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Record W2134794720 · doi:10.1517/17425255.4.9.1143

Whole body physiologically-based pharmacokinetic models: their use in clinical drug development

2008· review· en· W2134794720 on OpenAlexaff
Andrea N. Edginton, Frank‐Peter Theil, Walter Schmitt, Stefan Willmann

Bibliographic record

VenueExpert Opinion on Drug Metabolism & Toxicology · 2008
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDrug developmentPharmacokineticsDrugPharmacologyPhysiologically based pharmacokinetic modellingMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination. OBJECTIVES: To review the current state of WB-PBPK model use in the clinical phases of drug development. METHODS: A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed. CONCLUSIONS: This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.934
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.329
GPT teacher head0.494
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations152
Published2008
Admission routes1
Has abstractyes

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