Alternate virtual populations elucidate the type I interferon signature predictive of the response to rituximab in rheumatoid arthritis

BMC Bioinformatics

Volumn 14, Issue 1, 2013, Pages

  Schmidt, Brian J ^a   Casey, Fergal P ^a   Paterson, Thomas ^a   Chan, Jason R ^a  

^a Entelos Holding Corporation   (United States)

Author keywords

Biomarker; Biosimulation; Drug development; Mechanistic modeling; Patient population; Personalized medicine; Pharmaceutical research development

Indexed keywords

BIOSIMULATION; DRUG DEVELOPMENT; MECHANISTIC MODELING; PATIENT POPULATION; PERSONALIZED MEDICINES; PHARMACEUTICAL RESEARCH;

ALGORITHMS; BIOMARKERS; CELL CULTURE; DRUG PRODUCTS; EXPERIMENTS; FIBROBLASTS; KNOWLEDGE MANAGEMENT; PATIENT TREATMENT; TOOLS;

POPULATION STATISTICS;

ANTIRHEUMATIC AGENT; BETA INTERFERON; BIOLOGICAL MARKER; IMMUNOLOGIC FACTOR; MONOCLONAL ANTIBODY; RITUXIMAB;

ALGORITHM; ARTHRITIS, RHEUMATOID; B LYMPHOCYTE; COMPUTER SIMULATION; FEMALE; FIBROBLAST; HUMAN; IMMUNOLOGY; MACROPHAGE; MALE; METABOLISM; ARTICLE; RHEUMATOID ARTHRITIS;

ALGORITHMS; ANTIBODIES, MONOCLONAL, MURINE-DERIVED; ANTIRHEUMATIC AGENTS; ARTHRITIS, RHEUMATOID; B-LYMPHOCYTES; BIOLOGICAL MARKERS; COMPUTER SIMULATION; FEMALE; FIBROBLASTS; HUMANS; IMMUNOLOGIC FACTORS; INTERFERON-BETA; MACROPHAGES; MALE;

EID: 84880026485     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-221     Document Type: Article

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