Hey, You Got Your Chocolate in my Lipitor!

It's an idea that can only be described as brilliantly obvious: create a chocolate formulation of your pharmaceutical.

The original idea, as developed by England-based Lycotec, was to develop a mechanism that could more effectively transport drugs to the liver (and they appear to have produced some intriguing proof-of-concept results in increasing the potency of statins).

However, it's not much of a stretch to believe that patients might be more compliant if their daily medications became noticeably more delicious -- especially in chronic illnesses with few or no symptoms where adherence is considered a problem (such as hypertension).

Of course, if it works there will be safety issues to work through.  Child-proofing becomes a much more direct concern, for one.  But those issues seem addressable, and the potential benefits could be tremendous.

Sadly, the Lycotec website makes no mention of peanut butter.  Let's hope they're on it.

Changing the Rules, Ever So Slightly, For Rare Diseases

At the end of last year, US Reps Cliff Stearns (R-FL) and Ed Towns (D-NY) introduced the Unlocking Lifesaving Treatments for Rare-Diseases Act (ULTRA for short). Despite what its bold name might imply (and unlike many recent congressional healthcare bills), ULTRA is actually a modest and carefully-though-out piece of legislation.

The main thrust of ULTRA is to enable developers of drugs for rare diseases to take advantage of the FDA’s existing Accelerated Approval pathway. Accelerated Approval reduces the initial burden of proof for manufacturers to bring a drug to market by conducting smaller clinical trials that measure a drug’s efficacy against “surrogate” endpoints – that is, endpoints that do not directly measure the disease, but rather other factors that are associated with the disease. This can greatly reduce the time and cost of clinical trials.

To qualify for Accelerated Approval, however, trials for a new drug needs to meet two conditions:

• The drug must be studied for treatment of a serious disease, with unmet medical need


• There must be clinical evidence that improving the surrogate endpoint is reasonably likely to predict real benefit for those with the disease

ULTRA does not change the first criterion, only the second. For rare diseases, there is often not robust clinical evidence to support surrogate endpoints, so the bill alters the language slightly to permit the FDA to accept “reasonable scientific data that support and qualify the relevance of the surrogate endpoint”. In essence, the burden to prove the validity of the surrogate has been relaxed, permitting their use in pivotal trials, and using a surrogate may reduce the number of patients needed for a trial by as much as 50-75%.

Accelerated Approval still requires the drug manufacturer to complete full trials to more firmly establish the drug’s efficacy – it just allows the drug to be available on the market while those full trials are being conducted. ULTRA does not change this requirement for drugs of rare diseases, so in the end it is not lowering the standard for these drugs at all.

Obviously, anything can happen to a bill as it wends its way through congress. But as it is currently written, ULTRA is a highly rational, well-targeted adjustment to current law that should quickly show benefits for patients with rare diseases, and deserves quick action and passage.

(Further reading: the FDA Law Blog has an excellent review of the proposed act.)

Public Reporting of Patient Recruitment?

A few years back, I was working with a small biotech companies as they were ramping up to begin their first-ever pivotal trial. One of the team leads had just produced a timeline for enrollment in the trial, which was being circulated for feedback. Seeing as they had never conducted a trial of this size before, I was curious about how he had arrived at his estimate. My bigger clients had data from prior trials (both their own and their CRO’s) to use, but as far as I could tell, this client had absolutely nothing.

He proudly shared with me the secret of his methodology: he had looked up some comparable studies on ClinicalTrials.gov, counted the number of listed sites, and then compared that to the sample size and start/end dates to arrive at an enrollment rate for each study. He’d then used the average of all those rates to determine how long his study would take to complete.

If you’ve ever used ClinicalTrials.gov in your work, you can immediately determine the multiple, fatal flaws in that line of reasoning. The data simply doesn’t work like that. And to be fair, it wasn’t designed to work like that: the registry is intended to provide public access to what research is being done, not provide competitive intelligence on patient recruitment.

I’m therefore sympathetic, but skeptical, of a recent article in PLoS Medicine, Disclosure of Investigators' Recruitment Performance in Multicenter Clinical Trials: A Further Step for Research Transparency, that proposes to make reporting of enrollment a mandatory part of the trial registry. The authors would like to see not only actual randomized patients for each principal investigator, but also how that compares to their “recruitment target”.

The entire article is thought-provoking and worth a read. The authors’ main arguments in favor of mandatory recruitment reporting can be boiled down to:

• Recruitment is many trials is poor, and public disclosure of recruitment performance will improve it
• Sponsors, patient groups, and other stakeholders will be interested in the information
• The data “could prompt queries” from other investigators

The first point is certainly the most compelling – improving enrollment in trials is at or near the top of everyone’s priority list – but the least supported by evidence. It is not clear to me that public scrutiny will lead to faster enrollment, and in fact in many cases it could quite conceivably lead to good investigators opting to not conduct a trial if they felt they risked being listed as “underperforming”. After all, there are many factors that will influence the total number of randomized patients at each site, and many of these are not under the PI’s control.

The other two points are true, in their way, but mandating that currently-proprietary information be given away to all competitors will certainly be resisted by industry. There are oceans of data that would be of interest to competitors, patient groups, and other investigators – that simply cannot be enough to justify mandating full public release.

Image: Philip Johnson's Glass House from Staib via Wikimedia Commons.