Personalized Medicine. A Multidisciplinary Approach to Complexity

University Campus Bio-Medico of Rome, Italy | February 2-4, 2020

In recent years, the concept of “Personalized Medicine” (PM) has acquired a central place in medical literature. The definition of PM is in itself controversial and widely debated. The connection between “personalization” and genotype is evident, for example: knowledge about the genes of a patient is useful to tailor -sometimes and for some diseases- treatment to the patient’s condition.

In a broader sense, however, “personalizing medicine” means to consider the variability of the human body in itself and in relation to its context in order to diagnose and treat individual patients in the most fitting and effective manner. In this second, broader sense, PM has a long historical background, which ultimately coincides with the nature of medicine itself. Medicine is simultaneously a science and an art, both depending on scientific universal laws and dealing with the contingent particulars of actual life conditions. In other words, a “personalized” approach to health and disease seems inescapable when facing the striking feature of complexity showed by human biological functionalities. The complexity of human physiology emerges even more evidently nowadays due ever-increasing advances in bio-medicine and technologies.

In this framework, a personalized, individually-oriented approach to the human body, its dynamics, and conditions seems particularly convenient. This meeting aims to interlace recent viewpoints on the concept of “personalized medicine” from different domains: medicine, bioengineering, ethics of innovation, artificial intelligence, economics and the social sciences. This interdisciplinary approach can open the way for a reinforced multidimensional concept of “personalized medicine” itself. Combining a scientific and a humanistic approach to the understanding of personalized medicine is crucial. Humanities are particularly suited to questioning the theoretical consequences of the new frontiers in medicine and technologies. Yet they should also help science to set its theoretical premises.

Discussants

Maria Rosaria Brizi - University Campus Bio-Medico of Rome, Italy

Massimo Ciccozzi - University Campus Bio-Medico of Rome, Italy

Laura Dugo - University Campus Bio-Medico of Rome, Italy

Guglielmo Militello - University of the Basque Country (UPV/EHU)

Edwin Morley-Fletcher - President of “Lynkeus”

Andrea Pensotti - University Campus Bio-Medico of Rome, Italy – Actire Ltd

Julian Reiss - Institute for Philosophy and Scientific Method, JKU Linz, Austria

Alessandra Santacroce - President of IBM Italy Foundation, Italy

Daniela Scaramuccia - Director of IBM “Health & Life Sciences”, Italy

Jacob Stegenga - University of Cambridge, UK

Henrik Vogt - Norwegian University of Science and Technology, Norway

Other Participants

Silvia Caianiello - Institute for the History of Philosophy and Science in the Modern Age, Naples, Italy

William Peden - Polytechnic University of Marche, Italy

Julia Tinland - Sorbonne University, Paris, France

Paper Abstracts

1. Mariano Bizzarri  (Dept. of Experimental Medicine, Systems Biology Group Lab, University “La Sapienza”, Rome, Italy)

Personalized Treatments: where patient’s history and biological background meet

Current studies on “personalized medicine” focus prevalently on network-based models of integrated genome function. After the sequencing of the human genome in 2001, there has been interest in genomic analysis of tumour with the idea of characterizing somatic mutations that occurred during cancer emergence and then developing better adapted to the treatment of a given tumour. Thereby, since the eighties, the agenda of pharmacology discovery was dictated by aiming at discovering “relevant” molecules (along with their classical rules of interaction), abstracting from the true, physiological response of cells, tissues and organism. In this perspective, genes assume the fundamental “causal” role while cells simply act as causal proxies, dispensable because they represent an irrelevant intermediate level between the molecular input and the organismal output. Regrettably, the demonstration of the heterogeneity of the genomic profile in different areas of a single malignancy and between the original tumour and its metastasis, as well as the ceaseless changes occurring across time within the same tumor, has broken the hope of genomic-base personalized treatments. Indeed, those models only partially explain the unfathomable complexity behind the outbreak of a disease, as they prevalently rely on cell biochemical and genetic pathways, thus discarding the contribution of non-genetic factors, microenvironmental constraints and the interplay among different levels of tissue organization. Such framework, both theoretically and methodologically, is no longer tenable. Instead, we claim here that a comprehensive model should consider the disease as a “historical” process, in which different spatially (multi-level) and timely distributed factors interact each other in a complex, non-linear way. Accordingly, “personalization” means that we should decipher the interplay occurring between biological determinants and personal life events (exposition to toxins, life-style habits, acquired infection, and many other time-related medical occurrences), as a non-linear, complex process. Moreover, as the disease is properly a dynamic process – and not a static-stable condition - treatments should be tailored according to the “timing-frame” of each disease. This approach can help in detecting pre-disease state or critical transition points from which the illness might access different attractors, leading ultimately to different outcomes.

 

 2. Anya Plutynski  (Washington University in St. Louis, USA)

Why Precision Oncology is not Very Precise (and why this should not surprise us)

Precision oncology seems for many the best bet for precision medicine generally. In the ideal case, there is one test provided to patients, which will either provide clear-cut prognoses, or targeted therapy, given the presence or absence of specific biomarkers, followed by significant improvement in overall survival, with fewer side effects. I will argue that in the vast majority of applications of precision oncology, what we actually find, and indeed ought to expect, are rather different outcomes. Cut-offs for relevant biomarkers are contested and value-laden decisions, there appear to be moderate improvements in survival in the vast majority of cases, and overall, very few cancer patients are likely to benefit (cf. Hey, et. al., 2016; Tannock, et. al., 2016; Marquart, et. al., 2018). In this paper, I’m going to first explain why this is true, and why this should (by now) not surprise us. Moreover, I will explain how better communication of the scope and limits of precision oncology is essential to avoiding the therapeutic misconception with prospective participants in clinical trials and informed consent.

Keywords: precision oncology, biomarkers, reductionism, genomics, comparative effectiveness

 

3. Maël Montévil  (Institut de Recherche et d’Innovation, Centre Pompidou, Paris, France)

Conceptual and Theoretical Specifications towards Accuracy in Medicine

Technological developments in genomics and other omics methods originated the idea that precise measurements of these biological properties could lead to better therapeutic strategies. However, precision does not entail accuracy. Scientific accuracy requires a theoretical framework to understand the meaning of measurements, the nature of causal relationships, and potential intrinsic limitations of knowledge. For example, a precise measurement of initial position in classical mechanics is useless without a measurement of the initial velocity. Moreover, even in this deterministic framework, precise measurements do not entail predictability in the case of chaotic dynamics. These examples show that conceptual and theoretical accuracy is required for precision to entail progress of knowledge and rationality in action.

We outline our results in search of a theory of organisms. Biology is distinct from physics and requires a specific epistemology. For example, we develop the meaning of biological measurements, where historicity is a fundamental notion. We also emphasize that the historicity of biological norms that stems from evolutionary theory implies that patients and groups of patients can play an active role in establishing new norms to overcome a pathological situation, in line with the philosophy of G. Canguilhem. This dimension of medicine is required for accuracy.

 

4. Julia Tinland (volume)  (Sorbonne Université, Philosophy department, UMR Sciences, Normes, Démocratie, Site de Recherche Intégrée sur le Cancer (SiRIC) CURAMUS)

Personalized Medicine in Prevention: promoting or curtailing overdiagnosis, overmedicalization and overmedication?

In the development of predictive and preventive medicine, the accurate identification of risk and, even moreso, of individualized risk, is one of the highest stakes. The legitimacy of ensuing diagnostic and clinical practices depends on it. As such, the momentum gained by personalized medicine over the past two decades represents a substantial opportunity. Renewed focus on preventive approaches to care over purely curative ones has indeed been accompanied by advancements in genomics and epigenomics, epigenetics, and in our understanding of the psychosocial and environmental factors that might influence the complex systems that each patient embodies. However, it has also been tailgated by rising concerns over overdiagnosis, overmedicalization and overmedication (Hofmann, 2016): if we are now able to identify better than ever before individuals who are more at risk than others (at risk to develop a given pathology or comorbidities, negative responses to treatments, etc.), we are also more likely to consider them de facto ill and in need of medical treatment. Meanwhile, a higher predictive validity for markers of risk is also often presented as the most effective answer to such apprehensions. Progress in the personalization of diagnosis and care and in the individualization of risk is, as such, both the source of significant ethical concerns and a potential solution to them.

This paper defends the idea that, so long as the disruptive role that personalized medicine can play with regards to current nosologies is both acknowledged and accepted, it can help curtail issues of overdiagnosis, overmedicalization and overmedication associated with the rise of preventive medicine.

This paper thus aims to show how such issues arise through the development of personalized medicine in the context of prevention, as it can lead to an overrepresentation of patients under the umbrella of existing diagnostic categories. People who would not have been considered ill before are now seen as patients. It is through personalized medicine’s disruptive potential, however - which may see such categories profoundly altered - that it can also come to represent an effective way to curtail the issues mentioned above.

This line of argumentation is outlined via the detailed analysis of two case studies. Firstly, the implementation of pre-onset early detection and interventions in psychiatry (Addington, Heinssen, 2012), where the adoption of staged diagnostic models inspired by oncology (McGorry, 2007; Yung et al., 1996) over more the categorical models outlined in the DSM 5 (American Psychiatric Association, 2013) can be argued to help overcome concerns of overdiagnosis, overmedicalization and overmedication. Secondly, the diagnosis of asymptomatic patients with Chronic Lymphocytic Leukemia (CLL) (Binet et al., 1977; Rai et al., 1990) who are likely never to develop symptoms or require treatment (Baccarani et al., 1982), necessitates an adaptation of diagnostic and clinical practices based on a finer analysis of personalized risk. Therefore, a personalized, individually-oriented, approach to the dynamics of CLL seems quite necessary, so long as the constraints and limits of personalized diagnostics and clinical practices are adequately understood and represented.

Underlying this argument is a demonstration of how ethical and pragmatic considerations ought to serve as the basis for a more thorough, epistemological line of investigation (Mackenzie, Rogers, Doods, 2014) in order to understand better, as well as to evaluate, various diagnostic models.

 

5. Vincenzo Fogliano  (Wageningen University & Research, The Netherlands)

Laura Dugo  (Campus Bio-Medico University of Rome, Italy)

Abstract 1: Personalized Nutrition: overrated or misconceived?

The worldwide pandemic of obesity calls for new strategies to provide people a healthier diet. Unfortunately, for a vast majority of population it is difficult to resist the obesogenic environment: we are continuously exposed to tempting, delicious foods pushing us to eat more than we actually need. Homo Sapiens biological roots do not help in this respect: human body is programmed to accumulate calories to survive the periods of scarcity; which “unfortunately” do not arrive anymore. Social life, shopping at the supermarket, a simple walk in the city centers are opportunities to eat something.

In this framework, the possibility to use the combination of new IT technologies and personal biological data to nudge (push) people to control their eating behavior represents a thrilling opportunity. Personalized nutrition is considered the new frontiers to allow humanity escaping a destiny of overweight.

The first actor of the personalized nutrition revolution are technological devices. On one hand, the possibility to develop smartphone applications providing customized information and suggestions. On the other hand, wearable devices to monitor diet related parameters like blood glucose, blood pressure and biomarkers of body functionality.

The second actor will be the in-depth knowledge of our biological data: DNA and microbiota mapping allow to know the details of the specific nutrients’ need of our body. The modifications of our dietary needs can be recorded on air, informing us of the possibility to change our dietary pattern accordingly.

The food industry is able to get along the personalized nutrition revolution: new technologies are available to design new foods tailored on the need of niches of consumers. The expectation is that the consumers receiving personalized inputs are willing to pay more for a product which perfectly match their needs. Intelligent packaging, able to communicate to the consumers the specific characteristics of the products, could become the perfect tool to valorize such personalized foods. Last but not least the personalized food could be also the way to solve the eternal conflict between the consumer and food companies’ interests creating a mutual trust based on knowledge and understanding.

By the way, there are also some concerns shadowing the promising future of personalized nutrition.

The first one is of technical nature: the relationship between food (or food components) and health is not direct as it happens with the drugs (personalized medicine). In many cases the pillars of nutrition recommendations are very general. “Eat plenty of fruit and vegetables, increase the intake of dietary fibre, follow a varied diet” are indeed simple and effective measures that do not need to be personalized, being valid for everybody. There are some exceptions: in few cases scientific research proved a specific nutrient (and therefore a specific food) be useful for some subjects having a specific genetic profile or microbiota composition. Similarly, for people following specific diets for medical reasons (allergy, intolerance) or for their personal choice (vegan, paleo) the personalized nutrition tools could be helpful to keep them in the borders of a balanced intake of nutrients.

The other concern is of ethical nature: the knowledge of personal biological data and pattern of food consumption could be eventually used to restrict the individual food choices. As reported in the EAT-Lancet commission paper, the most effective solution to provide a healthy and sustainable diet would be the elimination of personal choices. In this dystopic future the “big nutritionist” would decide for each us the best meal in any moment of our life. It looks like science fiction, but actually in many societies the need to reduce the health care costs by forcing individual behavior is already ongoing.

Abstract 2: Personalized Nutrition: are we there yet?

The worldwide pandemic of obesity calls for new strategies to provide healthier diet. Unfortunately for a vast majority of population it is difficult to resist the obesogenic environment: we are continuously exposed to tempting, delicious foods pushing us to eat more than we actually need. Human body is genetically programmed to accumulate calories to survive the periods of scarcity, which “unfortunately” do not arrive anymore. In this framework, the possibility to combine new IT technologies and personal biological data represent a thrilling opportunity to induce people to control their eating behaviour. Development of smartphone applications and wearable devices goes along with the in-depth knowledge of our biological data; the modification of our dietary needs can be recorded “live” providing us with tailored advises about dietary and lifestyle patterns to change. Food industry is running towards the ever-growing interest of consumers about food quality and composition; we eventually expect food to prevent, or even cure, diseases. Diet cannot be administered as a drug though, as it is strictly connected with so many human’s feelings emotions and social habits. The market already created a whole new consumer’s niche of personalized nutrition products and services, but are we ready for this?

Keywords: Personalized nutrition, Obesity, Diet, Lifestyle, Nutrigenetic

 

6. Barbara Osimani  (Center for Philosophy, Science, and Policy, Univpm, Ancona, Italy /MCMP, LMU, Munich, Germany)

Pharmacovigilance as Personalized Evidence

The rise of personalized medicine is likely to considerably alter the evolution of pharmacosurveillance. Personalized medicine could for instance determine which enzymes are expressed in each individual and from the knowledge of the pharmacological drug it would be possible to avoid the drugs that compete for the metabolism with the other drugs that the patient is taking. Therefore, it would be possible to reduce the toxicity of the accumulating quantities of drugs that are slowly and completely metabolized in individual patients. However, integrating pharmacovigilance and personalized medicine is a difficult challenge, for theoretical and methodological reasons.

We illustrate them here and present a tool developed in order to facilitate causal assessment in pharmacovigilance as a means to integrate causal knowledge about drug and adverse drug reactions (ADRs) and statistical knowledge about subgroup effects. While possibly constituting a methodologically valid tool for evidence integration, such framework has also the philosophical role of displaying how diverse levels, dimensions and lines of evidence interact in causal reasoning.

Keywords: Drug safety; Personalized medicine; Pharmacosurveillance; Pharmacovigilance; Precision medicine.

7. Sara Green  (Section for History and Philosophy of Science, Department of Science Education, University of Copenhagen; Centre for Medical Science and Technology Studies, Department of Public Health, University of Copenhagen)

Patient-derived Organoids in Personalized Medicine – towards a science of the individual?

An interesting question for philosophy of science is how the “personal” gets constituted, scientifically as well as socially, through new technologies in personalized medicine. Tumor organoids are 3D cultures based on tumor samples from individual patients. Given their ability to capture individual variation, patient-derived models have been highlighted as breaking way for a “science of the individual” or a “one patient paradigm” in medicine. We combine philosophical and ethnographic analysis of laboratory research and clinical practice to investigate the translational potentials and challenges of tumor organoids. Rather than asking whether the models adequately represent the patient, we explore how practitioners in the field deal with the challenges of balancing variation and standardization. Moreover, we analyze the implications of using organoids for patient-specific drug screening. We show how uncertainties about the evidential status of organoids are intimately connected to uncertainties about the nature of cancer itself and about how much variation models in personalized medicine can and should embody.

Keywords: Personalized medicine; Precision oncology, Tumor organoids; Personalization; Patient-derived models.

8. Xavier Guchet  (Université de Technologie de Compiègne, France)

From Ecogenetics to Exposomics: what’s new in molecular epidemiology?

In the past decade, PM had to face severe criticisms and, as I argue in my talk, exposomics was identified as a response to them. In particular, while PM was accused of reducing individuals to their molecules, and in particular to their genes, and of eclipsing the social and political determining factors of health, exposomics was supposed to bring more concerns for public health and associated political issues within the framework of PM. In this respect, exposomics may appear in the continuity of a previous approach that also intended to give a better account of the complex relationships between genes and environmental factors, namely ecogenetics – a term coined in the early 1970s by geneticist G. J. Brewer, who emphasized the political significance and impact of this scientific discipline. I argue in my talk that contrary to this impression of continuity, there is a gap between ecogenetics and exposomics – a shift towards approaches of individual health that are devoid of any critical social and political questioning.

9. Antonella Ficorilli  (Società per l’epidemiologia e la prevenzione “GA Maccacaro”, impresa sociale srl, Milano)

Personalized Medicine and Research Biobanking: from traditional informed consent to participatory governance

Emerging personalized medicine necessitates the collection, storage and processing of an increasing number and type of human biological samples and associated data within research biobanks throughout the world, materials and data which will be used in future large-scale health-related studies. Hence, ethical concerns regarding biobanks have increased, particularly in matters pertaining to autonomy and privacy. This debate has mainly focused on whether or not maintaining the informed consent model used in traditional health research sufficiently guarantees the dignity and rights of subjects, while at the same time serving as a good tool to obtain an appropriate balance between the research subjects’ interests and the public interest. The present paper aims to illustrate the evolutionary path of ethical reflection in this regard towards new models of informed consent, such as broad consent and dynamic consent, and new models of governance that take into account the necessity of involving subjects in the decision-making process, especially in the light of advancements in data mining and big data technologies.

Keywords: personalized medicine, biobank, ethics, informed consent, participatory governance, big data

10. Edwin Morley-Fletcher (volume)

(President of “Lynkeus”)

A GDPR-compliant blockchain-based system for sharing synthetic data and for computation “bringing the algorithms to the data”

The EU-funded H2020 project MyHealthMyData (MHMD) - coordinated (2016-2019) by the Italian company Lynkeus – is a blockchain-based system, permitting to access the Off-chain data stored by multiple hospital repositories and by individuals. The blockchain is the concertation layer, recording what transactions happen and specifying under what conditions and with what type of consent. The authorised access to data or data computation is enacted through the relevant Smart Contracts. Any registered user can browse the central Catalogue, which is ingesting and indexing all the needed metadata, fostering an integrated system for dataset search, and providing statistical representations and analytics. Output privacy ensures that no sensitive information is revealed within the Catalogue’s queries results. The MHMD blockchain is the digital space where the execution of the researcher’s request can be enacted triggering the process automation based on Smart Contracts.

Though advanced, this system still stumbles on an inconvenient truth: health data remain silos-based. Big Data and AI are difficult to apply in medicine, especially in rare diseases, where data driven solutions are most needed.

Since effective data sharing is still the exception in healthcare, MHMD has investigated what can lead research centres and biomedical industries to either share medical data or to have computational outcomes with output privacy. Since the risk of data breaches increases with the number of copies shared and what happens after the data download is no-more under control of the blockchain, rather than simply publishing health data either as pseudonymous or anonymous data, in MHMD the preferred solution has been to publish synthetic data, i.e. fully artificial data, automatically generated by making use of machine learning algorithms, based on recursive conditional parameter aggregation, operating within global statistical models.

Synthetic data typify the case of “personal data [which are] rendered anonymous in such a manner that the data subject is not or no longer identifiable” (Recital 26 GDPR). Especially Differentially-Private Synthetic Data Generation provides an until-now lacking mathematical foundation to privacy definition, as highlighted by the National Institute of Standards and Technology Differential Privacy Synthetic Data Challenge 2019. Scalable quality-control systems and iterative approaches allow to generate synthetic data being even more informative and robust than the original ones, leading to statistically equivalent sets, at a vastly lower cost.

The other privacy enhancing direction followed by MHMD has been Health Data Computation without accessing the data. Secure Multiparty Computation (SMPC) allows a set of distrustful parties to perform the computation in a distributed manner, while each of them individually remains oblivious to the input data and the intermediate results. Another solution, based on MORE Homomorphic Encryption, has been developed within MHMD and has been awarded the Innovation Radar Prize 2019 in the category Industrial & Enabling Tech, increasing its security with an additional obfuscation layer based on polynomial evaluation maps.

Lastly, since advanced machine learning approaches require high-quality Big Data and these are difficult to attain, especially in a centralized location, MHMD is using SMPC and Differential Privacy in the context of a “black-box" federated learning framework, where a secure ML request containing a model training pipeline is distributed to the data providers along with a set of parameters, and local computation results are then securely aggregated, repeating this cycle to obtain training iterations and model validations.

11. Maria Sophia Aguirre (The Catholic University of America, USA)

U.S. Opioid Epidemic: An Integral Approach to Prevention, Treatment, and Prognosis.

In the U.S., the opioid crisis has been declared an epidemic. Studies related to this issue, have mainly focused on the current state of the opioid epidemic; chronic pain and its role in the crisis. They have also studied the properties of opioids and how they interact with human neurobiology; the effectiveness and risks of opioids as a treatment for chronic pain; opioid addiction and dependence. Finally, pharmacological and psychological interventions for opioid addiction, opioid dependence, and chronic pain management have also been addressed. The U.S. response to the overdose epidemic has included policy initiatives at the local, state, and federal levels. The federal government officially declared an opioid crisis public health emergency. Several states have sought to implement new guidelines for prescribing opiates, expanded access to naloxone which reverses opioid overdoses as well as expanded drug treatment options. To address the latter, some health professionals have proposed the inception of access to treatment facilities for opioid detoxification; using interdisciplinary treatment models for chronic pain, opioid addiction and dependence. The latter have encountered legal barriers in the country; and therefore, proponents of such solution lack robust empirical evidence to substantiate their recommendation for opioid abuse treatment. While socioeconomic factors are typically controlled for, more often than not, relational factors are excluded from the analysis. In this paper, we seek to fill this gap, by proposing an integrated relational methodology to address the opioid epidemic in the US. Utilizing the National Longitudinal Study of Adolescence to Adult Health (Add Health, Wave IV) we identify effective channels of relations that could assist in the design of effective prevention efforts, increase the effectiveness of treatment, and improve prognosis.

12. Roger Strand (Centre for Cancer Biomarkers, University of Bergen, Norway; Centre for the Study of the Sciences and the Humanities, University of Bergen, Norway)

The Impact of a Fantasy

Personalized Medicine is a sociotechnical imaginary in the sense of Sheila Jasanoff: It is a collective vision for the coproduction of a future science, technology and society. This vision has long historical roots but is also the result of a specific context with ongoing changes in society, including the political economy of science.

Part of this vision is a fantasy in the sense that it runs counter to current scientific understanding of illness and disease. One may try to argue against such fantasies by using facts. One should, however, not be surprised if such arguments prove to be ineffective. What is at stake, is not a matter of facts and knowledge alone. In this paper, I shall try to take seriously the insight that personalized medicine is an imaginary, an expression of desire, and in part a fantasy, and discuss the possible impacts thereof.

René Descartes postulated that "we might free ourselves from countless diseases of body and of mind, and perhaps even from the infirmity of old age, if we knew enough about their causes and about all the remedies that nature has provided for us." Personalized medicine can be seen as yet another attempt at realizing this Cartesian dream. Antonio Gramsci famously wrote: “The crisis consists precisely in the fact that the old is dying and the new cannot be born; in this interregnum a great variety of morbid symptoms appear.” Is the Cartesian dream coming to its end, with personalized medicine as a morbid symptom, a reductio ad absurdum? If so, what it the new that cannot be born?

13. Massimo Ciccozzi (volume) (Campus Bio-Medico University of Rome, Italy)

TBA

Principal Inquiries

  • To what extent can the complexity of human physiology be addressed in terms of personalized medicine?
  • Which concepts of “health” and “disease,” “body,” “cure” and “care” are implied by the idea of personalized medicine?
  • What is the relationship between personalized medicine and complex diseases and to what extent can personalized medicine be the key to understanding them?
  • Does the application of personalized medicine to complex diseases always mean the same thing? How can the differences in personalized medicine be applied to different medical branches?
  • Which personalized medicine is appropriate for which patients?

Academic Leaders

Chiara Beneduce - Radboud University, Nijmegen, The Netherlands - University Campus Bio-Medico of Rome, Italy

Marta Bertolaso - University Campus Bio-Medico of Rome, Italy

Speakers

Maria Sophia Aguirre - The Catholic University of America, USA

Mariano Bizzarri - “La Sapienza” University of Rome, Italy

Antonella Ficorilli - Società per l’epidemiologia e la prevenzione “GA Maccacaro”, Milan, Italy

Vincenzo Fogliano - Wageningen University & Research, The Netherlands

Sara Green - University of Copenhagen, Denmark

Xavier Guchet - University of Technology of Compiègne, France

Maël Montévil - Institute of Research and Innovation, Paris, France

Barbara Osimani - Ludwig-Maximilians-Universität München, Germany

Anya Plutynski - Washington University in St. Louis, USA

Roger Strand - University of Bergen, Norway