Evidence map›Paper›PMID 42530393›Full record

ReviewChembiochem : a European journal of chemical biology2026

Environmental Impact of Synthetic Cell Technology: Review of Life Cycle Assessment Data for Feedstocks and Production Methods.

Christina Hopf, Mehdi Ravandeh, Jan Steinkühler

Abstract readReview
In one paragraph

Review in Chembiochem : a European journal of chemical biology, 2026. 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Christina HopfBio-Inspired Computation, Institute of Electrical and Information Engineering, Kiel University, Kiel, Germany.
Mehdi RavandehBio-Inspired Computation, Institute of Electrical and Information Engineering, Kiel University, Kiel, Germany.
Jan SteinkühlerBio-Inspired Computation, Institute of Electrical and Information Engineering, Kiel University, Kiel, Germany.ORCID https://orcid.org/0000-0003-4226-7945

Funding

Bundesministerium für Bildung und Forschung 031B1533AEuropean Research Council 101163768
6 · The paper itself

Abstract

Bottom-up synthetic cells are frequently framed as enabling technologies for a future green bioeconomy, yet their environmental impacts remain poorly quantified. Here, we review and synthesize available life cycle assessment (LCA) data for the feedstocks, production routes, and assembly methods commonly used in synthetic cell research, focusing on cradle-to-gate system boundaries. We consider lipids from plant and algal sources, amphiphilic diblock copolymers, recombinant proteins, crude and PURE (protein synthesis using recombinant elements) cell-free protein synthesis (CFPS) systems, and key assembly approaches including bulk emulsification and microfluidics. We argue that many of the identified components may also play a role in future generations of synthetic cells that undergo primitive autonomous growth and cell cycles. The data illustrate how design choices in compartment composition, encapsulated biochemistry, and assembly efficiency can shift impacts by orders of magnitude. Early integration of LCA-informed design, such as favoring lower purity where functionally acceptable, using shared feedstocks, reducing material excess, and employing alternative autotrophic or solvent-free production routes, will be decisive for achieving environmentally viable synthetic cell technologies.

Indexed as

Artificial CellsEnvironmentSynthetic BiologyLipidsRecombinant ProteinsLipidsRecombinant Proteins

Identifiers

PMID42530393
PMCPMC13422140

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.