Document Detail


In silico design of clinical trials: a method coming of age.
MedLine Citation:
PMID:  15483415     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVE: To determine the feasibility and potential usefulness of mathematical models in evaluating immunomodulatory strategies in clinical trials of severe sepsis. DESIGN: Mathematical modeling of immunomodulation in simulated patients. SETTING: Computer laboratory. MEASUREMENTS AND MAIN RESULTS: We introduce and evaluate the concept of conducting a randomized clinical trial in silico based on simulated patients generated from a mechanistic mathematical model of bacterial infection, the acute inflammatory response, global tissue dysfunction, and a therapeutic intervention. Trial populations are constructed to reflect heterogeneity in bacterial load and virulence as well as propensity to mount and modulate an inflammatory response. We constructed a cohort of 1,000 trial patients submitted to therapy with one of three different doses of a neutralizing antibody directed against tumor necrosis factor (anti-TNF) for 6, 24, or 48 hrs. We present cytokine profiles over time and expected outcome for each cohort. We identify subgroups with high propensity for being helped or harmed by the proposed intervention and identify early serum markers for each of those subgroups. The mathematical simulation confirms the inability of simple markers to predict outcome of sepsis. The simulation clearly separates cases with favorable and unfavorable outcome on the basis of global tissue dysfunction. Control survival was 62.9% at 1 wk. Depending on dose and duration of treatment, survival ranged from 57.1% to 80.8%. Higher doses of anti-TNF, although effective, also result in considerable harm to patients. A statistical analysis based on a simulated cohort identified markers of favorable or adverse response to anti-TNF treatment. CONCLUSIONS: A mathematical simulation of anti-TNF therapy identified clear windows of opportunity for this intervention as well as populations that can be harmed by anti-TNF therapy. The construction of an in silico clinical trial could provide profound insight into the design of clinical trials of immunomodulatory therapies, ranging from optimal patient selection to individualized dosage and duration of proposed therapeutic interventions.
Authors:
Gilles Clermont; John Bartels; Rukmini Kumar; Greg Constantine; Yoram Vodovotz; Carson Chow
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Critical care medicine     Volume:  32     ISSN:  0090-3493     ISO Abbreviation:  Crit. Care Med.     Publication Date:  2004 Oct 
Date Detail:
Created Date:  2004-10-14     Completed Date:  2004-11-19     Revised Date:  2009-11-03    
Medline Journal Info:
Nlm Unique ID:  0355501     Medline TA:  Crit Care Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  2061-70     Citation Subset:  AIM; IM    
Affiliation:
Department of Critical Care Medicine and Clinical Research, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
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MeSH Terms
Descriptor/Qualifier:
Antibodies, Monoclonal / therapeutic use
Bacterial Infections / complications,  immunology
Clinical Trials as Topic
Cohort Studies
Computer Simulation*
Feasibility Studies
Humans
Immunologic Factors / therapeutic use*
Models, Theoretical*
Systemic Inflammatory Response Syndrome / drug therapy*,  immunology*,  microbiology
Treatment Outcome
Tumor Necrosis Factor-alpha / antagonists & inhibitors,  immunology
Grant Support
ID/Acronym/Agency:
R01-GM62740/GM/NIGMS NIH HHS
Chemical
Reg. No./Substance:
0/Antibodies, Monoclonal; 0/Immunologic Factors; 0/Tumor Necrosis Factor-alpha
Comments/Corrections
Comment In:
Crit Care Med. 2004 Oct;32(10):2159-60   [PMID:  15483435 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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