ReviewDrug discovery today2021
Using response surface models to analyze drug combinations.
Review in Drug discovery today, 2021. 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, 12 citations in OpenAlex.
- On the existence conditions of interaction indices in response surface models.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Targeting glycerophospholipid biosynthesis overcomes chemoresistance driven by SLFN11 loss in Ewing sarcoma.Cell death & disease · 2026Article
- Adjustment for day-to-day variability in the estimation of effective concentrations for the assessment of mixture toxicity.Archives of toxicology · 2025Article
- Drugtamer-PROTAC Conjugation Strategy for Targeted PROTAC Delivery and Synergistic Antitumor Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Interactions of plumbagin with five common antibiotics against Staphylococcus aureus in vitro.PloS one · 2024Article
- Systematic review of computational methods for drug combination prediction.Computational and structural biotechnology journal · 2022Review
- Data vignettes for the application of response surface models in drug combination analysis.Data in brief · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Quantitative evaluation of how drugs combine to elicit a biological response is crucial for drug development. Evaluations of drug combinations are often performed using index-based methods, which are known to be biased and unstable. We examine how these methods can produce misleadingly structured patterns of bias, leading to erroneous judgments of synergy or antagonism. By contrast, response surface models are less prone to these defects and can be applied to a wide range of data that have appeared in recent literature, including the measurement of combination therapeutic windows and the analysis of discrete experimental measures, three-way drug combinations, and atypical response behaviors.
Indexed as
Identifiers
What 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.