ArticleNature reviews bioengineering2026
Computational approaches in bioprinting processes.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Mimicking tumor hypoxia in a glioblastoma-on-a-chip.Materials today. Bio · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
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
What Socratic holds
Registered trials
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.