In silico clinical trials for pediatric orphan diseases

A. Carlier; Aliaksei S. Vasilevich; M. Marechal; Jan de Boer; L. Geris

doi:10.1038/s41598-018-20737-y

In silico clinical trials for pediatric orphan diseases

A. Carlier
, Aliaksei S. Vasilevich
, M. Marechal
, Jan de Boer
, L. Geris (Corresponding author)

Research output: Contribution to journal › Article › Academic › peer-review

45 Citations (Scopus)

81 Downloads (Pure)

Abstract

To date poor treatment options are available for patients with congenital pseudarthrosis of the tibia (CPT), a pediatric orphan disease. In this study we have performed an in silico clinical trial on 200 virtual subjects, generated from a previously established model of murine bone regeneration, to tackle the challenges associated with the small, pediatric patient population. Each virtual subject was simulated to receive no treatment and bone morphogenetic protein (BMP) treatment. We have shown that the degree of severity of CPT is significantly reduced with BMP treatment, although the effect is highly subject-specific. Using machine learning techniques we were also able to stratify the virtual subject population in adverse responders, non-responders, responders and asymptomatic. In summary, this study shows the potential of in silico medicine technologies as well as their implications for other orphan diseases.

Original language	English
Article number	2465
Number of pages	9
Journal	Scientific Reports
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41598-018-20737-y
Publication status	Published - 1 Dec 2018
Externally published	Yes

Funding

Liesbet Geris acknowledges the European Research Council under the European Union’s Seventh Framework Program ERC grant agreement n°279100. Aurélie Carlier acknowledges her post-doctoral fellowship of the Research Foundation Flanders (FWO-Vlaanderen). The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Hercules Foundation and the Flemish Government-department EWI. This work is part of Prometheus, the Leuven R&D Division of Skeletal Tissue Engineering of the KU Leuven.

Keywords

Adolescent
Biomarkers, Pharmacological/metabolism
Bone Morphogenetic Proteins/therapeutic use
Bone Regeneration/drug effects
Case-Control Studies
Child
Clinical Trials as Topic
Female
Humans
Male
Pseudarthrosis/congenital
Rare Diseases/drug therapy
Tibia/drug effects
Virtual Reality

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title = "In silico clinical trials for pediatric orphan diseases",

abstract = "To date poor treatment options are available for patients with congenital pseudarthrosis of the tibia (CPT), a pediatric orphan disease. In this study we have performed an in silico clinical trial on 200 virtual subjects, generated from a previously established model of murine bone regeneration, to tackle the challenges associated with the small, pediatric patient population. Each virtual subject was simulated to receive no treatment and bone morphogenetic protein (BMP) treatment. We have shown that the degree of severity of CPT is significantly reduced with BMP treatment, although the effect is highly subject-specific. Using machine learning techniques we were also able to stratify the virtual subject population in adverse responders, non-responders, responders and asymptomatic. In summary, this study shows the potential of in silico medicine technologies as well as their implications for other orphan diseases.",

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AU - Geris, L.

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N2 - To date poor treatment options are available for patients with congenital pseudarthrosis of the tibia (CPT), a pediatric orphan disease. In this study we have performed an in silico clinical trial on 200 virtual subjects, generated from a previously established model of murine bone regeneration, to tackle the challenges associated with the small, pediatric patient population. Each virtual subject was simulated to receive no treatment and bone morphogenetic protein (BMP) treatment. We have shown that the degree of severity of CPT is significantly reduced with BMP treatment, although the effect is highly subject-specific. Using machine learning techniques we were also able to stratify the virtual subject population in adverse responders, non-responders, responders and asymptomatic. In summary, this study shows the potential of in silico medicine technologies as well as their implications for other orphan diseases.

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In silico clinical trials for pediatric orphan diseases

Abstract

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Keywords

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