“Do no harm” is NOT Enough

computer-1149148_1280By Beth Russell

“If it ain’t broke, don’t fix it, right,” my granddad used to say, right before he would wink at me, chuckle, and say “let’s see if we can figure out how to make it better.” This type of ingenuity is at the root of American innovation, invention, and process evolution. Observation, experimentation, and a national drive for optimization are part of our culture. As we have moved from the 20th century into the 21st, there has been a fundamental shift from “one size fits all” solutions, towards more personalized solutions.

The Precision Medicine Initiative is one of the great goals of our time. However, most of our medical treatment is still geared toward the treatment that will usually work, rather than the treatment that is the best for the individual patient. What would the world look like if we could change that in years rather than decades? What if we could do it cheaply, and easily, with information that already exists?

We can. To start the process, we need only to do one thing – to share. Buried within our medical records, our genetics, and our health data, is the information that we need to make our medical treatments better. Our diversity in population, hospital, and practitioner policies, and personal health decisions compose an enormous health data set. If we are willing to share our data with researchers and to insist that the insurers, hospitals, and practitioners make sure that the data is interoperable, we will be well on our way.

We often have widely held medical practices that are not actually supported by scientific data. This is illustrated by a recent decision by the Department of Agriculture and the Department of Health and Human Services to remove daily flossing from their guidelines. Apparently, there was no actual scientific data behind it. Such practices are often low-risk procedures or treatments that do not warrant the expense of a clinical trial. Many of these will probably turn out to be accurate for most people, but not necessarily for everyone. I for one don’t plan to stop flossing anytime soon.

These sorts of medical practices are typically adopted based upon observation and consensus. This approach is cheap but relies on practitioners detecting a pattern of good or bad results, is highly subject to human bias, and is much more geared towards safety than efficacy. There will always be room for common sense and human observation in the medical process but they will miss both small, and rare effects.

For over a century the arrow has been shifting away from simple observation towards data-based decision making. Large observational studies like the Framingham Heart Study and the Nurse’s Health Study have had outsize impacts on medical practices but they are still too small. Only with many observations from numerous patients can we detect the variations in efficacy and safety that are needed for precision medicine.

Today, clinical trials are the gold standard for medical treatments. These experiments are expensive, time consuming, and often suffer from low subject numbers and a lack of diversity. They also can run into ethical issues, especially with vulnerable populations. Even when the results of clinical trials are excellent, their results aren’t always adopted initially by practitioners. Medicine tends to be slow to adopt change. Data sharing will allow scientific analysis to extend beyond the length of time and number of subjects that are used in any “trial” and will allow us to better evaluate drugs and treatment after they go to market, not just before they are approved.

Data sharing is also important for areas of medicine for which traditional clinical trials are difficult or impossible to run. One of these areas is surgery. Most surgeries are not subjected to clinical trials and there is great variation in the methods for even relatively common surgeries from hospital to hospital. How does a patient decide where to get a life-saving surgery? Recommendations from friends and family are the number one method for choosing a doctor. There is no place to look to find out whose favorite method is the best one overall, nor the best for the individual patient. This needs to change. Sharing our medical data will make this possible.

Medical practice is poised for a revolution. We are beginning to move from treating the symptoms to treating the person. This can only happen if enough of us are willing to share. So let’s practice our earliest kindergarten lesson already.

What Personalized Medicine is to Me

Charles Mueller

I hate our current medical system and I hate that industry runs it. I hate it because the medical field and medical industry all abide by a central dogma that “the answer to failures of a biological system (the human body) is a pill.” No. The answer to biological system failures is a biological system solution. It is learning how to manipulate your entire biological system and not just the one part you are concerned about. It is about learning to use the body’s systems to fix itself.

This is our fundamental problem with understanding disease. We subscribe to the belief that a diseased liver is an isolated problem and all you need to focus on is the liver. We forget the body is connected and we do not even explore solutions that might involve unorthodox approaches that manipulate entire systems rather than organs. We need a new dogma in medicine and the idea of personalized medicine might be just what we need.

There is a lot of talk right now about personalized (or precision) medicine after the President revealed his Precision Medicine Initiative. I think this initiative fails to recognize what personalized medicine really is and what is needed to make it real.

To me, personalized medicine is understanding how all the cells of the body communicate and respond to changes in the environment. The question though is how do you figure this out?

The first step is to identify the key metrics you need to understand the connectivity of the body’s systems. Once you figure this out, the next step is to monitor these in groups of people. Why groups of people? We cannot perform all of the controlled human experiments that would help us understand the body as a system because they would be morally and ethically wrong. So instead, it is about acknowledging that everyone makes choices that cause changes in their body. Your life is one giant experiment. Many people are probably similar to you and make similar choices. Many are similar at the biological level and make different choices. People are running around experimenting on themselves all of the time and nobody is asking them to come in so we can take some measurements and figure out what they are doing to themselves. This is the key. Let people be themselves and use Big Data analytics on the massive amount of data that is created from monitoring them. Monitor what the best available science tells us is important, group people into categories based on their metrics and life choices, and then figure out how different choices within a group result in health endpoints.

This is how collective monitoring results in personalized medicine. With such an approach, you will begin to really understand the system level of the body and how it responds to different life choices and the mechanisms for how those life choices alter human health.  Then it is just a matter of looking at you and what you have done to make highly informed predictions about the future of your health. You cannot just study one person in detail for the same reason that you cannot study one bacterial cell and say now you know everything that that strain does.

The President’s Precision Medicine Initiative plays into the existing dogma that I loathe. It fails to see the forest for the trees. It is primed to use Big Data analytics on personal data, like genetics, to identify which pill works best for you. There is reason they chose the word precision rather than personal. “Personal” would imply a new dogma, one that really focused on you and not one that focused on the precise pill for you.