Design of experiment and machine learning inform on the 3D printing of hydrogels for biomedical applications.

In the biomedical field, 3D printing has the potential to deliver on some of the promises of personalized therapy, notably by enabling point-of-care fabrication of medical devices, dosage forms and bioimplants. To achieve this full potential, a better understanding of the 3D printing processes is necessary, and non-destructive characterization methods must be developed. This study proposes methodologies to optimize the 3D printing parameters for soft material extrusion. We hypothesize that combining image processing with design of experiment (DoE) analyses and machine learning could help obtaining useful information from a quality-by-design perspective. Herein, we investigated the impact of three critical process parameters (printing speed, printing pressure and infill percentage) on three critical quality attributes (gel weight, total surface area and heterogeneity) monitored with a non-destructive methodology. DoE and machine learning were combined to obtain information on the process. This work paves the way for a rational approach to optimize 3D printing parameters in the biomedical field.

Size Exclusion of Radioactive Polymers (SERP) informs on the biodegradation of trimethyl chitosan and biodegradable polymer nanoparticles in vitro and in vivo.

Preparation of drug delivery systems and nanomedicines necessitates the use of biocompatible excipients that are readily eliminated from the body. The systematic preclinical development of novel materials requires tools to evaluate their pharmacokinetics, biodistribution and excretion. Herein, we propose a technique called Size Exclusion of Radioactive Polymers (SERP) to trail the disposition of a radiolabeled polymer and its nanoparticles using chromatography in the presence of complex biological media such as blood, urine and feces. Trimethyl chitosan (TMC) is a polysaccharide of natural origin showing promise for controlled and targeted drug delivery applications. SERP was used to monitor degradation of radiolabeled TMC and its nanoparticles in vitro in the presence of strong acid, enzymes released by macrophages, as well as in vivo after administration to rats. Excretion of the radiolabeled TMC nanoparticles in urine and feces was monitored for 14 days after dosing to healthy rats, confirming that the polymer could be readily eliminated from the body. This work demonstrates the ability of SERP to understand the biological journey of biomaterials in vivo. Paving the way to understand the fate of polymers and nanoparticles in complex environments, the technique might facilitate the development of safer and better tolerated nanomedicines.