PLGA from PolySciTech used in development of computational modeling for drug-delivery formulations

 

Diffusion of drugs through biodegradable polymer systems relies on several properties of the drug, polymer, and formulation parameters. These various properties can be utilized along with computational modeling to calculate the drug-release behaviors. Researchers at Purdue University used PLGA (Cat# AP041) from PolySciTech division of Akina, Inc. (www.polyscitech.com) to investigate the impact of formulation parameters on biodegradable drug-release systems and compare these to computationally predicted results. This research holds promise to improve formulation approaches in the future. Read more: Giolando, Patrick A., Kelsey Hopkins, Barrett Davis, Nicole Vike, Adib Ahmadzadegan, Arezoo Ardekani, Pavlos Vlachos, Joseph Rispoli, Luis Solorio, and Tamara L. Kinzer‐Ursem. "Mechanistic computational modeling of implantable, bioresorbable, drug release systems." Advanced Materials (2023): 2301698. https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.202301698

“Implantable, bioresorbable drug delivery systems offer an alternative to current drug administration techniques; allowing for patient-tailored drug dosage, while also increasing patient compliance. Mechanistic mathematical modeling allows for the acceleration of the design of the release systems, and for prediction of physical anomalies that are not intuitive and might otherwise elude discovery. This study investigates short-term drug release as a function of water-mediated polymer phase inversion into a solid depot within hours to days, as well as long-term hydrolysis-mediated degradation and erosion of the implant over the next few weeks. Finite difference methods were used to model spatial and temporal changes in polymer phase inversion, solidification, and hydrolysis. Modeling revealed the impact of non-uniform drug distribution, production and transport of H+ ions, and localized polymer degradation on the diffusion of water, drug, and hydrolyzed polymer byproducts. Compared to experimental data, the computational model accurately predicted the drug release during the solidification of implants over days and drug release profiles over weeks from microspheres and implants. This work offers new insight into the impact of various parameters on drug release profiles, and is a new tool to accelerate the design process for release systems to meet a patient specific clinical need.”

Video: https://youtu.be/WfCgdxeaFu8