{"id":"W2981176489","doi":"10.12927/hcpol.2019.25937","title":"Orphan Drug Pricing and Costs: A Case Study of Kalydeco and Orkambi","year":2019,"lang":"en","type":"article","venue":"Healthcare policy","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Ivacaftor; Orphan drug; Revenue; Cystic fibrosis; Drug pricing; Narrative review; Medicine; Business; Actuarial science; Intensive care medicine; Internal medicine; Cystic fibrosis transmembrane conductance regulator; Bioinformatics; Finance","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006112177,0.0001827266,0.000973916,0.0005564471,0.0001747684,0.00004957729,0.0001090901,0.00009926044,0.00005460847],"category_scores_gemma":[0.0009019593,0.0002267734,0.00003777792,0.0002941282,0.00004976312,0.0002650094,0.0001009383,0.0001814096,0.0001506927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004865477,"about_ca_system_score_gemma":0.0002253813,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2080218,"about_ca_topic_score_gemma":0.0120789,"domain_scores_codex":[0.9960299,0.0003727636,0.002559772,0.00055866,0.00007534447,0.0004035323],"domain_scores_gemma":[0.9971011,0.0006747521,0.001334342,0.0005095092,0.00007481482,0.0003054336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002093745,0.0002096783,0.8924124,0.001554273,0.00006725288,0.00002686727,0.0353388,0.00000989815,0.000001822409,0.06623247,0.001179785,0.002945797],"study_design_scores_gemma":[0.01656677,0.003815937,0.5484104,0.001302143,0.00005828696,0.003048437,0.3601322,0.00940915,0.00001836257,0.01775765,0.03686344,0.002617217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672664,0.002856891,0.00001640347,0.02726328,0.0001842937,0.001478127,0.0001136992,0.00003211122,0.0007888291],"genre_scores_gemma":[0.9925649,0.0002163834,0.0002782631,0.006341833,0.0002116608,0.00005231761,0.00000465472,0.00003267913,0.0002973119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.344002,"threshold_uncertainty_score":0.924755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2408333544792701,"score_gpt":0.463508640434325,"score_spread":0.222675285955055,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}