Evidence map›Paper›PMID 16353928›Full record

ReviewThe AAPS journal2005

Impact of pharmacometrics on drug approval and labeling decisions: a survey of 42 new drug applications.

Venkatesh A Bhattaram, Brian P Booth, Roshni P Ramchandani, B Nhi Beasley, Yaning Wang, Veneeta Tandon, John Z Duan, Raman K Baweja, Patrick J Marroum, Ramana S Uppoor and 5 more

Abstract readReview
In one paragraph

Review in The AAPS journal, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

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  11. SCOUT: An Exploratory Approach to Scouting Dose-Relevant Covariates.CPT: pharmacometrics & systems pharmacology · 2026
    Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Time to Expect More From Pharmacometrics.Clinical pharmacology and therapeutics · 2020
    Article
  17. Review
  18. Review
  19. Orphan drug development: the increasing role of clinical pharmacology.Journal of pharmacokinetics and pharmacodynamics · 2019
    Review
  20. Pharmacometrics and systems pharmacology for metabolic bone diseases.British journal of clinical pharmacology · 2019
    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

15 authors.

Venkatesh A BhattaramFood and Drug Administration, Rockville, MD 20852, USA.
Brian P Booth
Roshni P Ramchandani
B Nhi Beasley
Yaning Wang
Veneeta Tandon
John Z Duan
Raman K Baweja
Patrick J Marroum
Ramana S Uppoor
Nam Atiqur Rahman
Chandrahas G Sahajwalla
J Robert Powell
Mehul U Mehta
Jogarao V S Gobburu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The value of quantitative thinking in drug development and regulatory review is increasingly being appreciated. Modeling and simulation of data pertaining to pharmacokinetic, pharmacodynamic, and disease progression is often referred to as the pharmacometrics analyses. The objective of the current report is to assess the role of pharmacometrics at the US Food and Drug Administration (FDA) in making drug approval and labeling decisions. The New Drug Applications (NDAs) submitted between 2000 and 2004 to the Cardio-renal, Oncology, and Neuropharmacology drug products divisions were surveyed. For those NDA reviews that included a pharmacometrics consultation, the clinical pharmacology scientists ranked the impact on the regulatory decision(s). Of about a total of 244 NDAs, 42 included a pharmacometrics component. Review of NDAs involved independent, quantitative evaluation by FDA pharmacometricians, even when such analysis was not conducted by the sponsor. Pharmacometric analyses were pivotal in regulatory decision making in more than half of the 42 NDAs. Of the 14 reviews that were pivotal to approval related decisions, 5 identified the need for additional trials, whereas 6 reduced the burden of conducting additional trials. Collaboration among the FDA clinical pharmacology, medical, and statistical reviewers and effective communication with the sponsors was critical for the impact to occur. The survey and the case studies emphasize the need for early interaction between the FDA and sponsors to plan the development more efficiently by appreciating the regulatory expectations better.

Indexed as

Data CollectionDrug ApprovalDrug LabelingHumansInvestigational New Drug Application

Identifiers

PMID16353928
PMCPMC2751253

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.