Evidence map›Paper›PMID 34139105›Full record

ArticleCPT: pharmacometrics & systems pharmacology2021

A systems pharmacology model for gene therapy in sickle cell disease.

Bo Zheng, Lucia Wille, Karsten Peppel, David Hagen, Andrew Matteson, Jeffrey Ahlers, James Schaff, Fei Hua, Theresa Yuraszeck, Enoch Cobbina and 4 more

Open access · goldAbstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Mathematical modeling of SCD: a literature review.Journal of sickle cell disease · 2025
    Review
  2. Future Directions for Quantitative Systems Pharmacology.Handbook of experimental pharmacology · 2025
    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

14 authors at 2 institutions in 1 country.

Bo ZhengCSL Behring, King of Prussia, Pennsylvania, USA.
Lucia WilleApplied BioMath LLC, Concord, Massachusetts, USA.
Karsten PeppelCSL Behring, King of Prussia, Pennsylvania, USA.
David HagenApplied BioMath LLC, Concord, Massachusetts, USA.ORCID 0000-0003-0992-8465
Andrew MattesonApplied BioMath LLC, Concord, Massachusetts, USA.
Jeffrey AhlersCSL Behring, King of Prussia, Pennsylvania, USA.
James SchaffApplied BioMath LLC, Concord, Massachusetts, USA.
Fei HuaApplied BioMath LLC, Concord, Massachusetts, USA.
Theresa YuraszeckCSL Behring, King of Prussia, Pennsylvania, USA.
Enoch CobbinaCSL Behring, King of Prussia, Pennsylvania, USA.ORCID 0000-0003-0634-8764
Joshua F ApgarApplied BioMath LLC, Concord, Massachusetts, USA.ORCID 0000-0002-3396-1874
John M BurkeApplied BioMath LLC, Concord, Massachusetts, USA.
John RobertsCSL Behring, King of Prussia, Pennsylvania, USA.
Raibatak DasApplied BioMath LLC, Concord, Massachusetts, USA.
Applied BioMath (United States) · USCSL (United States) · US

Funding

CSL Behring
6 · The paper itself

Abstract

We developed a mathematical model for autologous stem cell therapy to cure sickle cell disease (SCD). Experimental therapies using this approach seek to engraft stem cells containing a curative gene. These stem cells are expected to produce a lifelong supply of red blood cells (RBCs) containing an anti-sickling hemoglobin. This complex, multistep treatment is expensive, and there is limited patient data available from early clinical trials. Our objective was to quantify the impact of treatment parameters, such as initial stem cell dose, efficiency of lentiviral transduction, and degree of bone marrow preconditioning on engraftment efficiency, peripheral RBC numbers, and anti-sickling hemoglobin levels over time. We used ordinary differential equations to model RBC production from progenitor cells in the bone marrow, and hemoglobin assembly from its constituent globin monomers. The model recapitulates observed RBC and hemoglobin levels in healthy and SCD phenotypes. Treatment simulations predict dynamics of stem cell engraftment and RBC containing the therapeutic gene product. Post-treatment dynamics show an early phase of reconstitution due to short lived stem cells, followed by a sustained RBC production from stable engraftment of long-term stem cells. This biphasic behavior was previously reported in the literature. Sensitivity analysis of the model quantified relationships between treatment parameters and efficacy. The initial dose of transduced stem cells, and the intensity of myeloablative bone marrow preconditioning are predicted to most positively impact long-term outcomes. The quantitative systems pharmacology approach used here demonstrates the value of model-assisted therapeutic design for gene therapies in SCD.

Indexed as

Models, TheoreticalAnemia, Sickle CellBone Marrow CellsErythrocytesGenetic TherapyHemoglobinsHumansNetwork PharmacologyStem Cell TransplantationHemoglobins

Identifiers

PMID34139105
PMCPMC8302248
OpenAlexW3172498960

What OpenQuestion 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 OpenQuestion graph.