Evidence map›Paper›PMID 33088989›Full record

ReviewInternational journal of bioprinting2020

3D Bioprinting: The Roller Coaster Ride to Commercialization.

Anton Elemoso, Grigoriy Shalunov, Yakov M Balakhovsky, Alexander Yu Ostrovskiy, Yusef D Khesuani

Abstract readReview
In one paragraph

Review in International journal of bioprinting, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Fundamental research · 2026
    Review
  2. A Pill That Prints-An Ingestible Bioprinter for Non-Invasive Structured Bioink Deposition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  3. Development and Quantitative Evaluation of a Novel AutonomousIEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025
    Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Development ofFrontiers in bioengineering and biotechnology · 2022
    Review
  10. 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

5 authors.

Anton ElemosoLaboratory of Biotechnical Research 3D Bioprinting Solutions, Moscow, Russian Federation.
Grigoriy ShalunovLaboratory of Biotechnical Research 3D Bioprinting Solutions, Moscow, Russian Federation.
Yakov M BalakhovskyVivax Bio, LLC, New York, NY, USA.
Alexander Yu OstrovskiyVivax Bio, LLC, New York, NY, USA.
Yusef D KhesuaniLaboratory of Biotechnical Research 3D Bioprinting Solutions, Moscow, Russian Federation.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Three-dimensional (3D) bioprinting as a technology is being researched and applied since 2003. It is actually several technologies (inkjet, extrusion, laser, magnetic bioprinting, etc.) under an umbrella term "3D bioprinting." The versatility of this technology allows widespread applications in several; however, after almost 20 years of research, there is still a limited number of cases of commercialized applications. This article discusses the potential for 3D bioprinting in regenerative medicine, drug discovery, and food industry, as well as the existing cases of companies that create commercialized products and services in the aforementioned areas and even in fashion, including their go-to-market route and financing received. We also address the main barriers to creating practical applications of 3D bioprinting within each sphere the technology that is being studied for.

Indexed as

3D bioprintingCommercializationDrug discoveryFoodRegenerative medicine

Identifiers

PMID33088989
PMCPMC7557343

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.