Personalized Medicine and Data
Technologies, Welfare System, and EthicalIssues

PersMed Lab
Thomas LEFEVRELEFEVRE

Sorbonne Paris Nord University, IRIS
Invited by the University of TokyoJapan Seminar
Seminar Series
24 - 27 October 2023
Co-organised with the University of Tokyo,
RIKEN and Keio University

Programme
Health big data in France: about ten years of technical,organizational, and political developments
24 October 2023 | from 14:00 (Tokyo time)
At RIKEN: 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan
In EnglishAbstract
In 2015, the French Ministry of Health and Social Affairs ordered an inventory
and reflection on big data in health. At the same time, the French Prime Ministerordered a reflection and the establishment of an ambitious action plan relating togenomics for research and healthcare for 2025, aiming at building several platforms
dedicated to genomic sequencing and high-dimensionality data analysis.
The first group, which I led and was constituted of public and private stakeholders,relied on a broad consultation within public and private institutions, researchand industry, and the civil community. Our group’s report and recommendations
concerned 4 aspects: the technical, economic, legal and ethical, and social
conditions of the development of big data in health in France. They served as abasis for initiating other structuring initiatives: the health section of the commission
on Artificial Intelligence (“Villani” mission) in 2017-18, then the mission to prefigure
the national data platform (also named Health data hub) in 2018, leading to thecreation of this platform in 2020. The choice was made of a single and centralizedarchitecture, the development of expertise in terms of large national and local
databases linkage, and the promotion of the creation of hospital data warehouses.
One of the missions of the Health data hub is to promote the reuse of health datafor research and public health purposes, but also for the development by public
or private actors of AI algorithms. At the same time, 4 interdisciplinary institutes
in artificial intelligence were created in 2019 (3IA), as well as a priority equipment
program for research in digital health in 2023. All of these initiatives raise a variety
of technical, social and legal questions, which we will discuss during this lecture.

Health big data policy in France – a tentative microsocio-history approach
25 October 2023 | 18:00 - 20:00 (Tokyo time)
At Keio University: 35 Shinanomachi, Shinjuku-ku, Tokyo
160-8582, JapanIn English

Abstract
In 2015, the French Ministry of Health and Social Affairs ordered an inventory andreflection on big data in health. At the same time, the services of the French Prime
Minister ordered a reflection and the establishment of an ambitious action plan
relating to genomics for research and healthcare for 2025. While I was piloting
the first group, and it seemed logical to consult with the second group, we wereexplicitly asked not to communicate with each other and to work separately. This
astonishing duality of reflection and action well symbolizes the situation and thedynamic about digital health in France, where history, the relationships of public
institutions with each other and towards citizens as well as the political dimension
shape broadly the current landscape: to understand the expectations and current
concerns in terms of big data and artificial intelligence in health in France, it isnecessary to represent the main actors, from the 80s to today.
In this lecture, I will therefore present a brief socio-history of French public
institutions which explains the current opportunities and obstacles in terms of big
data in health; I will take stock of the situation in terms of systems and initiatives topromote a certain number of uses of big data and AI, as well as the relationships
maintained between France and Europe, but also the United States on this issue,
particularly in terms of regulation and data protection. I will draw the ecosystemof health data in France, highlighting the areas where the efforts of the different
actors are concentrated, in what form, but also the areas of weakness or of lesser
interest. Among other things, I will address these specific questions: What are theexpectations and concerns in France regarding R&D and medical applications
based on medical big data? How are stakeholder concerns being overcome?

Frontières et modes d’existence de la médecine
personnalisée à l’ère du numérique
27 October 2023 | 15:00 - 17:00 (Tokyo time)
At The University of Tokyo: 7 Chome-3-1 Hongo, Bunkyo
City, Tokyo 113-8654, Japon
In French and Japanese>> MANDATORY REGISTRATION <<Abstract
Le programme de la médecine s’est articulé depuis au moins l’Antiquité autour deces 3 éléments : un sachant qui peut être aussi praticien, des savoirs concernant lesaffections et les moyens de s’en prémunir ou de s’en débarrasser, et une personne,
un consultant, un « malade ». Ce programme inclut donc par nature, un caractère
individuel et personnalisé.
Ces dix dernières années, le concept de médecine personnalisée, plus largementde médecine 4P (personnalisée, préventive, participative et prédictive), suscite unregain d’intérêt au sein du monde de la santé.
Que peut signifier, et impliquer, cette médecine personnalisée ? En sus des 3éléments cités, la médecine 4P rend plus visible la participation d’autres élémentsclés : le développement technologique, et les acteurs qui promeuvent cedéveloppement d’un point de vue idéologique et commercial.
La personnalisation mise en avant entend toucher au moins deux moments despratiques en santé : la prévention et le curatif. Ces deux moments ont vu leursmoyens d’action augmenter grâce d’une part au développement d’un modèlebiomédical de la santé prédominant, appuyé sur l’essor de l’evidence-based
medicine mais aussi de l’épidémiologie et du concept de facteur de risque, etd’autre part des technologies comme celles de séquençage du génome et dunumérique.
Aujourd’hui, la médecine personnalisée est à l’intersection du discours, dudéveloppement technologique et de ses potentiels apports à la santé. Ce discours
est tenu par plusieurs acteurs, aux intérêts qui peuvent diverger et apportant
autant de définitions de la médecine personnalisée : à partir d’une approcheinterdisciplinaire liant sociologie, épistémologie appliquée et sciences de la santé,
nous proposons de discuter de la position de ces acteurs (professionnels desanté, entreprises technologiques, financeurs entre autres), des définitions qui en
découlent ainsi que des implications actuelles ou possibles de ce discours sur lespratiques en santé et le système de soins en France. Enfin, nous reviendrons surl’articulation entre social et individuel et les dimensions non technologiques de lapersonnalisation.

SpeakerThomas LEFÈLEFÈVRE (Sorbonne Paris Nord University,IRIS)
Thomas Lefèvre is Assistant Professor – healthcare practitioner inlegal medicine and health law, at the Sorbonne Paris Nord Universityand at the J Verdier hospital, in the legal and social medicinedepartment. He is a researcher at IRIS (CNRS-Inserm-EHESS-USPN).
He is an engineer from the Institut Mines Telecom (2005), specialized
in signal and information processing, obtained a PhD in appliedmathematics and epistemology, and a ScD in social epidemiology. He is a
medical doctor specialized in public health and forensic sciences. He holds the “habilitation
à diriger les recherches” and supervises and co-supervises 6 doctoral students. One of
his two main research themes focuses on the study and assessment of the impact ofdigital technology and AI on professional organizations at a micro-social scale, in healthand in criminal law, which he explores using mixed methods and from an interdisciplinary
perspective. For example, he led the interdisciplinary Big Data Drop IT project, completedin 2020, on the impact of predictive techniques in forensic medicine and criminal law.
He led two national working groups, one for the French Ministry of Health (Big data andhealth, 2015-16), the other for the High Council for Public Health (National Strategy forRegistries in the Age of digital, 2020-21). In 2017, he created the ORFeAD network – Tools
and network for the federation, analysis and use of data in forensic medicine, making
extensive use of different AI techniques to facilitate access and structuring of multicenter
research. He is the author of more than thirty scientific articles, and recently contributed
several chapters to the reference textbook Artificial Intelligence in Medicine (SpringerNature).

Personalized Medicine and DataTechnologies, Welfare System, and EthicalIssues(PersMed Lab)GOALSThe PersMed lab raises three fundamental questions:• What are the respective benefits of home care and hospitalization?
• How personalized medicine can contribute to a public policy ofprevention?
• How to conciliate the development of personal medicine and theprotection of personal data?

CONTEXT
During the last decades,
tremendous progress has beenachieved in the application of newtechnologies to health. In this context,
there are rising expectations that major
health issues can be technologicallymanaged and that we will observefurther increase of human longevity.
In particular, it allows us ambitioning
the development of personalized
medicine,i.e.
diagnosis
andtreatment that are tailor-made foreach patient (Schleidgen et al., 2013).
A key is the accumulation of datain order to increase our knowledgeof each patient through thestatistical management of individual
heterogeneity.
In this context, the potentialities
of data management by extended
intelligence or by artificial intelligence(AI) have attracted a lot of attention(Morley&Floridi. 2020, 2019). It isconsidered as the most promisingavenue in terms of innovationand transformation of our socioeconomic systems but also of ourintimate life (Lechevalier, 2019; Emaet al., 2016). To put
it simply, AI in
healthcare is an
AI isoverarchingconsidered
term used toas the mostdescribe thepromisinguse of AI toavenue of our mimic humansocio-economic cognition in
the analysis,systems andour life.

5presentation,andcomprehension of complex
medical,andhealthcare data. Although theconcrete applications of AI
to healthcare are diverse(e.g. using AI to efficiently
diagnose and reduce error;
making more accurate andearlier cancer diagnosis withAI; developing new medicineswith AI), it is possible to consider
that the primary aim of healthrelated AI applications is to analyze
relationships between prevention
or treatment techniques andpatient outcomes. At the sametime, despite or because of allthese promises, AI in healthcare
raises several unprecedented ethicalconcerns related to its practicesuch as data privacy, automationof jobs, and representation biases(Lechevalier, 2019).

6are diverseinnature(Dalgarrondo&Hauray,2018). First of all, the development of
personalized medicine is at odds withthe logic of health insurance systems
AI is just one example, among many
that are build on a socialization of risks
others that deserve our closeand on a normalization of diagnoses
attention, as they have in common toand treatments. At the same time,
mobilize personal data on health, withthese socialization and normalization
the goal of developing a personalizedshow some diversity across countries,
medicine, in the same spirit thanfor example from the US – where
what was allowed by past personal
individual health insurance principles
relationship between doctors andare still dominant and lead to healthpatients. The range of application isexpenditures that are both diverse
also very wide from delivery of oxygen
across income groups and amongat home for a patient suffering fromthe most important in the world – tovarious kind of respiratory problems
Scandinavian countries – whereto diagnosis of cancer or thethe principle of publicconception of drugs. It
AI inhealth insurance is theconcerns medical carestrongest.
Besides
healthcare
in institutions (hospital,
the insurance issue,
raises severalclinics) and at home.
which is a condition
unprecedented
for the solvability
These technologicalethicalconcerns
ofpersonalized
premises cannot be
medicine,
thesuch as data privacy,
realized in putting
aside the functioning
automation of jobs, organization
ofof our health systems.
and representation healthsystems
themselves
isanbiases.
They also lead toimportantfactorseveral concerns that

that may promote and impede relies on estimations with different(e.g.
economic
the development of personalized methodologies
medicine: it can be more or less methodology focusing more on
efficiency and cost anddecentralized,dominatedsociological methodology
by some groups (e.g.
Thefocusing
moreondoctors) or others
developmentwell-being) and a(e.g. institutions) andof personalized
political
economycentered or not onperspectivethatpublic hospitals for
medicine is at odds
example. Last butwith the logic of health takes into accountthe different vision
not least, the use
insurance systemsofstakeholdersof personal datathat
arebuildona(doctors, patients,raises ethical andpolitical concerns. socialization of risks and health insurance,government,
The access to andon a normalizationetc.).
Basedonthe use of theseof diagnoses andthispreliminary
data are a condition
treatments.
investigation, it is thenfor the development
possible to discuss theof personalized medicine.
limits of the mandatory health
However, it lies on the consentof patient and is conditioned by a insurance in a context of personalizedcertain level of trust for medicine. One polar position is totheinstitutions focus on public insurance, in this case,incharge it is difficult to value the diversificationofstoring, of health services in order to takesharing, and into account the heterogeneity ofusing these individuals, even if the quality ofdata. Is it healthcare is taken into consideration.
p o s s i b l e The other polar position is to consider
to give this that personalized medicine requires
getting out the framework of publicinsurance. Between these two polar
responsibility positions, there are of course diverseto the private intermediate positions.
sector? Is the2) How personalized medicine
leadership of public institutions theguarantee of the absence of any can contribute to a public policy ofprevention? From this perspective
misuse or abuse?
the key issue is to analyze under which
conditions personalized medicine canTHREE QUESTIONS
contribute to the overall containment
This context raises three of healthcare expenses.
fundamental questions that will be at3) Howto
conciliate
thethe center of our investigation:
development of personal medicine
1) What are the respective benefits and the protection of personalof home care and hospitalization? data? From this perspective, the key
The issue at stake is to articulate issue is identifying the institutional,
these two modes with the practice social, and political conditions toof personalized medicine. It requires build trust between stakeholders.
a preliminary investigation that7

OUR CONTRIBUTION
In this context, it is important to mobilize not only data scientists andengineers but also researchers in social sciences in order to discuss, criticize
and compare the uses of data in healthcare, together with stakeholders,patients, medical doctors, policy makers, and the industry. Moreover, given
the differences across countries, adopting an international and comparative
perspective is essential. From this viewpoint, a dialogue between Japanand Europe is particularly relevant, the technological advances in this field
are comparable, the ethical principal are similar, while there is a significant
institutional, social, and cultural diversity.
Our proposal is based on the collaboration
betweenJapaneseandFrench
researchers from different fields anddisciplines as well as stakeholders
from different sectors. In
order to guarantee a fruitful
dialogue
betweenthese
contributors and a certain
level of convergence, theFFJ has already gather
them in large and small
groups before thebeginning of theproject. It has
also led toanefficient
screeningprocess.

>> PersMed Lab page - http://ffj.ehess.fr/lab_persmed.html
Contact: Fabien MICHEL (Project manager) - fabien.michel@ehess.fr
OV C ARErPesMed

FFJ healthprojects

8CTEL

IAIN NSHAURPERSMED
Find out more about the project on FFJ website
ffj.ehess.fr/lab_persmed.html

Fondation France-Japon de l’EHESS
Campus Condorcet | 2, cours des Humanités 93300 Aubervilliers - ffj@ehess.fr
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