Evidence map›Paper›PMID 40757668›Full record

ArticleCPT: pharmacometrics & systems pharmacology2025

Transforming Pediatric Rare Disease Drug Development: Enhancing Clinical Trials and Regulatory Evidence With Virtual Patients.

Fianne Sips, Marco Virgolin, Giuseppe Pasculli, Federico Reali, Alessio Paris, Annette Janus, Yann Godfrin, Daniel Röshammar, Luca Marchetti, Jane Knöchel

Abstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

10 authors.

Fianne SipsInSilicoTrials Technologies BV, 's-Hertogenbosch, the Netherlands.
Marco VirgolinInSilicoTrials Technologies BV, 's-Hertogenbosch, the Netherlands.ORCID 0000-0001-8905-9313
Giuseppe PasculliInSilicoTrials Technologies Spa, Trieste, Italy.ORCID 0000-0002-0499-2292
Federico RealiFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID 0000-0002-7891-5695
Alessio ParisFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID 0000-0002-6667-9330
Annette JanusAxoltis Pharma, Bioparc Laennec, Lyon, France.ORCID 0009-0002-0336-7994
Yann GodfrinAxoltis Pharma, Bioparc Laennec, Lyon, France.
Daniel RöshammarInSilicoTrials Technologies Spa, Trieste, Italy.ORCID 0009-0005-1633-7999
Luca MarchettiFondazione the Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID 0000-0001-9043-7705
Jane KnöchelInSilicoTrials Technologies Spa, Trieste, Italy.ORCID 0000-0001-9839-2433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug development in pediatric rare diseases is complicated by practical and ethical constraints on clinical trial design, stemming from small, highly heterogeneous, and vulnerable patient populations. Virtual patients (VPs) created with machine-learning (ML), mechanistically driven computational approaches, or hybrids thereof, have the potential to expedite and maximize the impact of trials. We discuss the potential of VPs to transform the efficiency and impact of clinical trials in pediatric rare diseases, based on adult and pediatric examples.

Indexed as

Computer SimulationDigital HealthDrug DevelopmentMachine LearningRare DiseasesAdultChildClinical Trials as TopicHumansNetwork Pharmacology

Identifiers

PMID40757668
PMCPMC12625110

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.