ReviewJournal of biomolecular techniques : JBT2026
From Core Facility to Collaborative Partner: Reimagining Institutional Shared Resources as CRO-Model Research Partners Enhanced by Agentic AI.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Academic biomedical research institutions are confronting a converging challenge: tightening federal research budgets and growing demands for faster and more reproducible science,1 and increasing pressure to maximize value derived from every research dollar. Traditional shared resources have enabled access to sophisticated technologies and expertise as transactional, fee-for-service facilities that prioritize throughput and cost recovery over scientific outcomes. We propose a shift toward a Contract Research Organization (CRO)-inspired operating model in which shared resources function as integrated research partners, supported by agentic artificial intelligence (AI) systems that enhance project management, experimental execution, data analysis, and scientific decision-making. This Perspective outlines the limitations of the current paradigm, identifies lessons from commercial CROs, explores the opportunities for agentic AI across major research domains, and presents a roadmap for institutional implementation. We argue that institutions that embrace this transformation will be better positioned to increase productivity, improve reproducibility, accelerate discovery, and strengthen research competitiveness in an increasingly resource-constrained environment.
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What OpenQuestion 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 OpenQuestion graph.