Six Radical Visions for the Future of Health (including Self-Serve Pharma)


Today I gave the closing presentation at the National Medicine Symposium, rounding out deep discussion over several days on how to get better use of medicines. I developed six radical ideas that could be part of the future of health. The intention was to be provocative rather than rigorous, generating new ways of thinking about how healthcare may evolve.

Here are brief summaries of the six visions I presented:

1. Complete data.


Image source: Toto

The amount of information that we have about the health of an individual could become comprensive, generating terabytes of data from just one person. Bathrooms that monitor not just what we excrete but also analyze our skin color and tone as we look in the mirror are just the beginning. Images and sensors could record everything we eat and all medicines we take, providing far better analysis on the effectiveness of drugs. Odor is a highly data-intensive yet effective way to identify maladies. We could build virtually complete data sets of our health on a second by second basis.

2. Personalized medicine


In a world in which individual genomes can be sequenced, we can not only identify which drug will be most effective for the individual, but potentially also synthesize pharmaceuticals for one specific person. While the cost will be high, some will be prepared to pay and there will be pressure for insurers to bear the cost.

3. Radical life extension


The trend for over two centuries is that for every decade that passes, life expectancy in developed countries increases by two years. If this varies, it is most likely to the upside, severely aggravating the existing aging of the population. The implications for healthcare would include not just new treatments, but a massive increase in aged care support.

4. Robot help

Robots and artificial intelligence will have manifold roles in healthcare, including avatar doctors, exoskeletons for nurses, and automated surgery. As I’ve written before, one of the most important tools will be emotional robots, that can demonstrate empathy and help patients in their recovery.

5. Modular R&D


The current pharmaceutical research and development chain is broken in many ways, driven by creating blockbuster drugs and rapidly running out of steam. There is an opportunity to break down R&D into discrete components from discovery through to clinical trials and regulatory approval, each of which is funded separately. If effective profit-share mechanisms can be created, risk will be distributed and there could be a flourishing of drugs developed for smaller markets. Innocentive, originally founded by Eli Lilly, is just the first step in distributed pharma innovation.

6. Self-serve pharma


Image credit: C-Ali

Patients now have massive medical information available, and they have the time and incentive to do research into what would be relevant to them. Why not throw out drug regulation, and leave people to make their own choices if they want? Most would rely on doctors, but others would self-medicate, usually extremely well. The world of self-serve pharma has already begun. How far will it go?

  • Ross-
    Love this vision of the future of medicine. I think you are spot on with the idea of dosage targeted to a specific person’s genome. There will need to be adjustments for contextual (i.e. environmental) influences as well. I happen to work with Marshfield clinic in northern WI and they presently have the largest population-based biobank in US. Lots of great research on personalized medicine will be coming from that biobank and other ones in US. Thanks for keeping us focused on the future of medicine.
    Marshfield Clinic biobank:

  • Thanks Tom, very interesting. Yes absolutely there will be many other indicators of what are the most effective medicines and dosages. If we get a lot more data (point 1 above) that will be a lot easier 🙂

  • Actually personalized medicine will likely bring down the costs of medicine. I have recently helped spin out a company ( that helps physicians and pharma predict if a patient will respond to therapy.
    Every given year a large Pharma company will push 8-10 large phase III clinical trials each costing hundreds of millions of dollars. Unfortunately most of those trial’s fail. Some fail because the study population was too broad and thus not enough patients responded to meet FDA approval standard. The cost of those failed trials are rolled into the payment structure for drugs that did work.
    Tools like the one we developed will allow Pharma to more effectively stratify patients and thus make more of those drugs successful. Less trial failures means the cost of effective treatments will be globally reduced.
    Costs will also be down for insurers since instead of the current “best practices” trial and error, physicians will be able to predict if a patient will respond to therapy and thus avoid many lines of therapy that are ineffective and costly.

  • Great article, particularly points five and six. Unfortunately, I fear too many people have a vested interest in the existing system for those issues to progress as quickly as they should.

  • I have found so many ways through which we can get the good results.Anyways keep it up and keep continue with your valuable thoughts.

  • Thanks Ian, very interesting.
    Yes Gregory, the current system is very entrenched, but there’s still scope for exciting stuff to emerge 🙂