Data and laboratory management
A.Y. 2020/2021
Learning objectives
The course is aimed to provide an advanced knowledge of the methodological, statistical and forensic approaches used in the management and analyses of data developed both in clinical and research medicine.
Expected learning outcomes
The students will learn how to generate, analyze ad handle data to be used either for diagnosis or to be published in peer reviewed scientific journal and shared with scientific community worldwide.
Lesson period: Third trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Third trimester
All classes planned during the third trimester of the first year of the Master Degree Medical Biotechnology and Molecular Medicine, will be given as frontal teaching and distance synchronous learning. In case of a new suspension of frontal lectures, all students will be asked to move to distance synchronous learning.
Each hour of lesson will be divided into 45' of formal teaching followed by 15' of discussion/interaction/question time. All lessons will be recorded and made available for students on the indicated platforms (i.e. Ariel, TEAMS, etc).
Unless otherwise specified, exams will be organized in classroom but if the student is unable to reach the building for COVID-related issues, other forms will be considered (this apply for exams scheduled until the 31st July - 2021).
Each hour of lesson will be divided into 45' of formal teaching followed by 15' of discussion/interaction/question time. All lessons will be recorded and made available for students on the indicated platforms (i.e. Ariel, TEAMS, etc).
Unless otherwise specified, exams will be organized in classroom but if the student is unable to reach the building for COVID-related issues, other forms will be considered (this apply for exams scheduled until the 31st July - 2021).
Course syllabus
Medical statistics:
Regulation of the European Parliament and of the Council on the protection of natural persons with regard to the processing of
personal data, right of access and rectification.
Conditions for consents, transparent information, responsibilities (technical and organizational measures), management of personal
data, tramsfer of personal data to third countries, liabilities and penalties.
- 7 -
European Union framework about medical producys for human use.
Good laboratory practices.
Clinical trial regulations.
Ethical issues in data management.
Statistics in data managements.
Scientific fraud.
Laboratory medicine:
Concept of translational medicine and implementation of research programs from "bed to the bench" side and vice versa to investigate
on pathogenesis of human diseases and the development of alternative or novel therapeutic approaches.
Approach and methodology to be used in immunological diseases and tumors.
Technology, animal models, data validation and analysis.
Statistics, publication of data and ethical limitation.
Clinical pathology:
Variability in laboratory measurements and analysis
Understanding and Monitoring Clinical Laboratory services
Diagnosis of bone infections
Diagnosis of allergic diseases
Diagnosis of autoimmune diseases
Cardiac pathologies markers
Diagnosis of coagulation diseases.
Forensic medicine:
Introduction to Forensic Sciences focusing on Forensic Genetics
The interaction between the criminal trial process and forensic science Principles of crime scene investigation
Recovery, transference, chain of custody of evidence
Principles of the serological analysis (traces identification)
Molecular basis of genetic variation in humans
DNA analysis of trace evidence: interpretation and pitfalls, statistics
DNA analysis in paternity testing
Other forensic DNA analysis applications
DNA databases.
Regulation of the European Parliament and of the Council on the protection of natural persons with regard to the processing of
personal data, right of access and rectification.
Conditions for consents, transparent information, responsibilities (technical and organizational measures), management of personal
data, tramsfer of personal data to third countries, liabilities and penalties.
- 7 -
European Union framework about medical producys for human use.
Good laboratory practices.
Clinical trial regulations.
Ethical issues in data management.
Statistics in data managements.
Scientific fraud.
Laboratory medicine:
Concept of translational medicine and implementation of research programs from "bed to the bench" side and vice versa to investigate
on pathogenesis of human diseases and the development of alternative or novel therapeutic approaches.
Approach and methodology to be used in immunological diseases and tumors.
Technology, animal models, data validation and analysis.
Statistics, publication of data and ethical limitation.
Clinical pathology:
Variability in laboratory measurements and analysis
Understanding and Monitoring Clinical Laboratory services
Diagnosis of bone infections
Diagnosis of allergic diseases
Diagnosis of autoimmune diseases
Cardiac pathologies markers
Diagnosis of coagulation diseases.
Forensic medicine:
Introduction to Forensic Sciences focusing on Forensic Genetics
The interaction between the criminal trial process and forensic science Principles of crime scene investigation
Recovery, transference, chain of custody of evidence
Principles of the serological analysis (traces identification)
Molecular basis of genetic variation in humans
DNA analysis of trace evidence: interpretation and pitfalls, statistics
DNA analysis in paternity testing
Other forensic DNA analysis applications
DNA databases.
Prerequisites for admission
Students must carry a bachelor degree in Biomedical Technologies allowing them to have a basic knowledge in general pathology, immunology and statistics.
Teaching methods
The integrated course of "Data and Laboratory Management" will have frontal lessons without laboratories. In each one of the 4 integrated modules of the course, the frontal lessons will be highly interactive for the students that will have the opportunity to download before all the presentations and associated material from the Ariel platform of UNIMI, within a special session referred to this integrated course. Doing so, the lesson will have a high level of synergy so the students can actively participate to the lessons. In particular, the student will have an active role in developing with the professors of each models of the integrated course all those examples of data manipulation and analysis in the context of human models of diseases and associated therapies.
Attending the lessons is mandatory.
Attending the lessons is mandatory.
Teaching Resources
Slides produced during the course.
Material provided or suggested by the teachers.
Material provided or suggested by the teachers.
Assessment methods and Criteria
Students can register to give the final exam only after they will be approved for all the courses comprise in the COMMON LEARNING ACTIVITY track of the Medical Biotechnology and Molecular Medicine Master Degree.
The exam is written with multiple choice questions and open-ended questions designed to assess the knowledge and understanding of students.
The exam is written with multiple choice questions and open-ended questions designed to assess the knowledge and understanding of students.
Modules or teaching units
Clinical pathology
MED/05 - CLINICAL PATHOLOGY - University credits: 2
Lessons: 14 hours
Professor:
Galliera Emanuela Rita
Forensic medicine
MED/43 - FORENSIC MEDICINE - University credits: 2
Lessons: 14 hours
Professor:
Piccinini Andrea Arnaldo Maria
Laboratory medicine
MED/46 - BIOTECHNOLOGY AND METHODS IN LABORATORY MEDICINE - University credits: 1
Lessons: 7 hours
Professor:
Mavilio Domenico
Medical statistics
MED/01 - MEDICAL STATISTICS - University credits: 1
Lessons: 7 hours
Professor:
Alicandro Gianfranco
Professor(s)
Reception:
On Appointment
Istituto Clinico Humanitas, Via A. ;anzoni 113, Rozzano, Milano