Evidence map›Paper›PMID 16770528›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2006

Model-based drug development: the road to quantitative pharmacology.

Liping Zhang, Vikram Sinha, S Thomas Forgue, Sophie Callies, Lan Ni, Richard Peck, Sandra R B Allerheiligen

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

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  9. Pharmacometrics meets statistics-A synergy for modern drug development.CPT: pharmacometrics & systems pharmacology · 2021
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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

7 authors.

Liping ZhangBristol Myers-Squibb, Princeton, NJ, USA.
Vikram Sinha
S Thomas Forgue
Sophie Callies
Lan Ni
Richard Peck
Sandra R B Allerheiligen

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High development costs and low success rates in bringing new medicines to the market demand more efficient and effective approaches. Identified by the FDA as a valuable prognostic tool for fulfilling such a demand, model-based drug development is a mathematical and statistical approach that constructs, validates, and utilizes disease models, drug exposure-response models, and pharmacometric models to facilitate drug development. Quantitative pharmacology is a discipline that learns and confirms the key characteristics of new molecular entities in a quantitative manner, with goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans and enabling critical decision making. Model-based drug development serves as an integral part of quantitative pharmacology. This work reviews the general concept, basic elements, and evolving role of model-based drug development in quantitative pharmacology. Two case studies are presented to illustrate how the model-based drug development approach can facilitate knowledge management and decision making during drug development. The case studies also highlight the organizational learning that comes through implementation of quantitative pharmacology as a discipline. Finally, the prospects of quantitative pharmacology as an emerging discipline are discussed. Advances in this discipline will require continued collaboration between academia, industry and regulatory agencies.

Indexed as

Computer SimulationModels, BiologicalAdultAgedAlgorithmsAntimetabolites, AntineoplasticBiomarkersClinical Trials as TopicDecision MakingDeoxycytidineDose-Response Relationship, DrugDrug IndustryFemaleGemcitabineHumansMaleAntimetabolites, AntineoplasticBiomarkersDeoxycytidineGemcitabineOsteocalcinRaloxifene HydrochlorideSelective Estrogen Receptor Modulators

Identifiers

What OpenQuestion holds

Textmetadata
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.