19 Treatment

Purpose: Biodegradable microparticles (MPs) have been extensively investigated over the past few decades, which have emerged as a powerful tool for the delivery of pharmaceutical reagents ¹. Conventional MP formulation techniques involve solvent displacement and emulsion evaporation processes ². The present study employed the first-in-class concept, sprayed multi adsorbed-droplet reposing technology (SMART) which combines extrusion-based printing with emulsion evaporation technique to fabricate 6-thioguanine (6-TG) loaded MPs for COVID-19 treatment. 6-TG blocks SARS-CoV-2 replication by inhibition of PLpro activity ³. Furthermore, poly (lactide-co-glycolide) (PLGA) was selected as the polymer for MP formulation due to its biocompatibility and biodegradability ⁴. Compared to conventional emulsion evaporation method, SMART employs the shear force exerted by syringe nozzle rather than the sonication energy to generate micro-sized emulsion droplets. Furthermore, the shear force given by the bioprinter is controllable and consistent since the emulsion is extruded from the nozzle under a preset printing speed and pressure. Another unique advantage of the SMART is the feasibility of incorporating living organisms during the MP formulation process since the bioprinter is designed for live cell printing. Overall, our invention enables the combination of bioprinting with particulate-based drug delivery systems in a ‘one-step’ process, which demonstrates great promises in different disease treatment.

Methods: Fig 1A shows the schematic of the fabrication of polymeric 6-TG-loaded PLGA MPs by SMART. Briefly, 6-TG was dissolved in 0.11M NaOH PVA solution (1% w/v) to generate the internal aqueous phase. The inner aqueous phase was further added to organic phase, PLGA dissolved in chloroform (7.5 mg/ml), followed by complete mixing to form primary emulsion. The primary emulsion was further added to external aqueous phase, 2% (w/v) PVA solution, followed by mixing completely to generate secondary emulsion. The secondary emulsion was then processed through an extrusion-based printing under different printing parameters. After the evaporation of organic solvent, MPs were centrifuged, collected and characterized. Furthermore, the correlation between loading efficiency and different process parameters (initial drug amount, printing pressure and speed) was investigated by design of experiment (DoE) analysis. Also, a regression model was created using advanced statistical analysis approaches with stepwise removement of the statistically no-significant terms (P >0.05). The in vitro SARS-CoV PLpro inhibition assay was conducted to compare the enzyme inhibition effect of free 6-TG and 6-TG encapsulated SMART MPs. The amount of loaded SMART MPs was based on the loading efficiency to produce the same concentration as free 6-TG.

Results: As is shown in Fig 1B, the printed 6-TG-loaded SMART particles showed spherical structure with smooth surface. The particle size distribution was around 1-3 m in diameter. The regression model of the correlation between loading efficiency with different process parameters (printing speed, s; printing pressure, p, and drug amount, a) was shown as the polynomial equation (1) with r² = 0.91: Loading efficiency = -79.1 + 9.22*a + 1.35*s + 0.596*p – 0.0021*p² -0.15*a*s (1) The surface plots and contour plots were created to visualize the regression model. As is shown in Fig 2A, there was a linear relationship between initial drug amount and loading efficiency when printing speed or printing pressure was held constant. However, when the drug amount was hold constant, both printing speed and pressure showed non-linear relationship with the response variable. The contour plots show a 2-D view in which points that have the same response value are connected to produce contour lines. Each color represents a range of the loading efficiency under different process parameters (Fig 2B). For instance, when initial drug amount is held constant (7.5 mg), printing speed ranging from 14.5 to 16.5 mm/s and the printing pressure ranging from 120kpa to 150kpa, are expected to generate loading efficiency higher than 36g/mg. Regarding the in vitro drug release assay (Fig 3A-C), 6-TG loaded SMART MPs formulated under different process parameters released more than 60% payload in the first 4h, followed by a slower release in the next 6h, and reached ~100% drug release at 10h. As is shown in Fig 3D, PLpro inhibition effect of 6-TG-loaded SMART MPs is comparable to free 6-TG, indicating the drug efficacy was maintained during the printing process under different printing parameters.

Conclusion: In this work, SMART technology was utilized to formulate polymeric drug-loaded MPs. SMART MPs have spherical structure with smooth surface, with controlled size distribution of around 1-3 m in diameter. A regression model was created to investigate the correlation of loading efficiency with process parameters, with r² =0.91. Furthermore, 6-TG loaded SMART MPs formulated under different process parameters released more than 60% payload in the first 4h, followed by a slower release in the next 6h, and reached ~100% drug release at 10h. Moreover, the SARS-CoV PLpro inhibition efficacy of 6-TG was maintained during the SMART MP printing process under different process parameters.

References: 1. Gupta J, Safdari HA, Hoque M. Nanoparticle mediated cancer immunotherapy. In: Seminars in Cancer Biology. Vol 69. ; 2021:307-324.
2. Hernández-Giottonini KY, Rodr\’\iguez-Córdova RJ, Gutiérrez-Valenzuela CA, et al. PLGA nanoparticle preparations by emulsification and nanoprecipitation techniques: Effects of formulation parameters. Rsc Adv. 2020;10(8):4218-4231.
3. Swaim CD, Dwivedi V, Perng Y-C, et al. 6-Thioguanine blocks SARS-CoV-2 replication by inhibition of PLpro. Iscience. 2021;24(10):103213.
4. Barichello JM, Morishita M, Takayama K, Nagai T. Encapsulation of hydrophilic and lipophilic drugs in PLGA nanoparticles by the nanoprecipitation method. Drug Dev Ind Pharm. 1999;25(4):471-476.

Acknowledgements: This wok was funded by National Institute of Health (NIH), grant#R01FD007456


Fig 1 (A) Schematic of the fabrication of 6-TG-loaded PLGA MPs by SMART; (B) SEM images of 6-TG loaded SMART MPs


Fig 2. (A) Surface plots and (B) Contour plots of drug loading versus different process parameters.


Fig 3. Drug release profile of SMART MPs under different (A) printing pressures (100kPa and 100kPa); (B) printing speeds (10mm/s and 20mm/s); (C) initial drug inputs (6mg and 9mg); (D) Inhibition effect of different 6-TG loaded SMART MPs on SARS-CoV2 PLpro.