Evidence map›Paper›PMID 33608998›Full record

ReviewCPT: pharmacometrics & systems pharmacology2021

Opportunities and challenges for applying model-informed drug development approaches to gene therapies.

Artur Belov, Kimberly Schultz, Richard Forshee, Million A Tegenge

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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Trial
  2. QSP model for AAV-mediated antibody delivery in rat brain.Journal of pharmacokinetics and pharmacodynamics · 2026
    Article
  3. Review
  4. Review
  5. Scoping review of the role of pharmacometrics in model-informed drug development.Journal of pharmacokinetics and pharmacodynamics · 2025
    Article
  6. Article
  7. Review
  8. Review
  9. Allometric-like scaling of AAV gene therapy for systemic protein delivery.Molecular therapy. Methods & clinical development · 2022
    Article
  10. 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

4 authors.

Artur BelovOffice of Biostatistics & Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration (FDA), Silver Spring, Maryland, USA.
Kimberly SchultzOffice of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration (FDA), Silver Spring, Maryland, USA.
Richard ForsheeOffice of Biostatistics & Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration (FDA), Silver Spring, Maryland, USA.
Million A TegengeOffice of Biostatistics & Epidemiology, Center for Biologics Evaluation and Research, US Food and Drug Administration (FDA), Silver Spring, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As part of the US Food and Drug Administration (FDA)'s Prescription Drug User Fee Act (PDUFA) VI commitments, the Center for Biologics Evaluation and Research (CBER) and Center for Drug Evaluation and Research (CDER) are conducting a model-informed drug development (MIDD) pilot program. Sponsor(s) who apply and are selected will be granted meetings that aim to facilitate the application of MIDD approaches throughout the product development lifecycle and the regulatory process. Due to their complex mechanisms of action and limited clinical experience, cell and gene therapies have the potential to benefit from the application of MIDD methods, which may facilitate their safety and efficacy evaluations. Leveraging data that are generated from all stages of drug development into appropriate modeling and simulation techniques that inform decisions remains challenging. Additional discussions regarding the application of quantitative modeling approaches to drug development decisions, such as through the MIDD pilot program, may be crucial for both the sponsor(s) and regulatory review teams. Here, we share some perspectives on the opportunities and challenges for utilizing MIDD approaches for product review, which we hope will encourage investigators to publish their experiences and application of MIDD in gene therapy product development.

Indexed as

Computer SimulationDependovirusDrug DevelopmentGenetic TherapyHumansImmunotherapy, AdoptiveModels, BiologicalOncolytic VirotherapyPharmacokineticsResearch DesignSafetyTechnology Assessment, BiomedicalTreatment Outcome

Identifiers

PMID33608998
PMCPMC8099439

What OpenQuestion holds

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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.