Drug developers have been struggling with the placebo response for decades, as a strong placebo effect diminishes the ability to distinguish pharmacologic treatment efficacy of an experimental drug. This issue is even more pronounced when dealing with subjective endpoints and/or patient-reported outcomes– such as daily average pain intensity, brief fatigue inventory or itching intensity. To contend with this issue, scientists have devised strategies to identify potential high placebo responders (such as trial designs with placebo lead-in periods) and exclude them from randomized clinical trials. While this practice may seem to be tempting, there are significant data suggesting that this strategy is sub-optimal.

First and foremost, excluding high placebo responders limits the available patient population and makes patient recruitment slow (at best) or impossible (at worst). Data suggests that placebo response rates are very high, particularly in indications like neuropathic pain and depression, among other neuropsychiatric diseases. For example, as many as 60% of migraine patients have been reported to respond to placebo in a clinical trial setting1. Excluding placebo responders will ultimately increase both trial cost and timeline, perhaps unreasonably so considering the resource constraints within which many companies are working. Limiting the available patient populations may further be impossible in rare diseases and specific disease subpopulations, where the available patient pool is already small and recruitment difficult and time-intensive.

Second, removing high placebo responders from clinical trials may decrease the translatability of data to the general clinical population. As trial inclusion criteria becomes exceeding narrow, the extent to which the data can be extrapolated to a heterogeneous patient population is compromised. Furthermore, regulatory agencies prefer that clinical trial subjects mimic real-world patient populations as closely as possible.

1 Powers SW, Coffey CS, Chamberlin LA, Ecklund DJ, Klingner EA, Yankey JW, Korbee LL, Parker LL, Hershey AD. for the CHAMP investigators. Trial of amitriptyline, topiramate, and placebo for pediatric migraine. N Engl J Med. 376: 115–23, 2017

Lastly – but perhaps most importantly – high placebo responders may also respond most positively to experimental therapies. This was observed as early as 1955, when Lasagna, et al. described that placebo responders exhibited a significantly higher incidence of relief from morphine than non-responders2. This is particularly true in pain studies, where a drug’s mechanism may actually impact the similar pathways in the brain as the placebo effect. For example, placebo treatment has been shown to stimulate endogenous release of neuropeptides such as opioids3 , cannabinoids4 and dopamine 5 , whose pathways are often exploited in drug discovery for neuropathic pain and Parkinson’s disease.

If exclusion of high placebo responders isn’t the most appropriate solution to deal with the placebo response in clinical trials, what is the answer? Tools4Patient scientists used this conundrum as motivation in developing the Placebell©™ approach, which calculates the placebo-covariate for inclusion in the statistical analysis to adjust for high placebo responders, not exclude high placebo responders. With this strategy, data variance caused by the placebo response can be minimized without facing any of the downsides of patient exclusion – thus moving one step closer to the goal of improving data quality and promoting better, faster decision-making during the drug development process.

2 Lasagna L, Mosteller F, von Felsinger JM, Beecher HK. A study of the placebo response. The American Journal of Medicine, 16(6): 770 – 779, 1955.
3 Eippert F, Bingel U, Schoell ED, et al. Activation of the opioidergic descending pain control system underlies placebo analgesia. Neuron. 2009;63(4):533–543.
4 Benedetti F, Amanzio M, Rosato R, Blanchard C. Nonopioid placebo analgesia is mediated by CB1 cannabinoid receptors. Nat. Med. 2011;17(10):1228–1230.
5 Lidstone SC, Schulzer M, Dinelle K, et al. Effects of Expectation on Placebo-Induced Dopamine Release in Parkinson Disease. Arch Gen Psychiatry. 2010;67(8):857–865. doi:10.1001/archgenpsychiatry.2010.88