Program Overview

Dottorato in TECNOLOGIE BIOMEDICHE INNOVATIVE IN MEDICINA CLINICA

Presentazione

The Ph.D. program in Innovative Biomedical Technologies in Clinical Medicine aims to provide training in translational research. To this end, particular attention is paid not only to training in the use of advanced biotechnologies but also to the ability to manage and analyze large amounts of data (Big Data Analysis) with innovative bioinformatics and network analysis tools, taking into account the complexity of many human diseases (Network Medicine).

The specific objectives of the Ph.D. program are:

• to respond to the continuous and increasing demand for new models of training in translational medicine;
• to achieve better interaction between the contents of biological, clinical, and informatics sciences;
• to create a new professional figure in the biomedical and technological field, expert in translational medicine, who is able to combine competence in the use of advanced technologies with the clinical skills necessary for identifying both study topics and application paths of new knowledge.

The specific training objectives of the Ph.D. program are:

• learning elements of epidemiology to interpret genetic susceptibility to multifactorial diseases (complex traits);
• learning methodologies for studying the genome and its variability;
• learning bioinformatics methodologies for evaluating the results of genetic research;
• learning methods for studying epigenetic modifications of chromatin and techniques for analyzing DNA methylation;
• learning methods for studying gene expression (mRNA, miRNA, and lncRNA);
• learning techniques for cell culture, isolation, characterization, and culture of progenitor, stem, and iPS cells;
• learning techniques for studying innate and adaptive immunity cells in vitro and ex vivo;
• learning methods for generating genetically modified animals;
• learning techniques of proteomics and metabolomics for identifying predictive disease markers;
• learning principles and applications of network medicine;
• learning and applying innovative imaging techniques;
• learning principles of pharmacology with particular reference to pharmacogenetics and pharmacogenomics;
• learning principles and applications of Big Data Science;
• learning the basics of clinical experimentation;
• learning the basics of in silico clinical experimentation;
• learning principles of animal experimentation, including elements of biomedical ethics;
• evaluating the entrepreneurial and industrial aspects of advanced biotechnologies;
• designing and implementing predictive algorithms (machine learning) to analyze and extract useful knowledge from the variety and quantity of available medical data.

Research Areas

The Ph.D. program focuses on various research areas, including:

• translational medicine
• innovative biomedical technologies
• network medicine
• big data analysis
• bioinformatics
• genomics
• epigenetics
• gene expression
• cell culture and characterization
• immunology
• animal models
• pharmacology
• clinical experimentation
• in silico clinical experimentation
• biomedical ethics

Program Structure

The program is structured to provide a comprehensive education in innovative biomedical technologies and their applications in clinical medicine. The curriculum includes a range of courses, seminars, and research activities designed to equip students with the knowledge and skills necessary to pursue a career in translational medicine.

Admission Criteria

The admission criteria for the Ph.D. program include:

• a strong academic background in a relevant field (e.g., biology, medicine, bioengineering);
• a master's degree or equivalent;
• a demonstrated interest in translational medicine and innovative biomedical technologies;
• a good understanding of English (the program is taught in English).

Tuition Fees

The tuition fees for the Ph.D. program are not specified in the provided context. However, it is mentioned that the program is funded by the Piano nazionale di ripresa e resilienza (National Recovery and Resilience Plan).

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