ArticleAnalytical and bioanalytical chemistry2026
Expanded evaluation of a robust on-line sample cleanup-LC-MS platform suited for new approach methodologies (NAM).
Article in Analytical and bioanalytical chemistry, 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
8 authors.
Funding
Abstract
Sample preparation in bioanalysis can require significant numbers of (manual) steps and consumables. Such procedures can be bottlenecks regarding cost, throughput, and greenness. This is also the case for analysis of new approach methodologies (NAMs) such as organoids and organ-on-a-chip systems. In this context, approaches tailored for measuring drugs in NAM-related cell culture media (CCM) are being developed. For mass spectrometry-based analysis, automated filtration/filter backflush solid-phase extraction liquid chromatography AFFL-SPE-LC is utilized. Case studies have shown that the "AFFL" platform allows for vast reductions in sample preparation efforts, as the "self-cleaning" filtration features and SPE conditions remove potentially clogging/contaminating materials from samples of biological origin, e.g., the salt and protein content in CCM. Here, broader demonstrations of the AFFL platform's traits for CCM analysis are provided, employing an extended panel of hydrophobic small-molecule drugs. The investigated AFFL platform shows reproducible chromatographic performance, as well as fit-for-purpose inter-matrix and inter-column robustness. Hundred-scale injections can be performed with satisfactory repeatability (e.g., retention time RSDs < 1%), with limited interference from the various CCM matrices investigated. Practical NAM applications are also demonstrated. The approach has clear advantages in greenness, obtaining an AGREE prep score of 0.71, contrasting the < 0.55 scores of more conventional/commercial approaches. The plastic consumable usage of our approach is 28 g/100 samples, a nearly 20-fold improvement over a previously established benchmark (500 g/100 samples). Taken together, these results demonstrate that AFFL provides a robust, low-waste, and scalable LC-MS-based workflow for chemical analysis of NAM-derived samples.
Indexed as
Identifiers
42709181What Socratic 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 Socratic graph.