Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.

Nielsen, Jens Christian et al.·Journal of medicinal chemistry·2024·
RPEP-089552024RETHINKTHC RESEARCH DATABASErethinkthc.com/research

Quick Facts

Study Type
Not classified
Evidence
Not graded
Sample
Not reported

What This Study Found

Key Numbers

How They Did This

Why This Research Matters

What This Study Doesn't Tell Us

Trust & Context

Original Title:
Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.
Published In:
Journal of medicinal chemistry, 67(14), 11814-11826 (2024)
Database ID:
RPEP-08955

Evidence Hierarchy

Meta-Analysis / Systematic Review
Randomized Controlled Trial
Cohort / Case-Control
Cross-Sectional / ObservationalSnapshot without intervening
This study
Case Report / Animal Study
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Cite This Study

RPEP-08955·https://rethinkpeptides.com/research/RPEP-08955

APA

Nielsen, Jens Christian; Hjo Rringgaard, Claudia; Nygaard, Mads Mo Rup; Wester, Anita; Elster, Lisbeth; Porsgaard, Trine; Mikkelsen, Randi Bonke; Rasmussen, Silas; Madsen, Andreas Nygaard; Schlein, Morten; Vrang, Niels; Rigbolt, Kristoffer; Dalbo Ge, Louise S. (2024). Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.. Journal of medicinal chemistry, 67(14), 11814-11826. https://doi.org/10.1021/acs.jmedchem.4c00417

MLA

Nielsen, Jens Christian, et al. "Machine-Learning-Guided Peptide Drug Discovery: Development of GLP-1 Receptor Agonists with Improved Drug Properties.." Journal of medicinal chemistry, 2024. https://doi.org/10.1021/acs.jmedchem.4c00417

RethinkPeptides

RethinkPeptides Research Database. "Machine-Learning-Guided Peptide Drug Discovery: Development ..." RPEP-08955. Retrieved from https://rethinkpeptides.com/research/nielsen-2024-machinelearningguided-peptide-drug-discovery

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Study data sourced from PubMed, a service of the U.S. National Library of Medicine, National Institutes of Health.

This study breakdown was produced by the RethinkPeptides research team. We analyze and report published research findings without making health recommendations. All interpretations are based solely on the published abstract and study data.