Evidence map›Paper›PMID 34562342›Full record

ReviewCPT: pharmacometrics & systems pharmacology2021

Metaheuristics for pharmacometrics.

Seongho Kim, Andrew C Hooker, Yu Shi, Grace Hyun J Kim, Weng Kee Wong

Abstract readReview
In one paragraph

Review in CPT: pharmacometrics & systems pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Metaheuristics for pharmacometrics.CPT: pharmacometrics & systems pharmacology · 2021
    Review
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

5 authors.

Seongho KimDepartment of Oncology, Wayne State University, Detroit, Michigan, USA.
Andrew C HookerDepartment of Pharmacy, Uppsala University, Uppsala, Sweden.
Yu ShiDepartment of Biostatistics, University of California Los Angeles, Los Angeles, California, USA.
Grace Hyun J KimDepartment of Biostatistics, University of California Los Angeles, Los Angeles, California, USA.
Weng Kee WongDepartment of Biostatistics, University of California Los Angeles, Los Angeles, California, USA.

Funding

Tumor Biology and Microenvironment (Program 1)P30CA022453 · NCI · WAYNE STATE UNIVERSITY · PI Julie Lynn Boerner · 1985 to 2026
$68.4M
Designing Efficient Designs under Model Uncertainty for Biological StudiesR01GM107639 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WONG, WENG K · 2014 to 2017
$1.0M
NCI NIH HHS P30 CA022453NIGMS NIH HHS R01 GM107639
6 · The paper itself

Abstract

Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature-inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be particularly flexible and useful in solving complicated optimization problems in computer science and engineering. A common practice with metaheuristics is to hybridize it with another suitably chosen algorithm for enhanced performance. This paper reviews metaheuristic algorithms and demonstrates some of its utility in tackling pharmacometric problems. Specifically, we provide three applications using one of its most celebrated members, particle swarm optimization (PSO), and show that PSO can effectively estimate parameters in complicated nonlinear mixed-effects models and to gain insights into statistical identifiability issues in a complex compartment model. In the third application, we demonstrate how to hybridize PSO with sparse grid, which is an often-used technique to evaluate high dimensional integrals, to search for

Indexed as

AlgorithmsComputer SimulationHumansNormal Distribution

Identifiers

PMID34562342
PMCPMC8592519

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.