TRANSACTIONS OF THE AMERICAN CLINICAL AND CLIMATOLOGICAL ASSOCIATION, VOL. 128, 2017
Discovering New Diseases to Accelerate Precision Medicine CALUM A. MACRAE, MD, PhD BOSTON, MASSACHUSETTS
Abstract A rate-limiting step in multiple areas of medicine is the limited number of discrete disorders that current technologies are able to identify. Most clinical disease entities are aggregates of large numbers of discrete biological processes that simply happen to share one or two common features. We have begun to translate a wide range of new technologies to the clinic in an effort to improve the resolution and the efficiency of bedside diagnostics with a view to improving drug trials, genetic studies, and the effectiveness of the clinician in a digital environment. The general trajectory for change that new technologies will bring is outlined with some specific examples of areas where such change has already begun to occur.
Redesigning medicine Medicine is undergoing more rapid change than at any time in the last 200 years. The costs of delivering care in the current model and the opportunity for new technologies or new industries to capture substantial parts of the biomedical economy have conspired to promise a revolution. Molecular insights in cancer and chronic disease have reached the clinic and are highlighting the need for improved resolution in diagnosis and management. Improved therapies are moving many inpatient cases to the outpatient setting, while the feasibility of asynchronous transactions is driving traditional outpatient care to the home. The implementation of electronic health records has accompanied these changes and promises to close at least some of the data gaps in healthcare. The advent of massive streams of structured data would open health care to rigorous analytics and predictive quantitative biology. The possibility that extant information will be continuously collated, curated, and integrated then validated, bringing formal Correspondence and reprint requests: Calum A. MacRae, MD, PhD, Brigham and Women’s Hospital and Harvard Medical School, 75 Francis Street, Boston, Massachusetts 02115, Tel: 617-732-8087, Fax: 617-732-7134, E-mail: [email protected]. Potential Conflicts of Interest: None disclosed.
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analytics to medicine, is clear, but there remain a set of substantial obstacles to this vision.
New measurements Without transformative changes in the resolution and scale of measurement in biomedicine, whether of the core biology or the transactions themselves, it will prove difficult to realize the care redesign that has been imagined. Most data within the electronic record consist of semisubjective aggregates of bedside impressions, billing codes, and a remarkably small set of measured phenotypes. Importantly, the majority of the traits captured by medical investigation consist of legacy endpoints, modern estimates of reflections from the Oslerian era or before. There is also a remarkable lack of standardization across medicine with virtually no efforts made to introduce universal standards for most areas of medicine. Ironically, genome sequencing currently represents one of the only complete and standardized datasets in modern biology, although other exceptions include the 12-lead EKG and the international normalized ratio for prothrombin time. The introduction of rigorous protocols for routine measurement would not only reduce variations in practice, but would also enable formal predictive computation, permit the early identification of disease, and lay the foundation for a truly “learning” digital health record. Real-time data trajectories and analytics could also stimulate completely different levels of precision in medicine, such as reimbursement based on evidence of efficacy in the individual patient. Traditional binary phenotypes, many rooted in 18th-century observations, must be replaced by quantitative metrics of the underlying physiologic and cell biologic traits. Standardized protocols for data collection, a feature of randomized controlled trials for decades, must be implemented in clinical practice. Innovation along these lines, and at the requisite scale, implies a need for new data display and data collection infrastructure and the ability of providers to integrate, in the clinic or at the bedside, the massive amounts of data accumulating in health care. Emerging technology must permit such bidirectional data flow without distracting and without onerous data entry, and without the need to duplicate costly informatics infrastructure for research.
New culture Not only are the mechanics of medicine in flux, the sociology of the caring professions is also undergoing remarkable change. Traditional
BK-ACC-ACCA_2017-170020.indb 84
6/2/2017 9:31:49 AM
DISCOVERING NEW DISEASES
85
clinical care or medical research teams have been built around the individual clinician-patient relationship or individual investigator, respectively, but the “teams of the future” will be created around very different architectures. A major challenge will be to preserve the core elements of the personal therapeutic relationship, while creating venues where new teams and new partnerships can evolve. For example, technology companies bringing new wearable sensors to market are collaborating with large pharmaceutical companies who need to segment clinical trial cohorts. Traditional payers are developing relationships with “big data” companies to try to understand the health of their customer base, although in many instances even the best current datasets are not big enough or the associated reference data are not robust enough to do so meaningfully. Surgeons and interventionists are conspiring to create less invasive ways to treat valvular heart disease with the eventual goal of eliminating conventional valvular surgery itself. Such a drive to make current approaches obsolete is a mantra in many innovative industries, yet the traditional rituals and regulatory constraints of modern medicine have slowed dramatic changes in our field. Nevertheless, fundamental rationalizing forces that have successfully remodeled other monopolies from the travel industry to the legal profession are now coming to bear on medical practice. By defining more clearly those traditions in medicine which are truly valuable, we will build systems that can reinforce and enrich these qualities while still allowing creativity and change to flourish. The natural history of information technology has been to broaden access and, in turn, to globalize previously local endeavors. While the need for emergency physiologic support will retain local infrastructure in many areas of medicine, the trend toward globalization will affect everything that physicians do. Management algorithms for basic medical decision-making will likely move to the individual patient, while stepwise improvements in information flow and simple convenience will begin to bypass traditional venues of medical care for all but catastrophic events. Many patients already perceive the medical establishment to be part of the problem, and our failures to deal with acknowledged issues such as heterogeneity of care delivery, lack of transparency, and chronic overstatement in research do little to mitigate this perception. That informed individuals are becoming more engaged in areas that previously were the province of the professional presents an immense opportunity, but also represents a substantial threat to the monopolies of old. In an era where everyone will have the same information, traditional medicine will have to consider where it truly adds value, and reward systems will need to be built around
BK-ACC-ACCA_2017-170020.indb 85
6/2/2017 9:31:49 AM
86
CALUM A. MACRAE
that value. The old order dependence on cross-subsidization between specialties is not likely to be sustainable, and the importance of cognitive input in the practice of medicine will have to be recognized where it is required.
Re-educating our profession To imagine even a fraction of this future becoming a reality without changing the culture of medicine is not easy, yet it is difficult to imagine much of this not happening due to the external pressures outlined above. While as a result of deeply vested interests biomedicine is one of the last sectors of our lives to yield to such transformation, medicine also has a remarkable record of sustained and innovative change. To ensure that the biomedical professions can participate fully, medical education must undergo substantial transformation. The best and the brightest must be attracted back to medicine. Q uantitative skills systematically under-represented in medical schools must be re-emphasized and reinforced. It will be important to rethink how we differentiate as individual professionals acquiring new skills and reimagining adaptable teams of clinicians, translational investigators, and basic scientists. Retaining the best elements of the current educational framework while teaching physicians, scientists, and p hysician-scientists how to manage an exponentially growing knowledge base will require new tools and new workflows. The tensions inherent in these challenges have already been laid bare in recent debates on maintenance of certification. Here, too, technology will play an important role, as it becomes feasible to measure not just activity but quality of care at the level of the individual patient.
The new paradigm is a natural extension of prior effortS Different parts of medicine will change at different rates. Cardiology has been at the forefront of many of the major movements within biomedicine, including wellness, prevention, randomized controlled trials, guidelines, and scoring systems. There is a long history of engineering and in silico modeling in cardiovascular science, and the implantation and management of devices is already a core function of our specialty. As genomics, technology, big data, and other innovations are applied increasingly to common complex disease, cardiovascular scientists and
BK-ACC-ACCA_2017-170020.indb 86
6/2/2017 9:31:49 AM
DISCOVERING NEW DISEASES
87
clinicians will likely be at the leading edge as the pressures to redesign clinical care become more intense.
Preserving the core As technological transformation begins to affect the clinical data collection infrastructure, so there are some direct implications for the physician-patient interaction. Recent trends toward data entry dominating the clinical encounter will be reversed and the opportunity to build truly therapeutic relationships will grow again. The devolution of non-professional services to the patient level, supported by technological advance, will allow physicians to re-professionalize and focus their efforts on the components of biomedicine that currently escape algorithmic solutions. At its core, the transformation of clinical measurement that is currently underway will herald a more holistic assessment of disease, reduce the administrative burden of the modern clinical encounter, and with these changes drive a return to traditional clinical encounters.
DISCUSSION Calkins, Baltimore: Enjoyed your talk. You’re in a unique position as a geneticist, and head of cardiology at the Brigham. I’m hoping you will make a lot of progress. Have you focused on precision medicine? You started your term with a concept of precision medicine. That sort of concept which has become extremely popular, and you hear about it everywhere. But practically, as a cardiologist, what does it mean to you or your division/department? Help us with that term and what you are doing at the Brigham in terms of bringing precision medicine to reality. MacRae, Boston: Hugh, thank you. An excellent question. I am reminded of something that Garret Fitzgerald once told me, which was that precision medicine was the future of medicine and always would be. I think the key thing about precision medicine is that it is what we have always done, and I think the only thing that’s changing is the resolution at which we are precise. I like to actually think about it almost as mechanistic medicine rather than precision medicine. I think what we are trying to do is get beyond the general descriptors that we have used for so many decades and get at things that actually discriminate what’s really going on in the patient. And I think the sad thing as I’ve said is that while we have done quite a lot of that in the lab, we have failed to connect it very directly with the patient so that often people will end up having mechanistically distinct disorders that are being managed in a completely different way and just simply because they happen to share a common superficial phenotype. The one other area that I think is driving precision is actually the cost of doing clinical trials. Fundamentally, what we’ve done is we’ve reached the point where the size of trials that we need, in order to see incremental effects, are no longer affordable by society. So, that’s one of the things that actually drove me away from using the term precision though I am
BK-ACC-ACCA_2017-170020.indb 87
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CALUM A. MACRAE
not disparaging it in any way; I am just saying that I think it’s part of everything we’ve always done. We should try to tailor the therapy to the patient. But what we really need to do is begin to be able to match the drug and the patient mechanistically. And the main driver for that is reducing the size of clinical trials which I actually think is a healthy way of moving forward. We recently took a drug for heart failure through registration, as you know, in collaboration with your colleague Dan Judge with 12 patients. And the only reason we were able to do that is because we had a mechanistically specific subset of disease. I believe thinking about precision medicine as a way to actually change the paradigm for how you get drugs into the clinic is one very valuable approach. But one other thing I will say about precision that I think is important is that disease stratification without new drugs is irrelevant. So, we can stratify until we are blue in the face but if we don’t actually develop or identify new ways of making new drugs, we are going to be in serious trouble because at the moment it is something like 15 to 20 years and about $1.5 billion dollars per drug. Unless we actually find the discrete way of developing drugs — we’re really going to be in a bind. With lots of new diseases but no way of actually ever treating them. Bodenheimer, New York City: Well, thank you very much for your provocative talk. You know I would feel personally sad if we were presaging the death of the physical exam. And I would just like your comments about can we look at the application on some of this precise technology and utilize this but then develop methods of s trengthening observation with physical exams so that we can deploy this throughout the world. We may be living in very rarefied academic centers but much health care is delivered throughout the world without access to such precise technology. MacRae, Boston: I could not agree with you more. I think two things: first of all, I hope I made it clear that not in any way would I devalue the physical exam. I actually think there are huge elements of the healing interaction that are only conveyed in the physical exam. I would be a very strong proponent of this. What I think is important is that we complement the physical exam and that we move it from being semi-subjective to being more objective, and I think there are rational ways of doing that quite effectively. I think many of the themes that I brought out are actually importantly related to what you just said. I think scalability is key. In fact, one of the most interesting things about a lot of these assays is that we have the good fortune of having faculty members that work in Africa, one of whom who has helped manage preventative health care across South Africa. I believe that we will find it much easier to implement some of these technologies on a smart phone, or using a simple bedside device in African context, where there are no vested interests and there are no limits on how quickly people have to move through the clinic, compared with Brigham and Women’s Hospital. So, I am convinced that there is going to be a large amount of this type of translation and I could not agree with you more that we have to do it in a way that preserves all of the essence of the physical exam which I think is a vital part of everything that we all stand for. Sacher, Cincinnati: Not to undermine the physical exam, but of course there is so much interest in the new advances in computing science such as the mining of big data. So, it seems to me that there may be something of applicability of what you are doing and perhaps sharing information with big data companies. MacRae, Boston: I could not agree more, and you probably saw we do quite a lot of work with technology companies like IBM, Microsoft, and with Google in exactly this space. One of the things that I think is actually quite interesting, though, is that many large efforts in this area already have spent a lot of time without clearly identifying signal amongst the noise. One of our strategies, and one of the reasons we got into this area, is to focus on informed ways to accentuate the signal, in the key areas that we are
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DISCOVERING NEW DISEASES
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actually interested in for medical therapy. But I think your point is very well taken. I think there are real synergies there in the long run I hope. Spivak, Baltimore: I want to congratulate you on your paper but, I am afraid things are already getting lost in translation. For example, we have diseases where we have specific therapy and I want to pick up Marfan’s syndrome as an example. And the reason I want to pick this as an example is I often see patients sent to me, and I am a hematologist, not for Marfan’s syndrome, who do have Marfan’s syndrome or marfanoid characteristics, who have seen a number of physicians and this has been totally missed. So, it’s one thing to have a specific treatment for a specific disease but physical examination seems to be a lost art today. MacRae, Boston: Again, I could not agree with you more. I think, as was mentioned at a couple of questions ago, the big problem is the disconnect between the ideal p hysical exam and that that is universally available. There is actually quite a large gap in quality across medicine. Actually, I thought about bringing this question up earlier in our discussion about ethics, but that is actually one of the biggest problems I think in all of the funding of health care. We actually, long ago, incented the elimination of cognitive input by having the pricing be flat across the entire medical profession, but that’s a digression we probably don’t want to get into right now. But the fundamental point you make is excellent. There are many diseases for which you have to actually see the right doctor. For many drugs, you have to end up in the right clinic with the right doctor before anybody will ever even think about giving them to you. That, I think, is actually a massive indictment of us as a profession. And so, my strategy, and the one that our entire group is thinking about, is really ways of trying to bring everybody up to minimal level by using technology. In a way that allows me to be as good as an examiner of a joint as Mike Weinblatt. That’s the type of thing that we have to be able to do if we are going to allow people, no matter where they enter the system, to rapidly triage to the right physician and the right therapy. But your point is well taken. If, for example, if we just measured height segments rigorously from waist to head and waist to floor and arm span, you would never have had that missed Marfan’s diagnosis problem. None of the latter measurements, and even height and weight, is probably present in the record more than 50% of the time. So, for example, if you take a photograph of somebody with your smart phone and ratiometrically look at the ratios between upper and lower segments of the body, you could actually pull out a substantial number of people who have exactly the type of skeletal abnormalities that you refer to.
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Discovering New Diseases to Accelerate Precision Medicine CALUM A. MACRAE, MD, PhD BOSTON, MASSACHUSETTS
Abstract A rate-limiting step in multiple areas of medicine is the limited number of discrete disorders that current technologies are able to identify. Most clinical disease entities are aggregates of large numbers of discrete biological processes that simply happen to share one or two common features. We have begun to translate a wide range of new technologies to the clinic in an effort to improve the resolution and the efficiency of bedside diagnostics with a view to improving drug trials, genetic studies, and the effectiveness of the clinician in a digital environment. The general trajectory for change that new technologies will bring is outlined with some specific examples of areas where such change has already begun to occur.
Redesigning medicine Medicine is undergoing more rapid change than at any time in the last 200 years. The costs of delivering care in the current model and the opportunity for new technologies or new industries to capture substantial parts of the biomedical economy have conspired to promise a revolution. Molecular insights in cancer and chronic disease have reached the clinic and are highlighting the need for improved resolution in diagnosis and management. Improved therapies are moving many inpatient cases to the outpatient setting, while the feasibility of asynchronous transactions is driving traditional outpatient care to the home. The implementation of electronic health records has accompanied these changes and promises to close at least some of the data gaps in healthcare. The advent of massive streams of structured data would open health care to rigorous analytics and predictive quantitative biology. The possibility that extant information will be continuously collated, curated, and integrated then validated, bringing formal Correspondence and reprint requests: Calum A. MacRae, MD, PhD, Brigham and Women’s Hospital and Harvard Medical School, 75 Francis Street, Boston, Massachusetts 02115, Tel: 617-732-8087, Fax: 617-732-7134, E-mail: [email protected]. Potential Conflicts of Interest: None disclosed.
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analytics to medicine, is clear, but there remain a set of substantial obstacles to this vision.
New measurements Without transformative changes in the resolution and scale of measurement in biomedicine, whether of the core biology or the transactions themselves, it will prove difficult to realize the care redesign that has been imagined. Most data within the electronic record consist of semisubjective aggregates of bedside impressions, billing codes, and a remarkably small set of measured phenotypes. Importantly, the majority of the traits captured by medical investigation consist of legacy endpoints, modern estimates of reflections from the Oslerian era or before. There is also a remarkable lack of standardization across medicine with virtually no efforts made to introduce universal standards for most areas of medicine. Ironically, genome sequencing currently represents one of the only complete and standardized datasets in modern biology, although other exceptions include the 12-lead EKG and the international normalized ratio for prothrombin time. The introduction of rigorous protocols for routine measurement would not only reduce variations in practice, but would also enable formal predictive computation, permit the early identification of disease, and lay the foundation for a truly “learning” digital health record. Real-time data trajectories and analytics could also stimulate completely different levels of precision in medicine, such as reimbursement based on evidence of efficacy in the individual patient. Traditional binary phenotypes, many rooted in 18th-century observations, must be replaced by quantitative metrics of the underlying physiologic and cell biologic traits. Standardized protocols for data collection, a feature of randomized controlled trials for decades, must be implemented in clinical practice. Innovation along these lines, and at the requisite scale, implies a need for new data display and data collection infrastructure and the ability of providers to integrate, in the clinic or at the bedside, the massive amounts of data accumulating in health care. Emerging technology must permit such bidirectional data flow without distracting and without onerous data entry, and without the need to duplicate costly informatics infrastructure for research.
New culture Not only are the mechanics of medicine in flux, the sociology of the caring professions is also undergoing remarkable change. Traditional
BK-ACC-ACCA_2017-170020.indb 84
6/2/2017 9:31:49 AM
DISCOVERING NEW DISEASES
85
clinical care or medical research teams have been built around the individual clinician-patient relationship or individual investigator, respectively, but the “teams of the future” will be created around very different architectures. A major challenge will be to preserve the core elements of the personal therapeutic relationship, while creating venues where new teams and new partnerships can evolve. For example, technology companies bringing new wearable sensors to market are collaborating with large pharmaceutical companies who need to segment clinical trial cohorts. Traditional payers are developing relationships with “big data” companies to try to understand the health of their customer base, although in many instances even the best current datasets are not big enough or the associated reference data are not robust enough to do so meaningfully. Surgeons and interventionists are conspiring to create less invasive ways to treat valvular heart disease with the eventual goal of eliminating conventional valvular surgery itself. Such a drive to make current approaches obsolete is a mantra in many innovative industries, yet the traditional rituals and regulatory constraints of modern medicine have slowed dramatic changes in our field. Nevertheless, fundamental rationalizing forces that have successfully remodeled other monopolies from the travel industry to the legal profession are now coming to bear on medical practice. By defining more clearly those traditions in medicine which are truly valuable, we will build systems that can reinforce and enrich these qualities while still allowing creativity and change to flourish. The natural history of information technology has been to broaden access and, in turn, to globalize previously local endeavors. While the need for emergency physiologic support will retain local infrastructure in many areas of medicine, the trend toward globalization will affect everything that physicians do. Management algorithms for basic medical decision-making will likely move to the individual patient, while stepwise improvements in information flow and simple convenience will begin to bypass traditional venues of medical care for all but catastrophic events. Many patients already perceive the medical establishment to be part of the problem, and our failures to deal with acknowledged issues such as heterogeneity of care delivery, lack of transparency, and chronic overstatement in research do little to mitigate this perception. That informed individuals are becoming more engaged in areas that previously were the province of the professional presents an immense opportunity, but also represents a substantial threat to the monopolies of old. In an era where everyone will have the same information, traditional medicine will have to consider where it truly adds value, and reward systems will need to be built around
BK-ACC-ACCA_2017-170020.indb 85
6/2/2017 9:31:49 AM
86
CALUM A. MACRAE
that value. The old order dependence on cross-subsidization between specialties is not likely to be sustainable, and the importance of cognitive input in the practice of medicine will have to be recognized where it is required.
Re-educating our profession To imagine even a fraction of this future becoming a reality without changing the culture of medicine is not easy, yet it is difficult to imagine much of this not happening due to the external pressures outlined above. While as a result of deeply vested interests biomedicine is one of the last sectors of our lives to yield to such transformation, medicine also has a remarkable record of sustained and innovative change. To ensure that the biomedical professions can participate fully, medical education must undergo substantial transformation. The best and the brightest must be attracted back to medicine. Q uantitative skills systematically under-represented in medical schools must be re-emphasized and reinforced. It will be important to rethink how we differentiate as individual professionals acquiring new skills and reimagining adaptable teams of clinicians, translational investigators, and basic scientists. Retaining the best elements of the current educational framework while teaching physicians, scientists, and p hysician-scientists how to manage an exponentially growing knowledge base will require new tools and new workflows. The tensions inherent in these challenges have already been laid bare in recent debates on maintenance of certification. Here, too, technology will play an important role, as it becomes feasible to measure not just activity but quality of care at the level of the individual patient.
The new paradigm is a natural extension of prior effortS Different parts of medicine will change at different rates. Cardiology has been at the forefront of many of the major movements within biomedicine, including wellness, prevention, randomized controlled trials, guidelines, and scoring systems. There is a long history of engineering and in silico modeling in cardiovascular science, and the implantation and management of devices is already a core function of our specialty. As genomics, technology, big data, and other innovations are applied increasingly to common complex disease, cardiovascular scientists and
BK-ACC-ACCA_2017-170020.indb 86
6/2/2017 9:31:49 AM
DISCOVERING NEW DISEASES
87
clinicians will likely be at the leading edge as the pressures to redesign clinical care become more intense.
Preserving the core As technological transformation begins to affect the clinical data collection infrastructure, so there are some direct implications for the physician-patient interaction. Recent trends toward data entry dominating the clinical encounter will be reversed and the opportunity to build truly therapeutic relationships will grow again. The devolution of non-professional services to the patient level, supported by technological advance, will allow physicians to re-professionalize and focus their efforts on the components of biomedicine that currently escape algorithmic solutions. At its core, the transformation of clinical measurement that is currently underway will herald a more holistic assessment of disease, reduce the administrative burden of the modern clinical encounter, and with these changes drive a return to traditional clinical encounters.
DISCUSSION Calkins, Baltimore: Enjoyed your talk. You’re in a unique position as a geneticist, and head of cardiology at the Brigham. I’m hoping you will make a lot of progress. Have you focused on precision medicine? You started your term with a concept of precision medicine. That sort of concept which has become extremely popular, and you hear about it everywhere. But practically, as a cardiologist, what does it mean to you or your division/department? Help us with that term and what you are doing at the Brigham in terms of bringing precision medicine to reality. MacRae, Boston: Hugh, thank you. An excellent question. I am reminded of something that Garret Fitzgerald once told me, which was that precision medicine was the future of medicine and always would be. I think the key thing about precision medicine is that it is what we have always done, and I think the only thing that’s changing is the resolution at which we are precise. I like to actually think about it almost as mechanistic medicine rather than precision medicine. I think what we are trying to do is get beyond the general descriptors that we have used for so many decades and get at things that actually discriminate what’s really going on in the patient. And I think the sad thing as I’ve said is that while we have done quite a lot of that in the lab, we have failed to connect it very directly with the patient so that often people will end up having mechanistically distinct disorders that are being managed in a completely different way and just simply because they happen to share a common superficial phenotype. The one other area that I think is driving precision is actually the cost of doing clinical trials. Fundamentally, what we’ve done is we’ve reached the point where the size of trials that we need, in order to see incremental effects, are no longer affordable by society. So, that’s one of the things that actually drove me away from using the term precision though I am
BK-ACC-ACCA_2017-170020.indb 87
6/2/2017 9:31:49 AM
88
CALUM A. MACRAE
not disparaging it in any way; I am just saying that I think it’s part of everything we’ve always done. We should try to tailor the therapy to the patient. But what we really need to do is begin to be able to match the drug and the patient mechanistically. And the main driver for that is reducing the size of clinical trials which I actually think is a healthy way of moving forward. We recently took a drug for heart failure through registration, as you know, in collaboration with your colleague Dan Judge with 12 patients. And the only reason we were able to do that is because we had a mechanistically specific subset of disease. I believe thinking about precision medicine as a way to actually change the paradigm for how you get drugs into the clinic is one very valuable approach. But one other thing I will say about precision that I think is important is that disease stratification without new drugs is irrelevant. So, we can stratify until we are blue in the face but if we don’t actually develop or identify new ways of making new drugs, we are going to be in serious trouble because at the moment it is something like 15 to 20 years and about $1.5 billion dollars per drug. Unless we actually find the discrete way of developing drugs — we’re really going to be in a bind. With lots of new diseases but no way of actually ever treating them. Bodenheimer, New York City: Well, thank you very much for your provocative talk. You know I would feel personally sad if we were presaging the death of the physical exam. And I would just like your comments about can we look at the application on some of this precise technology and utilize this but then develop methods of s trengthening observation with physical exams so that we can deploy this throughout the world. We may be living in very rarefied academic centers but much health care is delivered throughout the world without access to such precise technology. MacRae, Boston: I could not agree with you more. I think two things: first of all, I hope I made it clear that not in any way would I devalue the physical exam. I actually think there are huge elements of the healing interaction that are only conveyed in the physical exam. I would be a very strong proponent of this. What I think is important is that we complement the physical exam and that we move it from being semi-subjective to being more objective, and I think there are rational ways of doing that quite effectively. I think many of the themes that I brought out are actually importantly related to what you just said. I think scalability is key. In fact, one of the most interesting things about a lot of these assays is that we have the good fortune of having faculty members that work in Africa, one of whom who has helped manage preventative health care across South Africa. I believe that we will find it much easier to implement some of these technologies on a smart phone, or using a simple bedside device in African context, where there are no vested interests and there are no limits on how quickly people have to move through the clinic, compared with Brigham and Women’s Hospital. So, I am convinced that there is going to be a large amount of this type of translation and I could not agree with you more that we have to do it in a way that preserves all of the essence of the physical exam which I think is a vital part of everything that we all stand for. Sacher, Cincinnati: Not to undermine the physical exam, but of course there is so much interest in the new advances in computing science such as the mining of big data. So, it seems to me that there may be something of applicability of what you are doing and perhaps sharing information with big data companies. MacRae, Boston: I could not agree more, and you probably saw we do quite a lot of work with technology companies like IBM, Microsoft, and with Google in exactly this space. One of the things that I think is actually quite interesting, though, is that many large efforts in this area already have spent a lot of time without clearly identifying signal amongst the noise. One of our strategies, and one of the reasons we got into this area, is to focus on informed ways to accentuate the signal, in the key areas that we are
BK-ACC-ACCA_2017-170020.indb 88
6/2/2017 9:31:49 AM
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actually interested in for medical therapy. But I think your point is very well taken. I think there are real synergies there in the long run I hope. Spivak, Baltimore: I want to congratulate you on your paper but, I am afraid things are already getting lost in translation. For example, we have diseases where we have specific therapy and I want to pick up Marfan’s syndrome as an example. And the reason I want to pick this as an example is I often see patients sent to me, and I am a hematologist, not for Marfan’s syndrome, who do have Marfan’s syndrome or marfanoid characteristics, who have seen a number of physicians and this has been totally missed. So, it’s one thing to have a specific treatment for a specific disease but physical examination seems to be a lost art today. MacRae, Boston: Again, I could not agree with you more. I think, as was mentioned at a couple of questions ago, the big problem is the disconnect between the ideal p hysical exam and that that is universally available. There is actually quite a large gap in quality across medicine. Actually, I thought about bringing this question up earlier in our discussion about ethics, but that is actually one of the biggest problems I think in all of the funding of health care. We actually, long ago, incented the elimination of cognitive input by having the pricing be flat across the entire medical profession, but that’s a digression we probably don’t want to get into right now. But the fundamental point you make is excellent. There are many diseases for which you have to actually see the right doctor. For many drugs, you have to end up in the right clinic with the right doctor before anybody will ever even think about giving them to you. That, I think, is actually a massive indictment of us as a profession. And so, my strategy, and the one that our entire group is thinking about, is really ways of trying to bring everybody up to minimal level by using technology. In a way that allows me to be as good as an examiner of a joint as Mike Weinblatt. That’s the type of thing that we have to be able to do if we are going to allow people, no matter where they enter the system, to rapidly triage to the right physician and the right therapy. But your point is well taken. If, for example, if we just measured height segments rigorously from waist to head and waist to floor and arm span, you would never have had that missed Marfan’s diagnosis problem. None of the latter measurements, and even height and weight, is probably present in the record more than 50% of the time. So, for example, if you take a photograph of somebody with your smart phone and ratiometrically look at the ratios between upper and lower segments of the body, you could actually pull out a substantial number of people who have exactly the type of skeletal abnormalities that you refer to.
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