ArticleJournal of process control2011
Controlling the Evolution of Resistance.
Article in Journal of process control, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 15 citations in OpenAlex.
- Addressing antimicrobial resistance: Current challenges, emerging strategies, and an AI-powered, community-driven approach.PNAS nexus · 2026Review
- Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- Significant Unresolved Questions and Opportunities for Bioengineering in Understanding and Treating COVID-19 Disease Progression.Cellular and molecular bioengineering · 2020Article
- Optimal control modulation of HIV reservoir formation rate by antigen infusion.Proceedings of the ... IEEE Conference on Decision & Control. IEEE Conference on Decision & Control · 2019Article
- Robust closed-loop minimal sampling method for HIV therapy switching strategies.IEEE transactions on bio-medical engineering · 2012Article
- Dynamics of melanoma tumor therapy with vesicular stomatitis virus: explaining the variability in outcomes using mathematical modeling.Gene therapy · 2012Article
- HIV model parameter estimates from interruption trial data including drug efficacy and reservoir dynamics.PloS one · 2012Article
- Resistance evolution in HIV - modeling when to intervene.Proceedings of the ... American Control Conference. American Control Conference · 2012Article
- Nonlinear observer output-feedback MPC treatment scheduling for HIV.Biomedical engineering online · 2011Article
- Approximate-model closed-loop minimal sampling method for HIV viral-load minima detection.Proceedings of the ... American Control Conference. American Control Conference · 2011Article
- Measurement error robustness of a closed-loop minimal sampling method for HIV therapy switching.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2011Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Evolution has long been understood as the driving force for many problems of medical interest. The evolution of drug resistance in HIV and bacterial infections is recognized as one of the most significant emerging problems in medicine. In cancer therapy, the evolution of resistance to chemotherapeutic agents is often the differentiating factor between effective therapy and disease progression or death. Interventions to manage the evolution of resistance have, up to this point, been based on steady-state analysis of mutation and selection models. In this paper, we review the mathematical methods applied to studying evolution of resistance in disease. We present a broad review of several classical applications of mathematical modeling of evolution, and review in depth two recent problems which demonstrate the potential for interventions which exploit the dynamic behavior of resistance evolution models. The first problem addresses the problem of sequential treatment failures in HIV; we present a review of our recent publications addressing this problem. The second problem addresses a novel approach to gene therapy for pancreatic cancer treatment, where selection is used to encourage optimal spread of susceptibility genes through a target tumor, which is then eradicated during a second treatment phase. We review the recent in Vitro laboratory work on this topic, present a new mathematical model to describe the treatment process, and show why model-based approaches will be necessary to successfully implement this novel and promising approach.
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.