Evidence map›Paper›PMID 29928905›Full record

ArticleProgress in biophysics and molecular biology2018

Chaos synchronization and Nelder-Mead search for parameter estimation in nonlinear pharmacological systems: Estimating tumor antigenicity in a model of immunotherapy.

Nikhil Pillai, Morgan Craig, Aristeidis Dokoumetzidis, Sorell L Schwartz, Robert Bies, Immanuel Freedman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Progress in biophysics and molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Nikhil PillaiUniversity at Buffalo, State University of New York, USA. Electronic address: npillai2@buffalo.edu.
Morgan CraigUniversité de Montréal, Canada. Electronic address: morgan.craig@umontreal.ca.
Aristeidis DokoumetzidisUniversity of Athens, Greece. Electronic address: adokoum@pharm.uoa.gr.
Sorell L SchwartzGeorgetown University, USA. Electronic address: sorell.schwartz@georgetown.edu.
Robert BiesUniversity at Buffalo, State University of New York, USA. Electronic address: robertbi@buffalo.edu.
Immanuel FreedmanFreedman Patent, USA. Electronic address: freedman@freedmanpatent.com.

Funding

Quantification and prediction of treatment efficacy for HIV cure strategiesDP5OD019851 · OD · JOHNS HOPKINS UNIVERSITY · PI HILL, ALISON LYNN · 2014 to 2018
$2.1M
NIH HHS DP5 OD019851
6 · The paper itself

Abstract

In mathematical pharmacology, models are constructed to confer a robust method for optimizing treatment. The predictive capability of pharmacological models depends heavily on the ability to track the system and to accurately determine parameters with reference to the sensitivity in projected outcomes. To closely track chaotic systems, one may choose to apply chaos synchronization. An advantageous byproduct of this methodology is the ability to quantify model parameters. In this paper, we illustrate the use of chaos synchronization combined with Nelder-Mead search to estimate parameters of the well-known Kirschner-Panetta model of IL-2 immunotherapy from noisy data. Chaos synchronization with Nelder-Mead search is shown to provide more accurate and reliable estimates than Nelder-Mead search based on an extended least squares (ELS) objective function. Our results underline the strength of this approach to parameter estimation and provide a broader framework of parameter identification for nonlinear models in pharmacology.

Indexed as

ImmunotherapyModels, ImmunologicalNonlinear DynamicsHumansNeoplasmsChaos synchronizationImmunotherapyNonlinear modelsParameter estimationParameter identifiability

Identifiers

PMID29928905
PMCPMC6263737

What OpenQuestion holds

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Registered trials

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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.