Literature DB >> 32659325

A rapid millifluidic synthesis of tunable polymer-protein nanoparticles.

Joshua Seaberg1, Sina Kaabipour1, Shohreh Hemmati1, Joshua D Ramsey2.   

Abstract

Polymeric nanoparticles have drawn recent attention for their ability to enhance the efficacy of therapeutic proteins through reduced immunogenicity and extended circulation time. Though effective, most nanoparticle drug delivery systems are currently produced in batch processes that are limited in control parameters and scalability. To address these deficiencies, a millifluidic process was developed to encapsulate bovine serum albumin in poly(L-lysine)-grafted-poly(ethylene glycol) through an electrostatic self-assembly mechanism. The millifluidic process utilized ultrasonication to overcome the diffusional barriers to self-assembly in a laminar flow regime and produce a nanoparticle tunable by controlling the feed flow rate, tubing material, and ultrasonic power input. Nanoparticle diameters ranged from 13 to 300 nm with polydispersity index measurements ranging from 0.1 to 0.4. The copolymer fully encapsulated the protein in all system configurations and protected the encapsulated protein in the presence of proteases. Notably, the enzymatic activity of the millifluidic nanoparticles was both comparable to that of nanoparticles produced through the batch process and greater than that of the free protein, suggesting there is little difference in the self-assembly induced through the batch and millifluidic processes. This study presents the utility of millifluidics in the synthesis of polymer-protein nanoparticles and provides insight into the development of continuous processes for the production of nanoparticle drug delivery systems.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Comparison of continuous and batch processes; Drug delivery system; Millifluidic nanoparticle synthesis; Poly(L-lysine)-grafted-poly(ethylene glycol) copolymer; Polymer-protein nanoparticle

Mesh:

Substances:

Year:  2020        PMID: 32659325     DOI: 10.1016/j.ejpb.2020.07.006

Source DB:  PubMed          Journal:  Eur J Pharm Biopharm        ISSN: 0939-6411            Impact factor:   5.571


  2 in total

Review 1.  Hybrid Nanosystems for Biomedical Applications.

Authors:  Joshua Seaberg; Hossein Montazerian; Md Nazir Hossen; Resham Bhattacharya; Ali Khademhosseini; Priyabrata Mukherjee
Journal:  ACS Nano       Date:  2021-01-26       Impact factor: 18.027

2.  Estimating the density of deep eutectic solvents applying supervised machine learning techniques.

Authors:  Mohammadjavad Abdollahzadeh; Marzieh Khosravi; Behnam Hajipour Khire Masjidi; Amin Samimi Behbahan; Ali Bagherzadeh; Amir Shahkar; Farzad Tat Shahdost
Journal:  Sci Rep       Date:  2022-03-23       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.