Evidence map›Paper›PMID 32558397›Full record

ArticleCPT: pharmacometrics & systems pharmacology2020

A Quantitative Systems Pharmacology Model of Gaucher Disease Type 1 Provides Mechanistic Insight Into the Response to Substrate Reduction Therapy With Eliglustat.

Ruth Abrams, Chanchala D Kaddi, Mengdi Tao, Randolph J Leiser, Giulia Simoni, Federico Reali, John Tolsma, Paul Jasper, Zachary van Rijn, Jing Li and 6 more

Open access · goldAbstract read
In one paragraph

Article in CPT: pharmacometrics & systems pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. What Is a Digital Twin in QSP, and Are We Doing It Right?CPT: pharmacometrics & systems pharmacology · 2026
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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

16 authors at 3 institutions in 2 countries.

Ruth AbramsTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Chanchala D KaddiTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Mengdi TaoTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Randolph J LeiserTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Giulia SimoniFondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
Federico RealiFondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.ORCID 0000-0002-7891-5695
John TolsmaRES Group Inc, Needham, Massachusetts, USA.
Paul JasperRES Group Inc, Needham, Massachusetts, USA.
Zachary van RijnTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Jing LiTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Bradley NiesnerTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Jeffrey S BarrettTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Luca MarchettiFondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI), Rovereto, Italy.
M Judith PeterschmittSanofi Genzyme, Cambridge, Massachusetts, USA.
Karim AzerTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.
Susana Neves-ZaphTranslational Disease Modelling, Digital Data Science, Sanofi, Bridgewater, New Jersey, USA.ORCID 0000-0002-3388-0054
Sanofi (United States) · USUniversity of Trento · ITRenewable Energy Systems (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gaucher's disease type 1 (GD1) leads to significant morbidity and mortality through clinical manifestations, such as splenomegaly, hematological complications, and bone disease. Two types of therapies are currently approved for GD1: enzyme replacement therapy (ERT), and substrate reduction therapy (SRT). In this study, we have developed a quantitative systems pharmacology (QSP) model, which recapitulates the effects of eliglustat, the only first-line SRT approved for GD1, on treatment-naïve or patients with ERT-stabilized adult GD1. This multiscale model represents the mechanism of action of eliglustat that leads toward reduction of spleen volume. Model capabilities were illustrated through the application of the model to predict ERT and eliglustat responses in virtual populations of adult patients with GD1, representing patients across a spectrum of disease severity as defined by genotype-phenotype relationships. In summary, the QSP model provides a mechanistic computational platform for predicting treatment response via different modalities within the heterogeneous GD1 patient population.

Indexed as

Models, BiologicalSystems BiologyAdultEnzyme InhibitorsGaucher DiseaseHumansPyrrolidinesSeverity of Illness IndexSplenomegalyTreatment OutcomeeliglustatEnzyme InhibitorsPyrrolidines

Identifiers

PMID32558397
PMCPMC7376290
OpenAlexW3036599071

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.