Evidence map›Paper›PMID 37645046›Full record

ArticleArXiv2023

Rapid model-guided design of organ-scale synthetic vasculature for biomanufacturing.

Zachary A Sexton, Andrew R Hudson, Jessica E Herrmann, Dan J Shiwarski, Jonathan Pham, Jason M Szafron, Sean M Wu, Mark Skylar-Scott, Adam W Feinberg, Alison Marsden

Open access · greenAbstract readPreprint
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
29.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 43 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Zachary A SextonDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Andrew R HudsonDepartment of Biomedical Engineering Carnegie Mellon University, Pittsburgh, PA, USA.
Jessica E HerrmannSchool of Medicine, Stanford University, Stanford, CA, USA.
Dan J ShiwarskiDepartment of Biomedical Engineering Carnegie Mellon University, Pittsburgh, PA, USA.
Jonathan PhamDepartment of Mechanical Engineering, Stanford University, Stanford, CA, USA.
Jason M SzafronCardiovascular Institute, Stanford University, Stanford, CA, USA.
Sean M WuCardiovascular Institute, Stanford University, Stanford, CA, USA.
Mark Skylar-ScottDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Adam W FeinbergDepartment of Biomedical Engineering Carnegie Mellon University, Pittsburgh, PA, USA.
Alison MarsdenDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Cardiovascular Institute of the South · USStanford University · USCarnegie Mellon University · US

Funding

Trillion cell culture to fuel organ biofabricationDP2HL168563 · NHLBI · STANFORD UNIVERSITY · PI SKYLAR-SCOTT, MARK A. · 2022 to 2025
$2.4M
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease R01EB029362 · NIBIB · STANFORD UNIVERSITY · PI MARSDEN, ALISON L · 2019 to 2022
$1.4M
Development of a Collagen-based 3D Bioprinted Microfluidic Platform for Vascular Tissue Engineering and Disease ModelingR00HL155777 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI SHIWARSKI, DANIEL J · 2023 to 2025
$747k
Development of a Collagen-based 3D Bioprinted Microfluidic Platform for Vascular Tissue Engineering and Disease ModelingK99HL155777 · NHLBI · CARNEGIE-MELLON UNIVERSITY · PI SHIWARSKI, DANIEL J · 2021 to 2022
$222k
NHLBI NIH HHS DP2 HL168563NHLBI NIH HHS K99 HL155777NHLBI NIH HHS R00 HL155777NIBIB NIH HHS R01 EB029362
6 · The paper itself

Abstract

Our ability to produce human-scale bio-manufactured organs is critically limited by the need for vascularization and perfusion. For tissues of variable size and shape, including arbitrarily complex geometries, designing and printing vasculature capable of adequate perfusion has posed a major hurdle. Here, we introduce a model-driven design pipeline combining accelerated optimization methods for fast synthetic vascular tree generation and computational hemodynamics models. We demonstrate rapid generation, simulation, and 3D printing of synthetic vasculature in complex geometries, from small tissue constructs to organ scale networks. We introduce key algorithmic advances that all together accelerate synthetic vascular generation by more than 230 -fold compared to standard methods and enable their use in arbitrarily complex shapes through localized implicit functions. Furthermore, we provide techniques for joining vascular trees into watertight networks suitable for hemodynamic CFD and 3D fabrication. We demonstrate that organ-scale vascular network models can be generated in silico within minutes and can be used to perfuse engineered and anatomic models including a bioreactor, annulus, bi-ventricular heart, and gyrus. We further show that this flexible pipeline can be applied to two common modes of bioprinting with free-form reversible embedding of suspended hydrogels and writing into soft matter. Our synthetic vascular tree generation pipeline enables rapid, scalable vascular model generation and fluid analysis for bio-manufactured tissues necessary for future scale up and production.

Identifiers

PMID37645046
PMCPMC10462165
OpenAlexW4386271217

What Socratic holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.