Evidence map›Paper›PMID 42695112›Full record

ReviewJournal of biomolecular techniques : JBT2026

Automated Biomedical Research Laboratories: Development, Current State, and a Roadmap for Adaptation into Shared Research Resources.

Jay W Fox, Jeffery R Martens

Abstract readReview
In one paragraph

Review in Journal of biomolecular techniques : JBT, 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

2 authors.

Jay W FoxOffice for Research University of Virginia Medical Center.ORCID https://orcid.org/0000-0003-4600-1132
Jeffery R MartensOffice for Research University of Virginia Medical Center.

Funding

Women's Oncology Program - WONP30CA044579 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Jay William FOX · 1987 to 2026
$72.1M
NCI NIH HHS P30 CA044579
6 · The paper itself

Abstract

Automated biomedical research laboratories (ABRLs) integrate robotics, laboratory instrumentation, orchestration software, and increasingly, machine learning and large language models to plan, execute, and interpret experiments with limited human intervention. Over roughly two decades, these systems have progressed from stand-alone liquid handlers and high-throughput screening workcells to remotely operated "cloud" laboratories, synthetic-biology biofoundries, and closed-loop "self-driving" laboratories capable of autonomous hypothesis generation and testing. This review summarizes the development and current state of ABRLs across biomedical domains, proposes a levels-of-autonomy framework, and evaluates which classes of ABRL are most readily adaptable into institutional shared research resources (core facilities). We maintain that standardized high-throughput sample-preparation and screening workcells, remotely accessible cloud platforms, and design-build-test-learn biofoundry services are the strongest near-term candidates for the core model, whereas bespoke self-driving laboratories are better suited to highly specialized cores or consortium-scale infrastructure. We outline a staged adaptation roadmap including needs assessment and governance, pilot deployment, workflow standardization with rigorous validation and quality management, informatics/remote-access and cost-recovery integration, and federation, and we address the workforce, change-management, and biosecurity-governance factors that determine success. Finally, we propose an evaluation framework that extends an eight-domain core performance model with automation-specific indicators for reliability, reproducibility, cost per result, access equity, and responsible use. Thoughtful adaptation of ABRLs offers core facilities a path to higher throughput, improved rigor and data provenance, and broader access, if standardization, workforce development, and governance keep pace.

Indexed as

Automation, LaboratoryBiomedical ResearchLaboratoriesHigh-Throughput Screening AssaysHumansSoftwareABRLsbiofoundrycloud laboratorycore facilitylaboratory automationreproducibilityself-driving laboratoryshared research resources (SRRs)

Identifiers

PMID42695112
PMCPMC13541213

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.