Many individuals donate billions of dollars to medical research via foundations and fellowships, without being directly involved themselves with the research initiatives. These donors are successful and intelligent individuals often possessing remarkable management and organizational skills. The research foundations are typically set up to address a broad population-based diseases (i.e. breast cancer, Alzheimers disease, Parkinsons disease, etc.) and usually do not have a finely focused and single patient-oriented goal. The typical medical research foundation consists of a team of experts who are paid to supervise research activities and to provide grants to scientists who are usually already partially funded by the government, academia or industry.The Idea
There are, however, some individuals who, besides donating to basic and clinical research, would also like to solve personal medical problems and participate to some extent in the research effort. These individuals often have excellent project management and organizational skills, but of course lack the scientific and medical background to develop their own personal medical research initiative. In contrast, scientists and medical doctors working at the The Foundation for Holistic Medical Research (FHMR) would jump at the opportunity to apply their skills and knowledge to conduct cutting edge research and focus exclusively on individual patients, but lack funding. Personalized n-of-1 research could bridge this gap and link patients with funds and management expertise with teams of scientists and physicians who are interested in pursuing individualized goal-oriented science. The patient provides research grants, biological samples and contributes co-management expertise where appropriate. In other words, the patient participates in his or her own research process and treatment protocol from start to finish. The team of physicians and research scientists executes basic and clinical research that address the patient’s specific future needs and research interests.Background
Modern physicians face uncertainty on a daily basis over the best course of action to take for a given patient. This is owing to the fact that so many different interventions are available, all of which have varying levels of evidence to support their use but for which there is very little information regarding how to determine the best intervention for a specific patient. There is a growing acceptance that efforts to develop treatment interventions that work for every patient for the majority of common chronic conditions is exceptionally difficult, scientifically unlikely, and all too often has proved to be fruitless. This recognition has led [back] to the age-old notion that the clinical practice of medicine should acknowledge and embrace the unique characteristics of individual patients, particularly at the genetic and epigenetic levels, and seek to individualize patient care guided by “omics” data (proteomics, metabolomics, trasncriptomics, etc). This was the basic concept of medicine proposed thousands of years ago in many traditional systems of healthcare (e.g. Ayurveda, Traditional Chinese Medicine, Unani).
The renewed interest in individualized medicine has led to some very important discoveries. For example, many cancer therapeutic responses have been demonstrated to be influenced by very specific tumor genetic and epigenetic profiles, which has led to the obvious understanding that before one administers certain medicinal compounds, a patient’s tumor should be screened for the presence of specific genetic and epigenetic marks. In fact, the drug cetuximab (Erbitux®), used to treat colorectal cancer, is rendered ineffective in the presence of a specific mutation in the KRAS protein in the tumor. In response, in 2010 the US FDA relabeled this drug to indicate a need for genetic profiling before administering it. There are many other instances in which connections between the presence of genetic variations and non-cancer drug effectiveness or side-effect profiles have been made that have led to FDA relabeling, such as warfarin, carbamazepine and most recently clopidogrel (Plavix)--used to prevent re-thrombosis of coronary vessels after stenting. In the case of Plavix, carriers of a reduced-function CYP2C19 allele had significantly lower levels of the active metabolite of clopidogrel, diminished platelet inhibition, and a higher rate of major adverse cardiovascular events, including stent thrombosis. At present (2016), approximately 10% of labels for FDA-approved drugs contain pharmacogenomic or epigenomic information.
As compelling as these studies and consequent drug administration policy changes are, they do not necessarily indicate a shift towards true individualized medicine since they only reflect attempts to fractionate or stratify the larger population into smaller groups likely and un-likely to benefit from specific treatments. Hence, they do not involve a true consideration of all the nuances and characteristics individual patients may have that would indicate therapies tailored specifically to those patient characteristics. Obviously, as more insights or connections between various factors and drug responses are revealed, the more likely clinical care can be specifically directed to the unique combinations of factors that define an individual patient’s clinical presentation. Until that time, however, for many clinical conditions, a physician is faced with the dilemma of true ‘clinical approximation’ in which the best course of therapy is unknown a priori simply because the significance between individual patient characteristics, such as genetic profile, and likely response to particular therapeutic agents, have not been identified. N-of-1 medicine, which focuses on the objective determination of the optimal therapy for a single individual, is true medicine.The Foundation for Holistic Medical Research n-of-1 Medicine: From General to Particular
Randomized controlled trials (RCTs) are considered the sine qua non of applied biomedical research. The objective evaluation of the benefits and problems associated with clinical interventions, by directly comparing them with standard or sham (placebo) interventions, allows claims to be made about the ultimate effectiveness of those interventions. Although the statistical interpretation of any randomized clinical trial is arguable, the basic motivation and scientific foundation behind clinical trials are not in doubt, and few would argue that the positive results of a well-designed clinical trial could ever hinder the advancement of medical science. However, the one largely ignored issue that is of tremendous practical importance in the design and conduct of clinical trials is the generalizability of the results, especially if they suggest a novel intervention. Addressing this issue is important because it obviously impacts on wider use, dissemination and marketing of an intervention after the completion of a successful RCT. Ensuring that a trial’s design and subject enrollment facilitates applicability of the results is very complex given the tremendous heterogeneity of diseased populations. In this light, an n-of-1 trial that focus exclusively on the objective, empirically determined optimal intervention for a single patient, while not immediately generalizable, accomplishes the ultimate end point of clinical medical practice – the care of the individual patient.
In addition, clinical studies focusing on the treatment of single patients is actually more consistent with the vision of individualized or personalized medicine than stratifying patients into groups “more” or “less” likely to benefit from a specific treatment on the basis of population-level association studies. Finally, n-of-1 trials could be very efficient and less costly vehicles for motivating serious consideration about an intervention with respect to other patients, larger patient groups, or other clinical conditions. For example, it might be that patients who are found to respond best to a certain intervention share genotypic, biomarker, clinical or demographic characteristics.
The ultimate benefits of n-of-1 trials may derive from the reality that interventions of drugs, surgeries, herbs or whatever type rarely work in everyone. Just as interventions have differing effects across groups of patients stratified by certain common characteristics, it is highly likely that these interventions will show variation in efficacy between individuals, even within specific strata. There are a few studies that have examined the feasibility of n-of-1 trials from a cost perspective. As one might expect, the operational costs of n-of-1 trials are not trivial relative to standard care and knowingly putting a patient on the intervention for pre-specified periods without a favorable response is problematic from both the cost and care perspectives. However, this criticism is true of all clinical trials, and ways of mitigating this problem via adaptive and sequential designs can be implemented.
N-of-1 trials have the potential to radically change the way in which individualized medicine is pursued. Not only are the results of n-of-1 trials of immediate benefit to the patient and the treating physician, but if enough of them are pursued, patient characteristics that ultimately differentiate those that benefit from a particular intervention from those that do not can be explored, allowing for stratification of future patient groups in a way that would further benefit patient care. In conclusion, I firmly believe that there will be high net-worth individuals with personal or family medical dilemmas who would be willing to invest in an n-of-1 approach. FHMR will be able to offer the resources for all such pursuits.