Data and laboratory management

A.Y. 2019/2020
Overall hours
MED/01 MED/05 MED/43 MED/46
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.
Course syllabus and organization

Single session

Lesson period
Third trimester
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.
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.
Teaching Resources
Slides produced during the course.
Material provided or suggested by the teachers.
Assessment methods and Criteria
The final examination of the integrated course of "Data and Laboratory Management" will consist in a written test of 30 questions with multipole choices that will represent all the 4 different synergic modules of the course. Within 5 possible choices at every given question, the correct answer(s) can be one or more than one. The student won't know what questions will have either one correct answer or more correct ones. In this way, only a deep knowledge of all the program explained at lessons will allow the student to correctly answer to all the questions whose score is 1 (in case of a single correct choice) or 1,5 (in case of correct multiple choices). The score will be of 0,5 for partial correct answers to those questions with multiple exact choices. In case of any wrong answer, the score will be 0 regardless of the single or multiple exact choices of that question. This methodology will allow to every professor of the course to deeply test in the same way the level of knowledge of the students in each written test.
The final score is 30/30 and the "laude" will be granted only to those students that will get a score higher than 30 in the written test.
There are no scheduled preparatory, intermediate or "in itinere" examination tests and the we will schedule e minimum of 6 written examination tests for every academic year without any unofficial examination tests.
The student cannot carry any paper or electronic support material during the written examination test that will last 60 minutes.
The final results of the written examination test will be delivered electronically via the official online platform of UNIMI and the students will have the option to either accept or reject the final score of the test.
Clinical pathology
MED/05 - CLINICAL PATHOLOGY - University credits: 2
Lessons: 14 hours
Forensic medicine
MED/43 - FORENSIC MEDICINE - University credits: 2
Lessons: 14 hours
Laboratory medicine
Lessons: 7 hours
Professor: Mavilio Domenico
Medical statistics
MED/01 - MEDICAL STATISTICS - University credits: 1
Lessons: 7 hours
Professor: Biganzoli Elia
On Appointment
Istituto Clinico Humanitas, Via A. ;anzoni 113, Rozzano, Milano