ArticleJournal of clinical microbiology2026
Why are we doing this alone? A collaborative framework for LDT development and validation.
Article in Journal of clinical microbiology, 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
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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.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laboratory-developed tests (LDTs) play a critical role in meeting unmet diagnostic needs, particularly for rare infections and high-acuity or immunocompromised patient populations. However, current US regulatory and reimbursement frameworks have constrained innovation and delayed implementation of many essential laboratory diagnostic tests. Here, we propose a pragmatic, collaborative model focusing on infectious disease molecular diagnostics that maintains analytical rigor while allowing clinical validity to be supported by evidence from the medical literature and clinical judgment. To address the resource constraints faced by hospital laboratories, we envision a voluntary, national repository where laboratories and manufacturers contribute standardized analytical and, where appropriate, clinical validation data for both newly developed and modified Food and Drug Administration (FDA)-cleared assays. Data elements such as accuracy, limit of detection, analytical measurement range, analytical specificity, and inclusivity compared with reference determinations would be aggregated within groups representing technically identical assays, enabling cumulative validation and shared use of high-quality evidence. By leveraging these shared data sets, hospital laboratories could implement LDTs in-house with minimal redundant validation, enabling broader access to testing near the point of patient care and faster turnaround times. Manufacturers could use the same data to support applications for expanded intended use of existing FDA-cleared and -approved tests. This framework would strengthen hospital laboratory diagnostic capacity, accelerate test implementation, and improve patient outcomes and healthcare system efficiency.
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