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

计算机科学 管道(软件) 生物制造 可扩展性 比例(比率) 生物 遗传学 量子力学 数据库 物理 程序设计语言
作者
Zachary A. Sexton,Andrew R. Hudson,Jessica E. Herrmann,Daniel J. Shiwarski,Jonathan Pham,Jason M. Szafron,Sean M. Wu,Mark A. Skylar‐Scott,Adam W. Feinberg,Alison L. Marsden
出处
期刊:Cornell University - arXiv 被引量:5
标识
DOI:10.48550/arxiv.2308.07586
摘要

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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
小二郎应助JIA采纳,获得10
1秒前
huhdcid发布了新的文献求助10
2秒前
zho关闭了zho文献求助
2秒前
2秒前
今后应助wslingling采纳,获得10
2秒前
3秒前
充电宝应助Fine采纳,获得10
4秒前
Zhou驳回了7749应助
4秒前
4秒前
CodeCraft应助莹莹啊采纳,获得10
5秒前
6秒前
无极微光应助笑点低丹南采纳,获得20
6秒前
Akim应助动人的乾采纳,获得10
7秒前
7秒前
7秒前
嘟嘟许完成签到,获得积分10
8秒前
9秒前
9秒前
Hello应助嘟嘟采纳,获得10
9秒前
科研通AI6.3应助嘟嘟采纳,获得10
9秒前
shimenayao发布了新的文献求助10
10秒前
Owen应助雯茜采纳,获得10
10秒前
SC30发布了新的文献求助10
10秒前
Fushuai完成签到,获得积分10
10秒前
小兰完成签到,获得积分10
10秒前
11秒前
11秒前
耸耸完成签到 ,获得积分10
11秒前
CipherSage应助热情的戾采纳,获得10
12秒前
1526发布了新的文献求助10
12秒前
虚心映之发布了新的文献求助10
12秒前
12秒前
muluoyinhua完成签到,获得积分10
13秒前
尔尔发布了新的文献求助10
14秒前
15秒前
ChiangYu完成签到,获得积分10
15秒前
15秒前
汉堡包应助liqingsong采纳,获得10
15秒前
888完成签到,获得积分10
16秒前
高分求助中
Principles of Economics, 11th Edition 10000
Prescott's Microbiology: 2026 Release ISE 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Interactions of Vowel Quality and Prosody in East Slavic 1000
Erwählung und Berufung bei Paulus: Bedeutung, Entwicklung und Funktion einer Vorstellung in ihrem frühjüdischen und griechisch-römischen Kontext 850
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7192835
求助须知:如何正确求助?哪些是违规求助? 8829209
关于积分的说明 18641014
捐赠科研通 6828497
什么是DOI,文献DOI怎么找? 3175876
关于科研通互助平台的介绍 2327948
邀请新用户注册赠送积分活动 2150356