Technological developments have enabled the collection of large amounts of data from a single patient, whether in the form of personal genome sequences or one of a number of other ‘omics’ profiles ranging from the transcriptome to the microbiome. This data revolution has contributed to a paradigm shift in the way we think about healthcare, with the aim of empowering patients with their own information. To highlight this change, Genome Medicine launched a special series of articles on Participatory medicine, guest edited by Charles Auffray from the European Institute for Systems Biology and Medicine, France, and Leroy Hood from the Institute for Systems Biology, USA, whose Editorial addresses the forces driving this shift. Here Hood discusses the advantages of participatory medicine and how he sees it shaping the future of modern healthcare.


How would you define participatory medicine?

Participatory medicine actually has many different components. I’d say, first of all, there is a big revolution coming in healthcare. That revolution is reflected in several different names: systems medicine, P4 medicine (predictive, preventive, personalized and participatory), or personalized medicine. In a sense, each of these names reflects variations on the theme of data-driven personalized medicine. This concept encompasses the idea that soon each patient will be surrounded by a virtual cloud of billions of data points and that we will have the computational analytics to integrate these data and reduce their enormous dimensionality to simple hypotheses about how to optimize wellness and minimize disease for each individual.

I would say that personalized medicine has four major components – predictive, preventive, personalized and participatory – and the ‘participatory’ element is  by far the most challenging. It deals with questions like, how do we educate patients, physicians and the medical community as to this new personalized medicine? It raises questions about how can we create the means to use the data of personalized medicine from these patients, so we can mine it for the predictive medicine of the future. This necessity is very much limited by the constraints of institutional review boards and the widespread and I believe inappropriate perception that the patient owns their own data and they can do with it what they wish (really society should own this data as it provided the resources to create this revolution in medicine, and these data are essential for generating insights of P4 medicine of the future). Appropriate protections for individual privacy and data security are essential, as are laws that prevent companies, employers or even family from abusing personalized data.

Another aspect of participatory medicine is my deep conviction that patient-activated social networks are really going to be the key for driving personalised P4 medicine into the healthcare system. A key question is how we create these networks and how can we design them so they can be educational to the patients, but at the same time facilitate crowd sourcing – that is, learning about personalized medicine by being a part of a network. And how can we use these patient-driven social networks to persuade physicians to accept P4 medicine and its fundamental principles?

Participatory medicine really relates to the fact that, in a relatively short period of time, every patient, as I noted above, is going to have a virtual data cloud of billions of data points, and we’ll have the wherewithal to reduce that data dimensionality to models about how to optimise wellness and minimise disease for each individual. The key question is: what is going to be the information technology that will allow us to capture each of the individual data clouds and then aggregate them into related clusters so we can begin to see the nature of different subtypes of major diseases, such as cancer, cardiovascular disease, infectious diseases, neurodegeneration and so forth?

So the ‘participatory’ element really has to do with the social aspects of personalized medicine, and how we bring it into the healthcare system. It deals with questions of data confidentiality, of security, of the ethics concerned with what you tell patients and what you don’t tell patients. For example, questions raised recently by the US Food and Drug Administration action on ‘23 And Me’, as to what extent personalised genomics can inform patients about what their conditions are, as opposed to needing to bring these data to patients through physicians and so forth.


What advantages do you see in a participatory model of healthcare?

P4 medicine has enormous advantages over current evidence-based medicine. One – it’s highly proactive; two – it’s focussed on the individual; three – it’s all about wellness and optimising wellness; four – it’s about creating these personalized data clouds so that we can know the individual in depth and sort out the relative contributions to disease of one’s genome and their environmental exposures; five – it’s about revolutionising how we think about clinical trials including the idea that clinical trials should be focused on analyzing and aggregating data from individuals and not from populations of patients; and six – it is about creating the patient-activated social network that will ultimately drive the acceptance of P4 medicine.

Currently clinical trials take 30,000 patients and put them in a big group and give some of them the cancer drug and some of them a placebo, and they record and abstract all of the responses into curves from which they assess how the population will respond to the drug and whether the drug itself is successful.  I would argue that approach has serious limitations.  Each patient is unique, both genetically and environmentally. The patients – as reflected by P4 medicine – need to be dealt with as individuals. After you’ve assessed their individual data clouds, only then you can begin to aggregate patients into related groups, whose responses to the environment are related, and will let individuals be treated effectively.

The final point about participatory medicine is the imperative driving force of social networks. One – for education of the patients, physicians and other health care professionals; and two – to bring this revolution in medicine into the current healthcare system.


Do you think the healthcare system is already shifting towards a participatory model?

I would say it’s changing in very slow and so far generally in very marginal ways. I think if you go to 98 percent of physicians they don’t have the faintest idea what a genome sequence means or signifies. I think if you go to most physicians, they don’t even think about wellness nor do they have much understanding of nutrition. Physicians don’t even really know what wellness is – except to define it by the absence of disease. I think if you go to most physicians, they’re not trying to be proactive and they place their patients in big categories that have been pre-defined and often are inappropriate for specific treatments. So I would say the healthcare system is starting to change, but very slowly.

Perhaps the place it’s changing in most interesting ways is with cancer, where now it’s beginning to become acceptable to sequence the individual’s normal genome and their cancer genome and determine if you can find cancer-driver genes that have mutated, for which there are drugs that you might get responses to. But I think that’s just the opening salvo of what P4 medicine is going to do in the future for each individual patient for most diseases.


Do you think the shift towards a participatory model of healthcare will be restricted to Western countries, or do you think it could be a worldwide transformation?

I, from day one, argued, “It must be a worldwide transformation”. I think there are a lot of arguments for why that is going to be so. I’ll give you just one. We’re now beginning to see a digitalisation of measurements in medicine and what happens with digitalisation is those measurements become incredibly inexpensive. The prime example is DNA sequencing which now costs 100,000 times less than it did 20 years ago—and we can look forward to still another 20-fold reduction in cost over the next  5-8 years.  As an example, we can look at communications: a poor woman now can make a living in a small rural village in India for her family, using a cell phone. That’s a digitised form of communication that’s really cheap (there are something like five billion cell phones worldwide). I think we’re going to have – in ten years – a digitised form of medicine that makes our personalized data clouds really cheap and these will be exported to the developing world as well as to the developed world. Frankly, I think it’s going to open up the possibility for a democratisation of healthcare that was inconceivable to think about even five years ago.


What do you think are the major challenges that participatory medicine has to face?

I think that participatory medicine still faces many challenges. Most physicians don’t know what it is, the healthcare system itself as well as physicians are incredibly conservative, the payers don’t quite understand participatory medicine and they’re not going to accept it unless you not only prove you can improve healthcare practice but you can make it cheaper as well. The regulatory agencies will need to move towards understanding and accepting the imperatives of P4 medicine. We need to have society as a whole accept the idea that our individual data really belongs to society in the sense it must be available to be mined for P4 medicine of the future.

So I think in every dimension, the system is going to be resistant to change. There are questions of how you educate the patients as well as the physicians and the system itself. Also, questions of how we can gain access to the data – as noted above – so we can use the ‘big data’ of individual patients to create the predictive and preventative medicine of the future – this, I think, is really critical. How are we going to create an information technology framework for a healthcare system that deals with the enormous complexity of personal data clouds? These are all challenges.


What do you think about the cost effectiveness of a healthcare system based on a participatory model?

I think it’s going to be enormously cost effective, and I can give you a nice example. I created a company called Integrated Diagnostics about five years ago, and its mandate was to use systems approaches to identify panels of blood diagnostic biomarkers to detect disease. Recently we’ve identified a panel of 13 biomarkers that gives us the ability, in lung cancer, to distinguish patients that have benign lung nodules from those that have neoplastic lung nodules. Since many surgical procedures are done on patients with benign nodules, the estimated cost savings – if this test were used widely for the American healthcare system, since the US sees three million nodules a year– is about 3.5 billion dollars per year. That’s a beautiful example of where P4 medicine has created a diagnostic that improves healthcare and at the same time significantly reduces the cost of healthcare. This has been so successful, the test is now commercialized. In a very short period of time we have received approval for the test from insurers that cover almost a 100 million different patients. What drove the payers to accept the test so rapidly, in large part, was this promised cost saving.


What is next for your research?

My institute, the Institute of Systems Biology in Seattle, USA, is taking on a wellness project that I think is really going to be transformational. We will be looking at 100,000 well patients, employing a longitudinal Framingham-like test where we make six different types of measurements frequently each year across a 20 or 30 year lifetime period. The global vision for what this will allow us to do is firstly create those personal data clouds for each individual that will allow us to optimize their wellness and minimize their disease. Secondly, we’ll be able to mine the data of those people that remain well, and even those that become ‘more well’, for metrics of wellness – something that we’ve never had before. How you define wellness in health is an infinitely fuzzy sociologically questionable construct. We think we can have quantitative metrics for defining wellness. The third thing that is really exciting is over an extended period of time with 100,000 patients, you’ll be able to see transitions from wellness to disease for all major types of disease. We’ll have an enormous amount of data on the early stages of those diseases, with the hope of being able to understand the earliest stages of disease mechanisms and create early diagnostics, but most important being able to divert that patient, in a very early stage, from that disease trajectory back to a wellness trajectory.  This is where the cost savings for healthcare will really become significant.

So I think this project is going to create a database that, in a sense, will be an opportunity to mine the data of wellness on the one hand, and disease transitions on the other hand. I think these databases are going to create enormous economic opportunities and spinoffs that will, for example, constitute the wellness industry of the future which, I predict, in 10-15 years will far exceed in market capital the healthcare industry. These databases will also transform how we think about healthcare through coming to understand the wellness to disease transition.


To hear more from pioneers in participatory medicine, listen to this accompanying podcast with Leeroy Hood, Michael Snyder and Kim Norris on how the roles of the different stakeholders are being transformed, and what challenges still lie ahead. A full transcript of this podcast is available here.


Questions from Andreia Cunha, Senior Assistant Editor for Genome Medicine.


More about the researcher(s)

  • Lee Hood, President of the Institute for Systems Biology, USA.

    Leroy Hood

    Leroy Hood is founder and President of the Institute for Systems Biology, USA, where he develops projects that are leading the way in P4 Medicine (predictive, preventive, personalized and participatory medicine). Hood obtained his medical degree from Johns Hopkins School of Medicine, USA, and his PhD from the California Institute of Technology, USA. He went… Read more »


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  • Neverharm

    Predictive, preventive, personalized and participatory medicine: what a lovely assembly of labels! But maybe we can use some parsimony here. I propose that “predictive” and “preventive” can be well subsumed under “anticipatory” and “personalized” and “participatory” can both be subsumed under “interactive”. While the first two require a knowledge base in epidemiology, the other two require clinical and interpersonal skills, such as communication skills. Psychosocial medicine is already anticipatory and interactive, as it is framed in the bio-psychosocial model.