Modeling, design, and machine learning-based framework for optimal injectability of microparticle-based drug formulations-Reference-Cited by-同舟云学术

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Modeling, design, and machine learning-based framework for optimal injectability of microparticle-based drug formulations

Published:2020-07-10 Issue:28 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Sarmadi Morteza¹²³^ORCID,Behrens Adam M.²,McHugh Kevin J.²^ORCID,Contreras Hannah T. M.²^ORCID,Tochka Zachary L.²^ORCID,Lu Xueguang²^ORCID,Langer Robert¹²³^ORCID,Jaklenec Ana²^ORCID

Affiliation:

1. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

2. David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

3. Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Abstract

We investigate particle injectability as an essential parameter for design of microparticle-based drug delivery systems.

Funder

Bill and Melinda Gates Foundation

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

Reference43 articles.

1. New Methods of Drug Delivery

2. Drug delivery and targeting;Langer R.;Nature,1998

3. Polymeric Systems for Controlled Drug Release

4. Small-scale systems for in vivo drug delivery

5. Fabrication of fillable microparticles and other complex 3D microstructures

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