ArticleACS central science2023
Open-Source Chromatographic Data Analysis for Reaction Optimization and Screening.
Article in ACS central science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Revealing deamidation and isoaspartate formation during peptide analysis, purification and storage by tandem mass spectrometry.RSC medicinal chemistry · 2026Article
- Advancing Organic Chemistry Using High-Throughput Experimentation.Angewandte Chemie (International ed. in English) · 2025Review
- Chemical Process Development in the Pharmaceutical Industry in Europe-Insights and Perspectives from Industry Scientists.Angewandte Chemie (International ed. in English) · 2025Review
- Emerging trends in the optimization of organic synthesis through high-throughput tools and machine learning.Beilstein journal of organic chemistry · 2025Review
- Self-Driving Laboratories for Chemistry and Materials Science.Chemical reviews · 2024Review
- Calibration-free reaction yield quantification by HPLC with a machine-learning model of extinction coefficients.Chemical science · 2024Article
- Parallel multi-droplet platform for reaction kinetics and optimization.Chemical science · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automation and digitalization solutions in the field of small molecule synthesis face new challenges for chemical reaction analysis, especially in the field of high-performance liquid chromatography (HPLC). Chromatographic data remains locked in vendors' hardware and software components, limiting their potential in automated workflows and data science applications. In this work, we present an open-source Python project called MOCCA for the analysis of HPLC-DAD (photodiode array detector) raw data. MOCCA provides a comprehensive set of data analysis features, including an automated peak deconvolution routine of known signals, even if overlapped with signals of unexpected impurities or side products. We highlight the broad applicability of MOCCA in four studies: (i) a simulation study to validate MOCCA's data analysis features; (ii) a reaction kinetics study on a Knoevenagel condensation reaction demonstrating MOCCA's peak deconvolution feature; (iii) a closed-loop optimization study for the alkylation of 2-pyridone without human control during data analysis; (iv) a well plate screening of categorical reaction parameters for a novel palladium-catalyzed cyanation of aryl halides employing
Identifiers
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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.