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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Serie: ISTE Invoiced
- Sprache: Englisch
Biobanks ensuring the governance and management of biological resources have become essential entities. The development of biotechnologies, the increased prevalence of biological drugs and the identification of biomarkers associated with molecular classifications of tissue lesions make it essential to have organized access to human biological samples, which have become precious and rare. The digital era and the production of massive data that comes with it have rendered biobanks the guarantors of the reproducibility of experiments and of the overall quality of medical research.
Biobanks in Healthcare explores the upheaval linked to the massive deployment of digital health and precision medicine. The future of health biology lies in the deployment of biobanks in fields that have yet to be explored, putting them at the forefront of this extraordinary 21st-century research adventure.
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Seitenzahl: 259
Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Title Page
Copyright Page
Foreword
Acknowledgments
Introduction
1 Biobanks, a Source of Human Samples and Health Data
1.1. From the collection of biological samples to the concept of a biobank
1.2. Mapping of biobanks
1.3. Process management in biobanks
2 Biobanks in the Digital Age and Precision Medicine
2.1. Medical imaging biobanks
2.2. Radiomics data powered by digital technology
2.3. The infallible traceability of biobank data
3 The Biobanking Lexicon
3.1. Accreditation
3.2. Anonymization (or de-identification)
3.3. ANSM, the French National Agency for the Safety of Medicines and Health Products
3.4. Artificial intelligence
3.5. BBMRI, the coordinating center for European biobanks
3.6. BBMRI-ERIC, the research infrastructure for biobanking
3.7. BBMRI-ERIC Biobank of Excellence or Expert Center
3.8. Biobank information management system (BIMS)
3.9. Biobank or biological resource center (BRC)
3.10. Biomarker
3.11. Biospecimen
3.12. Buffy coat
3.13. Certification
3.14. Clinical biobank
3.15. Clinical research or clinical trials
3.16. Clinical trial sponsor
3.17. CNIL, the French National Commission for Information Technology and Civil Liberties
3.18. Cohort and megacohort
3.19. Collection of biological samples
3.20. Companion test
3.21. Computed tomography (CT)
3.22. CPP, the French Committee for the Protection of Individuals
3.23. Data protection officer (DPO)
3.24. Diagnostic biomarker
3.25. Digital health or e-health
3.26. Electronic case report form (eCRF)
3.27. ESBB, the European, Middle Eastern and African Society for Biopreservation and Biobanking
3.28. FDA, the US Food and Drug Administration
3.29. Formalin-fixed, paraffin-embedded (FFPE) tissue
3.30. Free and informed consent
3.31. General Data Protection Regulation (GDPR)
3.32. Imaging biobank
3.33. Imaging biomarker
3.34. ISBER, the International Society for Biological and Environmental Repositories
3.35. ISO 20387:2018 Biotechnology – biobanking – general requirements for biobanking
3.36. Laboratory information management system (LIMS)
3.37. Liquid biopsy (in oncology)
3.38. Machine learning and deep learning
3.39. Medical imaging
3.40. Microbiota
3.41. Monitoring biomarker
3.42. MTA or biological material transfer contract
3.43. NF S96-900
3.44. Omics
3.45. Peripheral blood mononuclear cells (PBMCs)
3.46. Personalized or individualized medicine
3.47. Pharmacodynamic/response biomarker
3.48. Population biobanking
3.49. Positron emission tomography (PET)
3.50. Pre-analytical phase
3.51. Precision medicine
3.52. Predictive biomarker
3.53. Prognostic biomarker
3.54. Prospective study/survey
3.55. Quality management system (QMS)
3.56. QR code
3.57. Radiomics
3.58. Region of interest or volume of interest (ROI/VOI)
3.59. Retrospective study/survey
3.60. Standard operating procedures (SOPs)
3.61. Stratified medicine
3.62. The process of fixation and paraffin embedding
3.63. Translational research
3.64. Tumor biobank
Conclusion
Glossary
References
Foreword
Introduction
Chapter 1
Chapter 2
Chapter 3
Conclusion
Index
Other titles from iSTE in Biology and Biomedical Engineering
End User License Agreement
List of Tables
Chapter 1
Table 1.1. Criteria for locating a collection and identifying a biobank in the...
List of Illustrations
Chapter 1
Figure 1.1. Annual number of publications with the term “biobanking” from 2000...
Figure 1.2. Activity indicators of the Côte d’Azur biobank. a) Quantitative da...
Figure 1.3. Population and clinical biobanks. For a color version of this figu...
Figure 1.4. Map of biobanks in Europe. The number of biobank members of the BB...
Figure 1.5. Strengths of large international biobanks. SOPs: standard operatin...
Figure 1.6. The European Prospective on Cancer and Nutrition (EPIC). For a col...
Figure 1.7. Quality management system (QMS) activities. FFPE: formalin-fixed p...
Figure 1.8. The legal framework for biobanks for the conservation of a collect...
Chapter 2
Figure 2.1. Two examples of magnetic resonance imaging (MRI) of the brain in c...
Figure 2.2. An example of a brain MRI with different image segmentations. For ...
Figure 2.3. Brain MRI protocols from the Rotterdam imaging study [IKR 15]
Figure 2.4. Cardiovascular MRI
Figure 2.5. (a) T1-weighted MRI of the thorax and abdomen and (b) musculoskele...
Figure 2.6. Thoraco-abdominal MRIs. (a) T1-weighted image from neck to the kne...
Figure 2.7. Classification of patients with Alzheimer’s disease according to t...
Figure 2.8. Alzheimer’s disease marker profile from normal cognitive state to ...
Figure 2.9. Examples of lung lesions defined according to the LIDC-IDRI study ...
Figure 2.10. Precision medicine is driving the strategic directions of modern ...
Figure 2.11. The sample life cycle, driven by the BIMS
Figure 2.12. Databases connected to the BIMS. CDB: clinical database; HIS: hos...
Figure 2.13. BBMRI-ERIC Biobanks of Excellence
Figure 2.14. FAIR principles for integrating and reusing the large amounts of ...
Chapter 3
Figure 3.1. Conformity assessment
Figure 3.2. Applications of tissue and liquid biopsies in oncology
Figure 3.4. The process of fecal microbiota transplantation
Figure 3.5. The procedure for a material transfer agreement or data transfer a...
Figure 3.3. Formalin-fixed, paraffin-embedded tissue blocks
Guide
Cover Page
Table of Contents
Title Page
Copyright Page
Foreword
Acknowledgments
Introduction
Begin Reading
Glossary
References
Index
Other titles from iSTE in Biology and Biomedical Engineering
WILEY END USER LICENSE AGREEMENT
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e1
Series EditorNicole Arrighi
Biobanks in Healthcare
From the Collection of Biological Samples to Digital Health
Nicole Arrighi
Paul Hofman
First published 2024 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUKwww.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USAwww.wiley.com
© ISTE Ltd 2024The rights of Nicole Arrighi and Paul Hofman to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.
Library of Congress Control Number: 2024943915
British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78630-023-2
Foreword
If we go back as far as possible in the history of humanity, it is possible that the first gesture of the first researcher was to collect objects taken from nature. Gathering, classifying and preserving these objects in order to observe and study them were probably at the origin of the first scientific approach of our ancestor, gifted with consciousness and abstraction, and the irrepressible desire to know the world. More recently, in the 17th-century curiosity cabinets, it was a question of enthralling the visitor, but also of affirming one’s rank and power. European kings understood this well when they created museums and other royal gardens that brought together collections of extraordinary animals and plants taken from the confines of their kingdom. These collections were at the origin of the change in our knowledge of life sciences. Just think of Buffon’s monumental Natural History during the Enlightenment!
Human biological collections were established with the advent of hospitals in the 19th century, which became not only places of charity but also establishments for care and for the transmission of knowledge. In order to describe and try to understand diseases or congenital anomalies, it was necessary to collect, preserve and classify affected organs and fragments of biological tissues. Thus, the famous anatomical collections of Jean-Martin Charcot at the Salpêtrière Hospital, of Marc-Antoine Petit, the first surgeon-major of the Hôtel-Dieu Hospital in Lyon, and of the medical schools of Montpellier and Strasbourg, were created. This period also gave birth to anatomopathology, the study and classification of the macroscopic and microscopic lesions of injured tissues, with Jean-Baptiste Morgagni in Padua, Rudolf Virchow in Berlin and Jean Lobstein in Strasbourg. Significant collections were thus accumulated over decades in accordance to the passions of these physician-researchers; collections that most often ended up in the dark basements of hospitals some time after the disappearance of their creators, closely followed by that of the notebook blackened with cabalistic annotations understandable only by its author.
At the dawn of the 21st century, with the development of high-throughput analysis techniques, access to quality biological samples became a major issue. Indeed, it quickly became apparent that the growing industrialization of research in biology and health required that biological objects be of impeccable quality and provided with reliable annotations for analysis. The first databases resulting from the exploitation of human samples were often marred by errors and generated erroneous scientific information. Another major issue was that of economic value. The development of biotechnologies, the rise of biological drugs and the identification of biomarkers associated with molecular classifications of tissue lesions made it essential to have orderly access to human biological samples, which had become precious and rare.
France was a pioneer at the international level in organizing and defining the missions of biological resource centers, or biobanks, new biology–health infrastructures designed to collect, store and make available human biological samples. It was also the first country to establish a standard for the operation of biobanks, which was recently converted into an ISO standard, and to establish ethical rules for access to biological samples from the human body, which are included in the Public Health Code. The normative progress has been considerable, the scientific production improved and the services rendered to the advancement of medicine indisputable. Functional biobanks today are those that combine quality assurance of biological samples and their annotations, technical and scientific expertise, transparency of governance, innovation, training and integration into the local, national and international research community.
More than 20 years after their creation, the biobanking project is not yet complete [CLÉ 19]. The business model is still unstable due to the lack of a real national strategy to structure and finance a national network of biobanks based on independent peer evaluations. In many cases, stocks are thus increasing indefinitely, in the hope of a hypothetical valorization. Moreover, access to epidemiological, bioclinical and genomic data associated with collections remains difficult, in the absence of harmonization of hospital information systems and a real willingness to share these data. Despite important advances at the European level, the legislative and regulatory framework is slow to adapt to the evolution of biobanks and the constitution of large cohorts that involve the storage of biological samples and associated data for future research.
Biobanks are at a crossroads. Like all essential infrastructures in biology and health, they must adapt to advances in research and technology. In the digital era and with the production of Big Data by practically all laboratories that have access to very high-throughput and low-cost technological platforms, biobanks are becoming the guarantors of the reproducibility of experiments and of the overall quality of research in biology and health. They are expanding their scope of intervention, automating processes and exploring new analysis techniques with precious samples, while preserving them for future generations. They are diversifying their storage capacities; in addition to information on biological objects, epidemiological, clinical, biological, genomic and imaging data are being included in their computer bases. Biobanks, by their very nature, are interface infrastructures, which erase the artificial divide between care and research activities. A striking example is their central role in medical genomics, which relies on the intensive deployment of digital technology to produce information that is simultaneously useful for patient care and for researchers studying disease.
This book reviews the current state of biobanking. It explores new avenues, in particular the change linked to the massive deployment of digital health and precision medicine. The authors show that the future of biology and health requires the deployment of biobanks in fields that have yet to be explored, at the forefront of the extraordinary adventure of 21st-century research.
Bruno CLÉMENT
Director of research at InsermInstitute of Nutrition, Metabolisms and CancerCRB Santé Biological Resource Center of Rennes University Hospital
Acknowledgments
This book is the result of collegial research that contributed to the creation of the Master of Science in Biobanking and Complex Data Management at Côte d’Azur University. The authors would like to thank all the experts from the various European and North American countries who have contributed to and continue to enrich the training program for future biobank managers.
Dr. Bruno Clément has given us the honor of writing the foreword to this book. He is the director of the Inserm U991 unit “Liver, Metabolism and Cancer” at the Pontchaillou Hospital of the Rennes University Hospital. Always extremely involved in action in favor of innovations in biotechnology, he strongly participated in the creation of the national project for biobanks and has played an essential role in the IBISA infrastructures (platforms of resources in biology, health and agronomy open to the scientific community).
Dr. Robert Hewitt, founder of the Biosample Hub and co-founder of the European, Middle Eastern and African Society for Biopreservation and Biobanking (ESBB), played a central role in the construction of the course by sharing his expertise in biobank management and his experience in the industry. We would like to thank him for his presence at the inauguration of the defense juries for the Master of Science in Biobanking and Complex Data Management at Côte d’Azur University.
Dr. Marius Ilié is a pathologist and a professor in the Faculty of Medicine of Nice and a member of the biobank scientific council of the laboratory of clinical and experimental pathology at Pasteur University Hospital in Nice. Through his expertise in sample management, he has contributed to numerous publications in biomedical research. He is a member of IRCAN team 4 (Inserm U1081/UMR CNRS 7284).
Dr. Élodie Long-Mira is a physician of molecular and clinical pathologies. Her research activities at the laboratory of clinical and experimental pathology of the Pasteur University Hospital in Nice are focused on lung cancer and melanoma. She is a lecturer at the Faculty of Medicine in Nice and teaches embryology and histology. She is a member of IRCAN team 4 (Inserm U1081/UMR CNRS 7284) and in charge of the melanoma collection at the Nice biobank.
Dr. Giorgio Stanta is Professor of Pathology at the University of Trieste. His major interest is in the application of molecular analysis to formalin-fixed and paraffin-embedded tissue samples. He has demonstrated the importance of pre-analytical conditions and standardization of genomic and proteomic methods. He is an expert of the BBMRI-ERIC network and coordinates the European group IMPACTS Archive Tissues: Improving Molecular Medicine Research and Clinical Practice1.
Dr. Georges Dagher was the Director of the French Biobank Infrastructure and Director of Research at Inserm (France). In addition to his clinical research activities, he has contributed to the OECD guidelines on good practices for biological resource centers, human biobanks and genetic databases. He participated in the development of the French standard NF S96-900 and its transformation into an international ISO standard for biobanks.
Dr. Kurt Zatloukal is Director of the Austrian Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). He is a pathologist and professor at the Medical University of Graz (Austria) and heads the Christian Doppler Laboratory for biospecimen research and biobanking technologies. As coordinator of the preparatory phase of the BBMRI infrastructure, he is involved in the development of new European standards in the pre-analytical phase of molecular diagnosis of tissue samples.
Taycir Skhiri is project manager of the FHU OncoAge (University Hospital Federation Oncoage, www.oncoage.org) the goal of which is to share research results and develop innovative solutions in the FHU OncoAge. Converting and applying the results of research requires the transmission of knowledge that meets, among other things, the demand for the professionalization of biobanks.
Dr. Kevin Washetine is a quality engineer in the clinical and experimental pathology laboratory of the Pasteur University Hospital in Nice. He coordinates the implementation of quality procedures. His work has enabled the laboratory to obtain and maintain certification according to the NFS 96-900 standard (quality of biological resource centers) from AFNOR and accreditation by COFRAC according to the ISO 15189 standard for pathology and molecular biology activities.
Zeineb Messaoudi is a quality engineer at the clinical and experimental pathology laboratory of the Pasteur University Hospital in Nice. She is implementing the transition from the NFS 96-900 standard to the international standard for biobanks ISO 20387 (quality management system for all biobanking activities).
Dr. Laurent Counillon is Director of the EUR Life University Research School, the infrastructure that, among other things, pilots the IDEX Masters of Science (initiatives of excellence launched by the French government). These interdisciplinary programs, taught at Côte d’Azur University in English, focus on creating programs of excellence with international visibility.
Dr. Sophie Raisin-Tani is a professor at Côte d’Azur University. Her involvement from the beginning of the project has accelerated the sharing of resources and the opening of the project to the international scene, increasing its attractiveness to students and biobank managers invited to participate in the teaching.
We wish to thank all the members of FHU OncoAge who, thanks to their multiple translational research activities, actively contribute to the influence of the Nice University Hospital biobank (BB-0033-00025).
Note
1
www.impactsnetwork.eu
.
IntroductionBiobanks in 2022: Why and How?
Research is based on several foundations: fundamental concepts, cellular and animal models, validation of discoveries obtained in laboratories through a “translational” approach and then, depending on the sector of interest, clinical or applied research or research carried out in silico using databases. Depending on the research topics, it is necessary to achieve a continuum between the discovery of new cellular mechanisms and an application in the living world, whether it is the plant, microbial or animal and human world.
One of the unavoidable links between basic research and its various applications is the use of different biological resources, whether they come from plants, microbes, animals or healthy or sick human beings [ALD 19, VAU 19]. From time immemorial, researchers have needed to analyze these different biological resources to validate their hypotheses or observations made with cellular models. Several purposes have progressively emerged, such as better understanding of developmental biology or of the mechanisms of cell death, growth or transformation. One of the most successful examples of the use of biological resources is the discovery of biomarkers of human diseases, which can be biomarkers for diagnostic, prognostic or predictive purposes in a therapeutic response [BAR 20, HEW 11]. While the these biological resources were initially used in a poorly controlled manner and without any real established rules, several reflection policies have gradually led to the establishment of a controlled and rigorous operation. Thus, the notion of a collection was born, associated with the need to control use and the necessary storage spaces. In recent decades, these different collections have been associated with the creation of biological resource centers (BRCs), still called “biobanks” today, the structuring of which has been progressive, and they have become essential “tools” in the world of research [WAT 19].
Biobanks have evolved in recent years and are now professionalized and complex structures whose operation is subject to national and international regulations. These biobanks can function as secure storage areas for biological collections (called “biorepositories”), making samples available for research projects. They can also be organized as Expert Centers, and thus both offer services to researchers (thanks to the existence of technical platforms) and enable scientific collaboration (thanks to unique knowledge). Biobanks can also develop their own research projects on specific topics, in particular on the control, management and use of biological samples, essentially with the aim of optimizing their operations and their service offer [WAS 18a].
Biobanks and collection policy have evolved over time. A typical example is the evolution of biobanks collecting patient samples. At first, many samples were accumulated and frozen, in particular tumor samples. The question of the quality of these thousands of stored samples then arose. Indeed, the discovery and/or validation of the different markers proved to be totally dependent on the reproducibility of the analyses on perfectly preserved samples. Finally, the need to acquire more and more associated or targeted data modified the functioning of biobanks by requiring the development of multiple and complex databases. Indeed, one of the key points associated with making biological samples available for research projects is now the need to associate very precise and relevant data with them. The world of biobanking has therefore evolved progressively over the last few decades, with this field becoming a medical specialty in its own right. Thus, schematically, the activity of biobanks has passed through several stages, from the “biobank 1.0” (massive collection activity often without any preconceived ideas and based on “quantitative” data) to the “biobank 2.0” (where the quality of samples is considered crucial along with the implementation of the control of the parameters of the pre-analytical phase), and finally the “biobank 3.0” (integrating several imperatives, in particular the controlled management of clinicobiological data, the anticipation of requests and the control of the business model) [DOU 17, ELL 15, LIN 20, SIM 14]. Thus, the creation and construction of a biobank-type structure must nowadays meet strict requirements, in particular associated with a collection strategy and planning of the use of stored samples [BAI 16, HOF 13].
The diversity of expertise required to generate the data associated with the samples, their integration and their analysis necessitate a rethinking of the organization and structuring of biobanks in order to address the services of specialists in different fields, notably medical, biological, imaging, statistics, bioinformatics and mathematics. This change must concern, at the national or international level, biobanks involved in the collection, integration and analysis of complex data. The concept of next generation biobanks (NGBs) is gradually emerging. An NGB must be able to combine huge databases hosting phenotypic, behavioral, familial, imaging, omics, radiomics and biological data from different centers. Operating an NGB requires overcoming several challenges, the first of which is that of computing infrastructures capable of processing tetrabits, pentabits and exabits. In addition, a suite of appropriate analysis methods and algorithms must be developed. Moreover, these NGBs are now accompanied by a paradigm shift from the analysis of data from a large number of patients to the analysis of a large volume of data from a single subject (“Big Data” vs. “Fat Data”). A crucial aspect for biobanks is their sustainability, taking into account the fact that the business model of these structures is often fragile [RAO 19, VAU 11]. Indeed, the operation of a biobank today requires a dedicated and qualified staff, a secure and expensive infrastructure and equipment that must be renewed regularly in order to maintain the quality of the collections.
There are more and more biobanks throughout the world and the number of collections that can be made available to researchers is increasing, which may lead to a gradual decrease in demand for certain biobanks due to competition. In this context, in order to be competitive, a biobank must make organizational and strategic choices. It is difficult to maintain a high level of expertise in several fields of activity, and focusing on a limited number of pathologies certainly makes it possible to concentrate on the completeness of the collections and to associate complete clinical and biological data, the latter becoming increasingly complex.
An essential point is to obtain the signed consent of patients to use their sample for research purposes. This key point must be associated with an internal process specific to each biobank, which must be perfectly mastered and conducted in consultation with the clinical services. The external visibility of a biobank and its recognition are increased when the partners of a biobank have access to different forms of expertise (e.g. histological diagnosis performed by senior pathologists in the field of pathology concerned; expertise in molecular biology and accessible genomic databases). Focusing on one or a few pathologies also makes it possible to associate, for the same patients, diversified collections of tissues (fixed and frozen) and biofluids (plasma, sera, buffy coat, whole blood, urine, other fluids, etc.). Clinical data and in particular the follow-up of patients according to the different successive treatments or the collection of events (progression, metastasis, death) can be more easily integrated into the biological databases [WAT 17]. In this context, it is often easier to join a national or international network of experts in the same field.
Certification or accreditation of the biobank according to national or international standards is also essential to the robustness of its operation and the quality of the service provided. A competitive biobank must also develop innovative projects, particularly in relation to the pharmaceutical and biotechnology industries. Different projects can allow for the transfer of the results of the innovation thus acquired to clinical practice, after a validation phase carried out with biological samples. Thus, the visibility of a biobank vis-à-vis different partners and/or applicants for biological samples can benefit from the implementation of performance indicators that must be adapted to the structure concerned and its ambitions [HOF 13].
Several challenges are emerging in the near future for biobanks, and these structures must meet a certain number of common objectives. For example, data from different databases or documents (pathological anatomy, molecular biology, imaging, clinical and therapeutic data) have to be gathered (or used) in a single accessible source. It will also be necessary to integrate, store and process complex and often very heterogeneous data volumes. One of the challenges is the sharing and access to information, which must be secure and based on perfectly de-identified data. This access could be envisaged for external partners wishing to know the available samples and the associated complex data. In view of these rapid developments and a change in the activities related to the biobanking profession, it is therefore crucial to continue or develop appropriate university training and to recruit people into the biobanks who have benefited from practical and theoretical training in this field. The control (capture and exploitation) of complex and Big Data associated with biological samples collected from cancer patients has become a major issue in oncology. This control requires several combined actions. The first step is to control the quality of the data collected. In the world of Big Data, there is a major risk of generating secondary data biased by incomplete or false primary data. No matter how sophisticated the tools deployed, especially those based on deep learning, machine learning and artificial intelligence approaches, it is impossible to turn “lead into gold”, i.e., to generate quality data from insufficient or erroneous initial data. The pathologist’s role is essential here and only their expertise can verify the quality of the diagnosis and the analyses performed on the tissue sections. The integration of associated molecular biology data is also a key step. These data are of varying complexity and may include whole genome sequencing data for a tumor, and also transcriptomic, proteomic and metabolomic data. Once again, the quality of the data (also related to the quality of the samples and therefore of the pre-analytical steps) is the essential point to control.
Biobanks are subject to strict legislation and the use of samples for research projects can only be undertaken in compliance with the law. Thus, public–public or public–private partnerships can only be established through contracts and signed procedures managing material transfer agreements (MTAs) [CLÉ 14, HOF 14, SIM 20]. These contracts must specify the purpose of the research carried out with the samples and the identity of the end-user. Indeed, some private companies serve as platforms for the recruitment of biological samples, especially from academic laboratories, and supply users without knowing the purpose of their research.
The biobank world is not immune to the arrival of artificial intelligence (AI) [LIN 20, MAR 20, NAR 20]. AI is in fact a very general term to designate “the set of theories and techniques used to create machines capable of simulating intelligence”. Often classified as one of the cognitive sciences, it uses computational neurobiology, mathematical logic and computer science. Since its birth 70 years ago with a few simple abstractions of how a neuron works in the human brain, AI has become an indispensable tool for computer vision applications. In particular, artificial neural networks
