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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