Unblocking blockbusters: Using boolean text-mining to optimise clinical trial design and timeline for novel anticancer drugs

Cancer Informatics

Volumn 7, Issue , 2009, Pages 231-238

  Epstein, Richard J ^a,b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b ST VINCENT S HOSPITAL   (Australia)

Author keywords

Bibliometrics; Clinical trials; Drug development; Medical informatics; Oncology

Indexed keywords

ANTIMETASTATIC AGENT; ANTINEOPLASTIC AGENT; MAMMALIAN TARGET OF RAPAMYCIN INHIBITOR; METALLOPROTEINASE INHIBITOR; PROTEIN TYROSINE KINASE INHIBITOR; TEMSIROLIMUS; TUMOR MARKER;

ANTINEOPLASTIC ACTIVITY; ARTICLE; CANCER INHIBITION; CANCER RESEARCH; CANCER SURVIVAL; CANCER THERAPY; COST MINIMIZATION ANALYSIS; DATA MINING; DRUG COST; DRUG DESIGN; GOLD STANDARD; HUMAN; KIDNEY CARCINOMA; MEDICAL INFORMATICS; ONCOLOGY; QUALITY OF LIFE; SCIENTIFIC LITERATURE; AKT SIGNALING; CANCER ADJUVANT THERAPY; CANCER PALLIATIVE THERAPY; CLINICAL TRIAL (TOPIC); CONTROLLED STUDY; COST EFFECTIVENESS ANALYSIS; DRUG EFFICACY; MAINTENANCE CHEMOTHERAPY; MTOR SIGNALING; PERSONALIZED MEDICINE; PHENOTYPE; STUDY DESIGN;

EID: 76749100919     PISSN: 11769351     EISSN: 11769351     Source Type: Journal    
DOI: 10.4137/cin.s2666     Document Type: Article

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