ArticleScientific data2023
A dataset of formulation compositions for self-emulsifying drug delivery systems.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Overcoming the oral delivery challenges of venetoclax: advancing a clinically improved Bcl-2 inhibitor.Drug delivery and translational research · 2026Review
- A Machine Learning Platform for Imputing Missing Critical Quality Attributes in Pharmaceutical Development.The AAPS journal · 2026Article
- Formulation Characteristics of Solid-Dispersible Self-Emulsifying Drug Delivery Systems for Dual Drug Delivery.Pharmaceutics · 2026Article
- Artificial intelligence for drug delivery: Yesterday, today and tomorrow.Acta pharmaceutica Sinica. B · 2026Review
- MakingInternational journal of pharmaceutics: X · 2025Article
- Lung cancer chemo-interception by sulfasalazine and disulfiram codelivered using a nano self-emulsifying drug delivery system in mice.Carcinogenesis · 2025Article
- A formulation dataset of poly(lactide-co-glycolide) nanoparticles for small molecule delivery.Scientific data · 2025Article
- Hallmarks of Polymersome Characterization.ACS materials Au · 2025Review
- Establishing a Pharmacoinformatics Repository of Approved Medicines: A Database to Support Drug Product Development.Molecular pharmaceutics · 2025Article
- Cyclodextrin-based therapeutics delivery systems: A review of current clinical trials.Current research in pharmacology and drug discovery · 2025Review
- Overcoming Challenges in Small-Molecule Drug Bioavailability: A Review of Key Factors and Approaches.International journal of molecular sciences · 2024Review
- Machine learning in drug delivery.Journal of controlled release : official journal of the Controlled Release Society · 2024Review
- A dataset of formulation compositions for self-emulsifying drug delivery systems.Scientific data · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Self-emulsifying drug delivery systems (SEDDS) are a well-established formulation strategy for improving the oral bioavailability of poorly water-soluble drugs. Traditional development of these formulations relies heavily on empirical observation to assess drug and excipient compatibility, as well as to select and optimize the formulation compositions. The aim of this work was to leverage previously developed SEDDS in the literature to construct a comprehensive SEDDS dataset that can be used to gain insights and advance data-driven approaches to formulation development. A dataset comprised of 668 unique SEDDS formulations encompassing 20 poorly water-soluble drugs was curated. While there are still opportunities to enhance the quality and quantity of data on SEDDS, this research lays the groundwork to potentially simplify the SEDDS formulation development process.
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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.