ArticleComputers & chemical engineering2025
Rapid Design of Combination Antimicrobial Therapy against
Article in Computers & chemical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Using Machine Learning to Design Effective Antimicrobial Dosing Regimens.Computers & chemical engineering · 2026Article
- Enhancing the Time-to-Positivity Paradigm for Guidance of Antimicrobial Therapy: A Model-Based Approach.Computers & chemical engineering · 2025Article
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.
Funding
Abstract
Treatment of serious bacterial infections with antimicrobial agents, such as antibiotics, is a major clinical challenge, because of growing bacterial resistance to multiple agents. Combination therapy (i.e. combined dosing of more than one agent) is often used for the purpose, but its systematic design remains a challenge. To address this, we recently reported a method to mathematically model bacterial response to antimicrobial agents, and to use this model for systematic design of clinically relevant combination therapy. The method relies on (a) longitudinal data of bacterial load, estimated from optical density measurements during time-kill experiments in an automated instrument, and (b) use of these data to fit a mathematical model for combination therapy design. In this work, we studied an application of the proposed method to (a) an important bacterial pathogen (
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.