Suppose I reported that billions of dollars will be spent on life-extension research next year and that soon that number will reach tens of billions? The first reaction of aging-science researchers would be “no way.” They would point to the pittance allocated to longevity research by the NIH. Yet, I am about to assert here that investing in life-extension is going big time. This is the first of a series of related blog posts on an emerging paradigm in medicine and its implications for longevity. The series is inspired by what I learned at the Bio-IT World Conference & Expo last week from listening to many speakers and from wandering through the exhibit floor and talking with many people.
Aging science vs. life-extension engineering
I drew an important distinction in the blog entry What are aging, life-extension and anti-aging? I pointed out that there are a lot of life extension approaches, ones that increase the life expectancy of a defined population, that are of an engineering or social nature. These approaches may or may not have anything to do with postponing aging from a biochemical viewpoint. Example approaches that have worked are better sanitation systems, clearing out water and air pollution, eradicating parasite populations, systematic inoculation programs, building safer highways, and implementing speed limits and seatbelt laws. Indeed, the fact that the average American lives twice as long as our predecessors did 150 years ago has mostly to do with these kinds of life extension measures. While the results of these engineering and social approaches have been life extension, they are invariably thought of in other terms such as “public health,” “cleaner environment,” and “food safety.” A powerful new engineering approach in medicine with life extension consequences is gearing up right now.
In contrast, in my treatise ANTI-AGING FIREWALLS THE SCIENCE AND TECHNOLOGY OF LONGEVITY treatise and in this blog I have largely come at aging through the lenses of aging science, identifying 14 of the leading theories of what causes aging and another 7 candidate theories of aging and then writing about developments relating to them. So I have dealt with topics relating to aging theories ranging from oxidative damage and chronic inflammation at the “classical” end of the spectrum to telomere shortening and damage and increasing mTOR signaling at the “new science” end of the spectrum. I will doubtlessly continue to do the same.
What I am going to discuss in this particular series of blog entries is a different engineering and social approach to life extension that, in my opinion at least, will also end up telling us many of the things we need to know about the science of aging.
Personalized Predictive Preventative Participatory Medicine (PPPPM)
The new approach is directed to health and medicine in the coming decades, although I believe it will have major implications for life extension and perhaps even for slowing biological aging. I will call it Personalized Predictive Preventative Participatory Medicine (PPPPM). The dimensions of PPPPM are only now becoming clear and I will only generally characterize it here, saving detailed characterizations and discussions of examples for subsequent blog entries.
In a nutshell, the essence of PPPPM is:
1. The objective of PPPPM is not so much to cure diseases as it is to detect and predict disease susceptibilities before a disease starts or at very early stages of disease progression and initiate personalized interventions to prevent the progression of the disease before it becomes symptomatic or does damage.
2. PPPPM is participatory in the sense that the collaborative participation of large numbers of health research institutions and care agencies is involved in doing the research and creating the infrastructure to make it workable. It involves a tight and continuing linkup loop of researchers, practitioners, patients and healthy people who want to stay healthy.
3. The predictions of PPPPM are based on the identification of sets of biomarkers that are predictive of disease susceptibilities and stages of disease progression for particular diseases. The biomarkers can consist of known gene mutations, SNPs, copy number variations and the like, and other “omics” markers (proteomic, transcriptomic, metabolomic, epigenomic etc.) as well as the results of all kinds of existing clinical tests and clinical data.
4. The biomarkers will be arrived at through massive correlation analyses and pattern matching between public data bases of the kinds of data involved and association studies of many different kinds. See the blog entry Genome-wide association studies for examples. The biomarkers will be continuously refined through feedback from personal histories, of course with numerous layers of personal privacy protection.
5. Identifying PPPM biomarkers will proceed one disease at a time, the challenges including creation of massive public data bases of “omics” information and performing multivariate association studies. It is a task that requires mobilization of incredible networked computer power and human analytics.
6. Identifications of disease-prevention interventions including drug candidates will proceed along the same lines using the same kinds of tools and analytics, where interventions will be determined on the basis of the known biomarker patterns as well as individual patient or well-persons’ patterns of “omic” markers.
7. Fully implementing PPPM will require genetic, genomic and other “omic” profiling on the part of increasing numbers of people, something that should become commonplace in 10-15 years.
Here is a simplified example of how the approach could work. Say a healthy person discovers early in life that he has a susceptibility to Alzheimer’s disease. For example, a current-generation genetic test shows he possesses the APOE4 gene allele, a predictor of late-onset AD. Starting at around age 50, he would periodically have his other Alzheimer’s-predictive biomarkers checked. These should show early signs of the actual disease before any dementia is detected. This might, for example, require a combination of epigenomic scans and lab tests. If and when very-early disease signs are detected, strong preventative measures are immediately initiated. These might consist of drugs, supplements or lifestyle changes.
The basic concept is that it should be a lot easier to stop a disease in its very early stages from progressing or reverse its progress than waiting for symptoms to show up and damage is done, and then trying to “cure” it. All too many diseases like Alzheimer’s have shown themselves to be remarkably resistant to being cured because by the time they are symptomatic, it is too late to stop them.
PPPPM may sound like a grand concept for the future, and it is. However it is already being actively pursued for several disease conditions by large research consortia. Many large relevant databases already exist and many important biomarkers are already known. One of several existing examples of PPPPM is the cancer biomedical informatics grid, “a virtual network of interconnected data, individuals and individuals that redefines how research is conducted, care is provided, and patients/participants interact with the biomedical research enterprise.”
The current energy and vitality of PPPPM follows from the fact that it is not just a research approach but also heavily involves finance, entrepreneurship and industry participation. Large pharmaceutical companies who badly need new drug candidates to replace those going off-patent are using the PPPPM approach to discover them. A number of large government agencies like the National Cancer Institute are involved. And dozens of new companies and players are lining up to do the information processing and collaborative networking required. Players with names like Microsoft and IBM are involved. There is the smell of billions of dollars involved. But I will leave details and descriptions of concrete examples to subsequent blog entries.
And what happens when diseases of aging are effectively postponed? It is a no-brainer that on the average people live longer, that is life extension. And I have no doubt that as effective PPPPM approaches gear up and more and more biomarker-disease correlations and prevention-treatment disease correlation are learned, we will be learning more and more about how to postpone biological aging too.
Just as a post-script, the basic principles of computer science were already well-established in 1950, but computers were doing very little to help people then. It took years of commercial activities, engineering and technology innovations, inventions and new approaches in manufacturing, software and marketing to get where we are now where computers empower all aspects of our lives. This was a social-engineering-industrial-marketing feedback process involving institutions, government (for early Internet development), businesses, entrepreneurial activities and intense involvement of business of all kinds and now, everybody. It was tumultuous with many failures and incredible successes, and continues to be. The same kind of process has already started related to health. We are already deeply engaged in a similar tumultuous process of life extension and it will be a wonderful crazy ride. Real practical life extension is no fantasy.