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Criteria to select molecular targets for anti-fibrotic therapy

Distler, J. H. W. ; Distler, O.

In: Rheumatology, 2008, vol. 47, p. v12-v13

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    Titre
    • Criteria to select molecular targets for anti-fibrotic therapy
    Auteur
    • Distler, J. H. W.. Department for Internal Medicine 3 and Institute for Clinical Immunology, University of Erlangen-Nuremberg, Erlangen, Germany and Center of Experimental Rheumatology and Center of Integrative Human Physiology, Rheumaklinik, University Hospital Zurich, Zurich, Switzerland.
    • Distler, O.. Department for Internal Medicine 3 and Institute for Clinical Immunology, University of Erlangen-Nuremberg, Erlangen, Germany and Center of Experimental Rheumatology and Center of Integrative Human Physiology, Rheumaklinik, University Hospital Zurich, Zurich, Switzerland.
    Type de document
    • Postprint
    Identifiant OAI-PMH
    • oai:doc.rero.ch:300640
    Summary
    Tissue fibrosis is a major cause of morbidity and mortality in SSc. An increasing number of promising molecular targets for anti-fibrotic therapies have been described recently. However, the number of patients eligible for clinical trials is limited in SSc. The present article discusses criteria to select the most promising molecular targets for clinical trials in SSc. Based on consensus among experts, important criteria for the selection of molecular-based therapies were as follows: First, there should be strong experimental evidence that targeting the molecule of interest inhibits fibrosis. Optimally, the anti-fibrotic effects should be confirmed in at least two complementary animal models of SSc. Second, inhibitors of the molecule of interest should be clinically available. Third, clinical experience with the drug of interest in other diseases hastens the initiation of clinical trials and reduces the risk of unexpected side-effects. Finally, funding for clinical trials with the drug of interest in SSc should be available. We propose that the priority of novel targets for evaluation in clinical trials in SSc might be selected based on these consensus criteria