PMID- 33313390
OWN - NLM
STAT- MEDLINE
DCOM- 20210428
LR  - 20210428
IS  - 2373-9878 (Electronic)
IS  - 2373-9878 (Linking)
VI  - 6
IP  - 1
DP  - 2020 Jan 13
TI  - Computational-Based Design of Hydrogels with Predictable Mesh Properties.
PG  - 308-319
LID - 10.1021/acsbiomaterials.9b01520 [doi]
AB  - Hydrogel systems are an appealing class of therapeutic delivery vehicles, though 
      it can be challenging to design hydrogels that maintain desired spatiotemporal 
      presentation of therapeutic cargo. In this work, we propose a different approach 
      in which computational tools are developed that creates a theoretical 
      representation of the hydrogel polymer network to design hydrogels with 
      predefined mesh properties critical for controlling therapeutic delivery. We 
      postulated and confirmed that the computational model could incorporate 
      properties of alginate polymers, including polymer content, monomer composition 
      and polymer chain radius, to accurately predict cross-link density and mesh size 
      for a wide range of alginate hydrogels. Additionally, the simulations provided a 
      robust strategy to determine the mesh size distribution and identified properties 
      to control the mesh size of alginate hydrogels. Furthermore, the model was 
      validated for additional hydrogel systems and provided a high degree of 
      correlation (R(2) > 0.95) to the mesh sizes determined for both fibrin and 
      polyethylene glycol (PEG) hydrogels. Finally, a full factorial and Box-Behnken 
      design of experiments (DOE) approach utilized in combination with the 
      computational model predicted that the mesh size of hydrogels could be varied 
      from approximately 5 nm to 5 mum through controlling properties of the polymer 
      network. Overall, this computational model of the hydrogel polymer network 
      provides a rapid and accessible strategy to predict hydrogel mesh properties and 
      ultimately design hydrogel systems with desired mesh properties for potential 
      therapeutic applications.
FAU - Campbell, Kevin T
AU  - Campbell KT
AD  - Department of Biomedical Engineering, University of California Davis, Davis, 
      California, United States of America.
FAU - Wysoczynski, Kajetan
AU  - Wysoczynski K
AD  - Department of Biomedical Engineering, University of California Davis, Davis, 
      California, United States of America.
FAU - Hadley, Dustin J
AU  - Hadley DJ
AD  - Department of Biomedical Engineering, University of California Davis, Davis, 
      California, United States of America.
FAU - Silva, Eduardo A
AU  - Silva EA
AD  - Department of Biomedical Engineering, University of California Davis, Davis, 
      California, United States of America.
LA  - eng
GR  - T32 HL086350/HL/NHLBI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20191210
PL  - United States
TA  - ACS Biomater Sci Eng
JT  - ACS biomaterials science & engineering
JID - 101654670
RN  - 0 (Alginates)
RN  - 0 (Biocompatible Materials)
RN  - 0 (Hydrogels)
RN  - 0 (Polymers)
MH  - Alginates
MH  - Biocompatible Materials
MH  - *Drug Delivery Systems
MH  - *Hydrogels
MH  - Polymers
PMC - PMC7725240
MID - NIHMS1577124
OTO - NOTNLM
OT  - Alginate
OT  - Computational Modeling
OT  - Cross-link Density
OT  - Fibrin
OT  - Hydrogels
OT  - Mesh Size
OT  - Mesh Size Distribution
OT  - Polyethylene Glycol
EDAT- 2020/12/15 06:00
MHDA- 2021/04/29 06:00
PMCR- 2021/01/13
CRDT- 2020/12/14 11:00
PHST- 2020/12/14 11:00 [entrez]
PHST- 2020/12/15 06:00 [pubmed]
PHST- 2021/04/29 06:00 [medline]
PHST- 2021/01/13 00:00 [pmc-release]
AID - 10.1021/acsbiomaterials.9b01520 [doi]
PST - ppublish
SO  - ACS Biomater Sci Eng. 2020 Jan 13;6(1):308-319. doi: 
      10.1021/acsbiomaterials.9b01520. Epub 2019 Dec 10.