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Small population studies can revolutionize clinical trials

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May 12, 2015

In today’s environment of rising health care costs, more people are calling for improved clinical efficacy for prescription drugs for both routine and serious medical conditions. Take a routine condition, such as heartburn: the Medicare Part D Prescription Drug Program’s highest expenditure drug, Nexium ($2.5 billion in annual claims), is effective in just 5% of its prescription population — and many other popular drugs do not fare much better. Meanwhile, most cancer drugs extend mean survival in just 20-30% of late-stage patients by no more than 2-3 weeks — yet they cost tens of thousands of dollars per injection. We are paying a lot for drugs that are no better than sugar capsules.

One emerging idea to address this problem is to adopt more N-of-1 clinical trials, which focus on a single patient to establish a drug’s efficacy. This is a dramatically different model compared to the current standard of large population studies. Today, more researchers are acknowledging the shortcomings of large population studies that often fail to account for variability between patients. This failure is largely responsible for many drugs’ ineffectiveness.

N-of-1 trials might be the most direct approach to address the variability issue. In these trials, a drug is tested on the patient to identify specific characteristics, such as the correct dosage, genetic profile requirements for the drug to be effective, possible causes of side effects, and the thresholds of disease onset. Then, the data collected from these single-patient trials can be analyzed together to identify new correlations within patient population as to who may benefit from the drug, provided that they show similar genetic and physiological profiles.

The idea of N-of-1 trials is potentially disruptive, because they are potentially more affordable, accessible, and effective: N-of-1 trials could make drugs more affordable by significantly reducing wasteful drug use among patients lacking the right profile for the drug. They could also reduce cost of drug development by eliminating some of the need for large-scale population studies. And certainly, the efficacy of drugs will improve as the trial data improve target patient selection. However, the current description of N-of-1 trials falls short on explaining how to improve patient targeting and efficacy, while increasing access. While the model implies that we need to narrow the usage of many drugs, what steps do we need to take to broaden access?

In a previous post, we shared the idea of a “bench-to-bedside-to-bench” (B2B2B) model for clinical research. N-of-1 trials can improve our ability to identify patients who will benefit from a particular drug, and they can also increase access by helping us design more broadly effective classes of drugs (new drug variants or combinations) — but only if we commit to using the data gathered from small trials to improve our understanding of disease pathways and mechanisms.

For many infectious diseases, we can create a detailed map of how a particular antigen can lead the disease progression in a healthy host. But, for systemic diseases, many of which are chronic, our mapping capabilities must improve. Today, despite an advanced understanding of many disease pathways, our understanding of other questions — what causes chronic diseases? how do chronic diseases progress over time? how do chronic diseases affect systemic interdependencies? — remains poor. In order to conquer growing epidemics, such as type-2 diabetes, neurological disorders, and auto-immune diseases, we not only need better patient targeting tools but also better disease models. This is the final piece that will unlock access and efficacy.

The current system of clinical trials is simply not cutting it. Therefore, we welcome the growing voices of innovative researchers seeking to break away from tradition to test new approaches that better address the health issues of the 21st century.

Spencer Nam

Spencer researches disruptive innovation in the healthcare industry. He has over 15 years of professional experience working with U.S. and international healthcare enterprises, most recently as an equity research analyst covering medical technology companies.