Follow The (Clinical Trials) Money

A New York Times article, Do Clinical Trials Work?, describes how modern clinical trials are broken since drugs for most of the complicated modern diseases only work for X percent of the population.

It’s widely understood that many drugs only work for people with certain genetic traits and comorbidities. The challenge is in determining which traits and conditions affect outcomes while controlling for a range of factors, including: age, sex, medical history, disease, stage of the disease, and confounding with other diseases, to name a few.

The clinical trials business is undergoing serious changes. As the NYT article suggests, trials need to be smaller and targeted to patients with more narrowly defined inclusion / exclusion criteria. The issue is that existing methodologies driven by mass-media marketing for identifying and recruiting patients for more specific criteria aren’t effective, hence all the trial delays.

Simply taking existing trials and breaking them up into smaller trials doesn’t sound particularly difficult. Why hasn’t it been done? There’s always a single answer to that universal question: follow the money.

Recruiting patients into trials is already an extremely expensive proposition. There are cancer studies in which the cost of finding and recruiting each patient exceeds $50,000. Mass media marketing is expensive. Additionally, 80 percent of trials are delayed, and the average delay is almost five months. These financial and time costs kill people who aren’t receiving market-approved treatments as cheaply or as quickly as they otherwise could have.

Marketing larger numbers of smaller trials and recruiting patients into them is cost prohibitively expensive. The more trials, the more marketing dollars required. The challenge is not in trial design, but the ability to find the right patients and recruit them into the right trials.

A handful of startups and well-established vendors are trying to solve the patient recruitment problem.

CenterWatch is an established company that maintains a database of clinical trials and allows patients to use powerful search tools to find trials that they’re interested in. Once a patient finds a trial that they are interested in, they provide the patient with the contact information and additional details for the trial. The service is straightforward and the filtering tools are robust, but overall it feels very Web 1.0 to me. It requires a lot of clicking and navigation. They could be ten times more successful if they could automate and simplify the user experience.

Emerging Med is another industry veteran that is focused on cancer trials. Emerging Med claims to have guided 170,000 patients through a search for clinical trials over the last 13 years. Their service is remarkably similar to CenterWatch’s. The presence of two companies that do almost the same thing clearly validates the market and indicates that it’s sufficiently large.

ePatientFinder (ePF) works with pharmaceuticals, device manufacturers, and CROs (contract research organizations) to match trials with a nationwide network of referring physicians. Working with EHR vendors, ePF runs analytics to de-identify patients who meet trial inclusion / exclusion criteria. This partnership network enables more targeted searches and allows ePF to compensate its EHR vendor partners, many of which are struggling. ePF is trying to invert the entire patient recruitment process. Their model is radically different from the traditional industry practices. Historically, patients have been recruited through expensive mass media marketing campaigns. ePF finds patients cost effectively by working with physicians to accurately target patients based on EHR data. They may have found a great application of analytics technologies, which have been overhyped for years (I’m guilty!).

TrialReach has compiled a database of clinical trials and uses a survey tool to help filter patients for these trials. They are based in the UK and are focused on European trials. TrialReach posts ads online to direct patients to TrialReach’s website, where patients are asked to answer a few questions. If the patient passes the survey, their information is sent to the CRO. TrialReach’s secret sauce is its placement of advertisements through the use of proprietary tracking algorithms and a network of ad distribution partners.

I’m actually a bit surprised there aren’t more companies actively pursuing the clinical trials space. The analytics space is overhyped, overfunded, and overcrowded, and most of the analytics companies aren’t making the kind of money they told their investors they would (similar to the startup EHR market). There have been a few breakouts though, such as Ayasdi, that are doing well.

The biggest flaw in the NYT article was its title. It paints a reasonably accurate picture of the current state of clinical trials and begins discussing some of the more advanced concepts such as personalized medicine, comorbidities, etc. It fell short of explaining why trials are structured the way they are and most certainly didn’t investigate existing or up and coming commercial solutions to the problems they pointed out. It’s always easier to pull down than push up. Unfortunately, if you follow the money, you’ll quickly realize that the NYT needs eyeballs to feed itself, hence the sensationalist title.


Kyle Samani is a healthcare technology entrepreneur who is passionate about healthcare and technology startups.

  • Robert D. Lafsky, M.D.

    “Simply taking existing trials and breaking them up into smaller trials doesn’t sound particularly difficult. Why hasn’t it been done?” There’s still something called statistical significance you have to produce. Theoretically with perfect biological knowledge you could prove a treatment with one patient, but the system is too complex for perfect knowledge. So you’re still reaching conclusions based on statistical outcomes, for which you need groups of a big enough size. Of course if technology can make the groups bigger, more power to it.

  • kylesamani

    Dr Lafsky

    You’re point is valid, but I think the general solution of more effectively recruiting patients solves the point you brought up as well. If we can improve efficacy of finding patients 5 or 10x, then A LOT of problems will be solved, including sizes for statistical significance.

↑ Back to top

Founding Sponsors

Platinum Sponsors