Signature development for the detection of Pulmonary Hypertension
Luca Semeraro
Signature development for the detection of Pulmonary Hypertension.
Rel. Mauro Gasparini, Matthieu Villeneuve. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2021
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Abstract
This thesis follows and assembles what I did during a six-months traineeship at Actelion Janssen. Once the company's therapeutic areas of interest are briefly described, the emphasis in this work is on one of them: Pulmonary Hypertension (PH). Then, a WHO classification and available diagnostic tests for this disease are examined and two clinical studies in PH labelled TRACE and CIPHER are outlined: the first is a multicenter, double-blind, placebo-controlled, phase 4 study to evaluate the effect of Uptravi treatment on the daily life physical activity of patients with pulmonary arterial hypertension, while the second one is a prospective, multicenter study designed to identify a biomarker signature for the early detection of PH and another signature to distinguish two sub-classes of this pathology from the others.
The problem presented in the latter belongs to the challenging field of genetic analysis and is here addressed by developing a process for the identification of blood-based biomarker signatures for any disease through the implementation on R of different statistical methods such as Gradient Boosting, Support Vector Machines, GLM with elastic-net regularization and resampling techniques like Cross-Validation and Nested Cross-Validation
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