Evidence map›Paper›PMID 42559577›Full record

ArticleNature reviews bioengineering2026

Computational approaches in bioprinting processes.

Alessandro De Giorgi, Zhenwu Wang, Qing Li, Alessandro Polini, Francesca Gervaso, Yu Shrike Zhang

Abstract read
In one paragraph

Article in Nature reviews bioengineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Alessandro De GiorgiDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA.ORCID 0009-0006-1120-9725
Zhenwu WangDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA.ORCID 0000-0002-4721-7763
Qing LiSchool of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, New South Wales, Australia.
Alessandro PoliniCNR NANOTEC - Institute of Nanotechnology, c/o Campus Ecotekne, Lecce, Italy.ORCID 0000-0002-3188-983X
Francesca GervasoCNR NANOTEC - Institute of Nanotechnology, c/o Campus Ecotekne, Lecce, Italy.ORCID 0000-0002-8644-1653
Yu Shrike ZhangDivision of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, MA, USA.ORCID 0000-0002-0045-0808

Funding

High-throughput Imaging-integrated Vascular Model for Understanding Thromboembolism and Therapeutics ScreeningR01HL166522 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI Junjie Yao, Y. Shrike Zhang · 2023 to 2026
$2.7M
Biomaterials for embolization and ablation of arterio-venous malformationsR01HL165176 · NHLBI · MAYO CLINIC ARIZONA · PI OKLU, RAHMI, ZHANG, Y. SHRIKE · 2022 to 2025
$2.6M
Stretchable Hydrogel Bioinks-Enabled Microfluidic Bioprinting of Functional Small-Diameter Blood VesselsR01HL153857 · NHLBI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI ZHAO, XUANHE · 2020 to 2024
$2.4M
High-Throughput Volumetric Photoacoustic Imaging of Living Vascularized OrganoidsR01EB028143 · NIBIB · DUKE UNIVERSITY · PI YAO, JUNJIE · 2019 to 2022
$2.0M
A Bioprinted Volumetric Model of Vascularized GlioblastomaR01CA282451 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Kaisorn Lee Chaichana, Y. Shrike Zhang · 2023 to 2026
$1.7M
Handheld Wound Analyzer for in situ HealingR01GM134036 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI ZHANG, Y. SHRIKE · 2020 to 2023
$1.4M
Development of An Optoelectronically Active BioinkR21EB030257 · NIBIB · UNIVERSITY OF HOUSTON · PI YU, CUNJIANG · 2020 to 2020
$694k
Autonomous Hybrid Bioprinting of Hierarchical Perfusable Vascularized Liver TissuesR01EB038366 · NIBIB · UNIVERSITY OF NOTRE DAME · PI Yanliang Zhang · 2026 to 2026
$663k
Cryobioprinting for Shelf-Ready Tissue Fabrication and StorageR56EB034702 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI ZHANG, Y. SHRIKE · 2023 to 2023
$499k
NCI NIH HHS R01 CA282451NHLBI NIH HHS R01 HL153857NHLBI NIH HHS R01 HL165176NHLBI NIH HHS R01 HL166522NIBIB NIH HHS R01 EB028143NIBIB NIH HHS R01 EB038366NIBIB NIH HHS R21 EB030257NIBIB NIH HHS R56 EB034702NIGMS NIH HHS R01 GM134036
6 · The paper itself

Abstract

Bioprinting technologies often require repeated experimental trials to optimize operational parameters and characterize bioprinted constructs. In this context, computational simulations have emerged as a powerful complementary tool, enabling them to analyse the bioprinting processes and address the distinct challenges associated with each technique. By predicting bioink behaviours, evaluating shear stress effects and enhancing printability, simulations can substantially streamline bioprinting workflows and provide insights that are difficult to obtain experimentally. This Review examines computational approaches for the three principal bioprinting strategies: extrusion-based, droplet-based and light-based methods. We begin with a concise overview of each technique, followed by a discussion of bioink rheology, an essential factor for accurate in silico modelling. We then outline the fundamental theoretical frameworks and primary computational methodologies used to simulate each process, along with the key challenges that remain. Next, we highlight major applications of computational simulations in bioprinting, including nozzle designs, printability assessments and photopolymerization predictions. We finally conclude by discussing emerging directions in which simulation-based approaches could further accelerate advances in the field.

Identifiers

PMID42559577
PMCPMC13441235

What Socratic holds

Textmetadata
LicenceTDM
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.