Parcours Biohealth engineering 1re et 2e année

This course is aimed to provide students with an in-depth understanding of the ways in which membranes and cells are utilized in biotechnology systems. The teachers are experts in their respective fields, and will discuss the biotechnology of membrane transport proteins in cellular functions, and the modelling and simulation of larger-scale cell systems. During the tutorial sessions students will be guided through practical implementation of developing and analyzing models of cell systems using the R software package.

Exemples of topics:

• Role of membrane transport proteins in cellular functions
• Biotechnology tools to measure cell membrane transport functions (e.g. patchclamp electrophysiology)
• Why is the cardiac action potential longer than the nerve action potential ?
• Membrane transport proteins linked to cell functions and to disease
• Introduction to Systems Biology and biochemical networks
• Metabolic network modelling at the genome scale
• Integration of omics data into genome-scale metabolic network models
• Kinetic modelling of biochemical networks
• Reconstruction of gene expression networks
• Simulation of genome-scale metabolic networks
• Simulation of genome-scale metabolic networks and integration of omics data
• Simulation of the circadian clock rhythm
• Projects

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This course is aimed to introduce students to planning and communication strategies in science. The content includes critical analysis of scientific articles, planning of scientific projects, and strategies for oral communication of scientific results. The students will prepare and present 2 oral presentations, one of 10 minutes and one of 180 seconds. The presentations will be based on the critical analysis of a scientific project and articles. The course planning includes sufficient periods of private work to prepare these presentations. The students will participate in the grading of these presentations, with the aim to reinforce active participation in processes of analyzing and communicating scientific results. Assessment of the course will be made during tutorial classes.

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The teaching unit deals with basic laboratory gestures for biotechnology experiments such as in microbiology, biochemistry, biotechnology engineering experiments. It will provide students with a solid practical reference to ensure success at each stage in their practical education (including for the teaching unit biotechnology engineering) and insertion in the biotech industry.

With appropriate safety practices, student will learn:

• About principles and applications of widely used biotechnology methods in microbiology, biochemistry and biotechnology engineering
• About basic requirements of a laboratory through practice problems (high-precision liquid and solid handling, buffer preparations, absorbance measurements, enzymatic measurements, standard range for quantitation).
• How to operate basic equipment (analytical balance, pH meter, spectrophotometers with cuvettes or microplates).

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This teaching unit aims at teaching organ physiology. Particularly, students will become familiar with cardiovascular system, metabolism, neuro hormonal regulation, respiratory physiology in order to understand organ function alone and in interactions with the others. This is the basis of pathophysiology understanding as well as pharmacology application. Tutorial class aims at applying theorical knowledges through a personal work with tutoring. Practical session aims at understanding and illustrating cardiac electrophysiology and arterial blood pressure variation.

Exemples of topics:

• Cardiovascular physiology (physiology and application)
• Metabolism
• Neuro-hormonal regulation (ANS, RAAS)
• Respiratory physiology (basis and control)
• Physiopathology application (tutorials / 4 themes)
• ECG / arterial blood pressure measurement (practicals)

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Through this unit, the student will be introduced to pharmaceutical development, that describes the different steps needed to go from an active molecule to an effective dosage form. The specificities of the main dosage forms will be presented and different operations needed to reach these specificities will be studied.

The aim is to make student aware of the necessity of pharmaceutical development to turn an active molecule into an efficient dosage form. This unit aims to give the student the knowledge and tools to understand the critical steps encountered during the pharmaceutical development.

This unit will be organized around 4 lecture sessions aiming at presenting pharmaceutical development, pharmaceutical dosage forms, strategies that can be involved in improving drug properties to meet the specificities of the different dosage forms and the pharmaceutical unit operation needed to prepare the different dosage forms. The students will attend 2 tutorial classes where we will study practical cases based on actual pharmaceutical formulations. These tutorial classes will illustrate the lecture sessions and help student understand practical aspects involved in pharmaceutical developments. A small practical project will conclude the unit. It will be divided into 4 sessions: 1 tutorial class to introduce the practical sessions, 2 practical sessions meant to discover a few unit operations and 1 final tutorial class to conclude the small project.

Exemples of topics:

• Introduction to Pharmaceutical Development
• Pharmaceutical dosage forms : detailed in sub-chapters (oral, injectable, …) with emphasis on specificity
• Improving drug properties to meet specificities of dosing forms
• Pharmaceutical unit operations related to the specificities of dosing forms
• Case study : oral forms
• Case study : injectable forms
• Discussion about practical sessions, briefing and debriefing
• Solid pharmaceutical forms :
• Liquid pharmaceutical forms : improving the stability of suspensions

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This course is devoted to a refresher course in statistics and computer science.

The objective of the first part is to train students to master the statistical methods used in the life and health sciences.

• Master the description of collected data
• Master the choice of a decision support tool (statistical test) in adequacy with the experimental context
• Master the concepts of modeling, regression, estimation of regression parameters, model validation and prediction
• Master the correct interpretation of the results obtained and know how to communicate them.

At the end of this part, the students will be able to carry out a work requiring the statistical tool or to carry out a critical study of an article, a survey or experiment using usual statistical methods.

The second part of the course will provide students with a basic knowledge of programming in order to make them autonomous and to provide a skill that is sought after and appreciated in the different fields of biotechnology and health.

Statistic (12h)

• Anova
• Chi-squared test
• Correlation
• Linear regression
• Logistic regression

Computer science (12h) :

Introduction to computer science and programming using Python :

• A notion of computation
• Python programming language
• Testing and debugging
• Data structure

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This course is aimed to provide students with an in-depth understanding of the ways in which DNA is utilized in biotechnology. The teachers are experts in their respective fields, and will discuss the biotechnology of DNA from its role in coding different proteins, to the technology utilized to analyse DNA sequences, through to the use of bioinformatics for genomics. During the tutorial session students will be guided through practical implementation of bioinformatics software for analysis of DNA and genetic data.

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The main challenge in the use of artificial intelligence in health care is to have access to structured and quality data while respecting ethical issues and personal data protection laws. Main parts of the course: (i) Principles of data management (ii) Challenges related to data management in healthcare (iii) Ethical considerations (iv) Practical sessions (Jupyter notebooks).

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Using a scientific programming language (e.g., Python) as a tool for modelling and numerical analysis.

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This module consists of writing a report on an innovation in the field of health, by teams of two to three students. The students will have to collect information using several sources, including at least two interviews with professionals (from research laboratories, industries, hospitals, etc.). The students will have to take into account the scientific, technical and biomedical aspects of the chosen innovation but also its socio-economic aspects. This exercise will allow students to get used to the rules for writing a scientific document.

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To lay the groundwork for the design of drugs and new biologically active substances by exploiting the knowledge related to the Chemistry-Biology interface. The program of this teaching unit will allow the student to discover the key –elements of research in the field of the design of new molecules of drug candidate.

The teaching unit (on line and face to face learning) is open to students from Master BioHealh Engeneering (BHE), Master Sciences et Ingénierie du Médicament (SIM), Double Cursus Santé.

Exemples of topics:

• Introduction to Medicinal Chemistry and Drug Design
• Plants as source of drugs
• Physicochemical profile of the ligand
• Ligands and their chemical structure: Intermolecular interactions
• Direct drug design by molecular modeling
• Main principles of the metabolism of drugs
• Case studies : Platinum-derived anti-cancer drugs and PARP inhibitors
• Pharmaceutical development and biopharmaceutical aspects of drugs
• Initiation to molecular modeling

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Participants are supervised by Master 2 students and teachers from IAE, pharmacy faculty and INP-Phelma. They benefited from support on the different phases of the creative process and participated to the challenge around collective intelligence, “thinking differently” and risk assessment. The goal is to experiment, make mistakes and learn in order to develop its capacity for innovation. This innovative form of pedagogy which emphasizes inter-disciplinar skills and fields allows students to transpose training into practice by working on a concrete case and to acquire knowledge and methods useful for their professional future.

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Students will perform an intership in order to discover the world of the research and to practice research. They will anticipate their application in laboratories, start-ups or industries. Then, they will write a report and defend their intership behind a jury composed of several experts.

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UE très complète et intégrée de gestion d’un projet biotech menée en équipe de 4 à 5 étudiants. A partir de thématiques proposées, les étudiants travaillent à la conception du projet et au design des expériences grâce à un accompagnement enseignant. Ils passent ensuite à la réalisation pratique de la preuve de concept (4 semaines de TP en laboratoire), et réfléchissent à la stratégie de commercialisation du produit fini (étude de marché, étude de la concurrence, positionnement, forces et faibles du projet, détermination de la cible et du prix de vente…). Cette UE de 12 ECTS est une véritable préparation au stage grâce à la mise en situation professionnelle.

Exemples de techniques disponibles en salle de TP : cytométrie de flux, production et purification de protéines, PCR, culture cellulaire, microscopes à fluorescence, ...

This teaching unit is a team work on a biotechnological project. Students will built a scientific project from the general strategy to the specific description of experimental protocols. A part of the work also concerns a brainstorming to determine the best sales strategy: marketing & economic model approaches. Thus, the general goal of this teaching is to learn how to manage a project (design, experimental skills, planification, analysis and communication)

Exemples of methods available in the facilities: flow cytometry, production and purification of proteins, PCR, cell culture, fluorescence microscopy, ...

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The objective of this course is to answer an open scientific or technological question with the tools studied during the track M1

A researcher or engineer from a laboratory or public/private company will supply an open scientific or technological question in the domain of experimental data. Most often, the question does not yet have an answer, and the students will work on this open problem in group during two weeks of intensive labor.

The class will have a final leader board evaluating the different solutions, part of the grade will be based on this leader board to motivate the groups through its competitive character.

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OBJECTIVES

Acquire the fundamentals of image processing methods

OUTLINE

• Digital images and representations
• Image improvement
• Image filtering and restoration
• Contour extraction
• Region segmentation
• Color images
• Machine learning example

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Introduction to proteomic principles and applications. Principles of mass spectrometry. Protein analysis by mass spectrometry. Overview of separation methods and strategy. Principles of bioinformatics and identification methods in proteomics. Quantification methods in proteomics. Study of post-translational modifications. Data analysis, ontology. Interactomics. Methods for research and validation of biomarkers. Methods for characterization of biopharmaceutical products.

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Fields covered by this course: gene therapy, cell therapy and cellular engineering (stem cells, organoids, ...), tissue engineering (3D bioprinting, biomaterials, ...).

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Animal experimentation rules. Basic notions on animal models (choice of model and experiment establishment). Genetics and transgenesis. Comparative anatomy and physiology in rodents. Live imaging with visit of a platform. Animal models in pharmacology. Alternative methods (cell culture). Role of toxicology and animal experimentation in the evaluation of drug safety. Comparative antomy and physiology in pigs. Practical course - rat model or pig model.

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Biomimetic nanotechnology in health. Applying nanotechnology to health and diseases. Biophysical and spectroscopic techniques in health. Electrochemical techniques and nanostructured biosensors. Microarrays.

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Descriptif :

- effets sanitaires des principaux toxiques sur la santé à travers des illustrations des grands cadres nosologiques (pathologies induites sur les organes « porte d’entrée » tels que la peau et le poumon et effets systémiques)

- effets des familles de toxiques (amiante, nanoparticules, champs électromagnétiques, pesticides, polluants persistants minéraux ou organiques).

Intervenants : enseignants-chercheurs de l’Université Grenoble Alpes, de l’INSERM et du CEA, experts des agences de veille sanitaire (ANSES, InVS), praticiens hospitaliers et d’entreprise (MSA)

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This course aims to provide examples about applications of AI in health research. Several methods will be developed including unsupervised clustering, causal interference, text mining and to have a critical reading of IA methods applied in health. Each teacher will share his/her experience on his/her research field and you will be able to identify the finality of the different methods in a health project.

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Fields covered by this course: methods of AI applicated to analysis of Omics data (genomics, metabolomics, proteomics, transcriptomics, metagenomics for pathogens) / Methods for modelisation of biological networks : dynamical modeling of biological processes / Introduction to dynamical systems / Applications for precision medicine.

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Part 1 - Courses given by teachers of Grenoble School of Management (GEM): project management, market analysis, strategy, finance. Part 2 - Real project on biologics submitted by an academic lab, a start-up or a biotech company. This project is realized by teams of 4-6 students (french speaking and international non-french speaking students coming from partners universities).

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Part 1 - Courses given by teachers of Grenoble School of Management (GEM): project management, market analysis, strategy, finance. Part 2 - Real project on cell therapy, gene therapy or tissue engineering submitted by an academic lab, a start-up or a company. This project is realized by teams of 4-6 students (french speaking and international non-french speaking students coming from partners universities).

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This module is co-organized by our University and by Grenoble School of Management (Grenoble Ecole de Management). It combines:

- tutorials in project management, market analysis, marketing and finance (30 hours)

- concrete missions submitted by start-ups, bigger companies or laboratories. Groups of 4 to 6 students have to fulfill these real tasks within the 4 months of MSc teachings.

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This teaching unit deals with the different aspects of current and future alternatives to fight infectious diseases caused by bacteria, viruses, fungi, or parasites. The program includes the consumption of anti-infectives in humans and animals, resistance mechanisms to anti-infectives, the development of new anti-infectives, phage therapy, vaccinology, immunotherapy, the influence of antibiotics on gut microbiota, and the management of healthcare associated infections and epidemics. The goal of this teaching unit is to provide an extended information on the prophylaxis and treatment of infectious diseases. These notions can be useful in the medical, pharmaceutical, cosmetic, food-processing, and scientific fields.

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The main challenge in the use of artificial intelligence in health care is to have access to structured and quality data while respecting ethical issues and personal data protection laws. Main parts of the course: (i) Principles of data management (ii) Challenges related to data management in healthcare (iii) Ethical considerations (iv) Practical sessions (Jupyter notebooks).

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UE dédiée aux stratégies de repositionnement des traitements pharmacologiques. Explorations des différentes approches permettant d’identifier et d’exploiter de nouvelles propriétés pharmacologiques de molécules déjà développées et sur le marché. 50% des enseignements sous forme de travaux pratiques.

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Health is one of the most impacted areas by the use of AI. Significant advances in the field of research, treatment and care have been announced, along with fears about the use that can be made of this technology. The objective of this course will be to address the fundamental principles for an ethical use of AI in medicine by seeing concrete cases of use, whether in medical search algorithms, the processing of patient personal data, medical robots or the governance of AI-based technologies in health care.

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Genetics of male infertility. Genetics of female infertility. Importance of environmental factors in male and female infertility. Disorders of sex development (DSD), genetic causes and consequences on fertility. Endocrine causes of male and female infertility. Epigenetics and procreation.

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This teaching unit aims to introduce students to Internet Of things(IoT) in the field of healthcare,and make them aware of the opportunities and issues related to data generated by these IoT. Detailed program : IoT for healthcare: definition and overview / Artificial intelligence to exploit data generated by IoT for healthcare / Concerns related to data generated by IoT for healthcare / Regulation of the use of health data for research / Research on the development of new IoT: overview and perspectives / Tutorial: presentation of IoT currently marketed.

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In this course, you will discover the field of artificial intelligence applied to health trough online conferences. You will learn the definition and the main concepts developed in AI. The technological and ethical aspects will be illustrated by watching some experts from movies and through discussions.

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The purpose of the course unit is to familiarize yourself with machine learning (ML) and deep learning (DL) algorithms. We will cover the basic principles behind ML and DL algorithms and apply them to textbook datasets as well as to medical ones. The course takes a pragmatic, user-oriented, approach rather than a more theoretical one (aimed at ML&DL researchers). The course unit comprises a series of hands-on tutorials. Knowledge of the Python programming language is a prerequisite for this course (for the hands-on part).

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Courses given by teachers of Grenoble School of Management (GEM): project management, market analysis, strategy, finance.

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Analysing and synthesizing scientific concepts. Reporting the results of my science (classes, tutorials, oral and written exercises)

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The theme of the course focuses on the understanding of biological and artificial neural networks from a theoretical perspective (links between neurons and psyche, advantage of a distributed parallel system compared to a Turing-Von Neumann machine) but also from a methodological perspective (concrete implementation of artificial neural networks). Part 1: the origins of cognitive psychology. Part 2: synaptic learning algorithms. Part 3: similarity between biological and artificial neural networks. Part 4: Similarity between biological and artificial neural networks. Towards conscious artificial networks?

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Biomarkers play a key role in 70% of medical decisions by enabling screening, diagnosis, choice of the relevant treatment in all human diseases. Content: (i) exemples of new biomarkers in the field of oncology, infectious and inflammatory diseases, ... (ii) exemples of innovative bioanalytical tools and their biomedical applications (protein biochips, point of care devices, biosensors, digital olfaction, ...).

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