Evidence map›Paper›PMID 39673036›Full record

ReviewHandbook of experimental pharmacology2025

Application of Quantitative Systems Pharmacology Approaches to Support Pediatric Labeling in Rare Diseases.

Susana Zaph, Randolph J Leiser, Mengdi Tao, Chanchala Kaddi, Christine Xu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Handbook of experimental pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Susana ZaphTranslational Disease Modeling - Translational Medicine, Research & Development, Sanofi-US, Bridgewater, NJ, USA. Susana.zaph@sanofi.com.
Randolph J LeiserTranslational Disease Modeling - Translational Medicine, Research & Development, Sanofi-US, Bridgewater, NJ, USA.
Mengdi TaoTranslational Disease Modeling - Translational Medicine, Research & Development, Sanofi-US, Bridgewater, NJ, USA.
Chanchala KaddiTranslational Disease Modeling - Translational Medicine, Research & Development, Sanofi-US, Bridgewater, NJ, USA.
Christine XuPharmacokinetics, Dynamics, Metabolism - Translational Medicine, Research & Development, Sanofi-US, Bridgewater, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative Systems Pharmacology (QSP) models offer a promising approach to extrapolate drug efficacy across different patient populations, particularly in rare diseases. Unlike conventional empirical models, QSP models can provide a mechanistic understanding of disease progression and therapeutic response by incorporating current disease knowledge into the descriptions of biomarkers and clinical endpoints. This allows for a holistic representation of the disease and drug response. The mechanistic nature of QSP models is well suited to pediatric extrapolation concepts, providing a quantitative method to assess disease and drug response similarity between adults and pediatric patients. The application of a QSP-based assessment of the disease and drug similarity in adult and pediatric patients in the clinical development program of olipudase alfa, a treatment for Acid Sphingomyelinase Deficiency (ASMD), illustrates the potential of this approach.

Indexed as

Drug LabelingRare DiseasesSystems BiologyAnimalsChildHumansModels, BiologicalEfficacy extrapolationModel-informed drug development (MIDD)Pediatric drug developmentQuantitative systems pharmacology (QSP)Rare drug developmentVirtual twins

Identifiers

PMID39673036

What Socratic 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 Socratic graph.