ReviewPharmaceutical research2016
Drug Disposition Classification Systems in Discovery and Development: A Comparative Review of the BDDCS, ECCS and ECCCS Concepts.
Review in Pharmaceutical research, 2016. 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
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
13 citing papers in PubMed.
- Enhancing Therapeutic Efficacy Through Tailored Pharmacokinetics: A Review of Mesoporous Silica Nanoparticle-Based Delivery Systems.International journal of nanomedicine · 2026Review
- Cross-Species Multitask Learning with Molecular and ADME Descriptors for Liver Microsomal Metabolic Stability.Computational and structural biotechnology journal · 2026Article
- Biowaiver based on biopharmaceutics classification system: Considerations and requirements.Pharmaceutical science advances · 2024Review
- A Window for Enhanced Oral Delivery of Therapeutics via Lipid Nanoparticles.Drug design, development and therapy · 2024Review
- Simplifying the Extended Clearance Concept Classification System (EC3S) to Guide Clearance Prediction in Drug Discovery.Pharmaceutical research · 2023Article
- IVIVE: Facilitating the Use ofToxics · 2022Review
- Novel Bruton's Tyrosine Kinase inhibitor remibrutinib: Drug-drug interaction potential as a victim of CYP3A4 inhibitors based on clinical data and PBPK modeling.Clinical and translational science · 2022Article
- Prediction of Drug Clearance from Enzyme and Transporter Kinetics.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Use of imaging to assess the activity of hepatic transporters.Expert opinion on drug metabolism & toxicology · 2020Review
- Advancing internal exposure and physiologically-based toxicokinetic modeling for 21st-century risk assessments.Journal of exposure science & environmental epidemiology · 2019Review
- Rapid experimental measurements of physicochemical properties to inform models and testing.The Science of the total environment · 2018Article
- Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics.Toxicological sciences : an official journal of the Society of Toxicology · 2018Article
- Identification of cryptolepine metabolites in rat and human hepatocytes and metabolism and pharmacokinetics of cryptolepine in Sprague Dawley rats.BMC pharmacology & toxicology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BDDCS, ECCS and ECCCS are compound disposition classification concepts that aim to streamline, de-risk and speed-up drug development. Although all three systems have the same purpose and are based on classifying drugs into four main categories, they have different backgrounds and contrast in their criteria. Here the details, differences and most important applications of the three systems are reviewed with particular emphasis of their roles for drug discovery and development.
Indexed as
Identifiers
27439505What OpenQuestion 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 OpenQuestion graph.