Feasibility and application of machine learning enabled fast screening of poly-beta-amino-esters for cartilage therapies.

ABSTRACT: Despite the large prevalence of diseases affecting cartilage (e.g. knee osteoarthritis affecting 16% of population globally), no curative treatments are available because of the limited capacity of drugs to localise in such tissue caused by low vascularisation and electrostatic repulsion. While an effective delivery system is sought, the only option is using high drug doses that can lead to systemic side effects. We introduced poly-beta-amino-esters (PBAEs) to effectively deliver drugs into cartilage tissues. PBAEs are copolymer of amines and di-acrylates further end-capped with other amine; therefore encompassing a very large research space for the identification of optimal candidates. In order to accelerate the screening of all possible PBAEs, the results of a small pool of polymers (n =

SUBMITTER: Perni S 

PROVIDER: S-EPMC9392801 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature