Scientific Poster Publication made on June 2016 at the DIA Annual Conference, Philadelphia (USA).

This proof-of-concept study on peripheral neuropathic pain patients investigates the potential influence
of the investigator on the placebo response in RCTs while manipulating different variables, including
patient expectation, conditioning and prior experiences, observational and social learning.

PNP patients were given a blinded placebo (presented as “new treatment”) in addition to their regular
analgesic treatment. They were randomized to follow a “Influenced” or sham procedures designed to
assess the environmental factors that may influence the placebo response when administrating a drug.

41 completed the study. They suffered from PNP based upon medical examination for at least 6
months. The sex ratio was 21:22 (49/51%) for males and females, respectively. The mean age of the
patients was 57 years old (SD=11.4). The median history of PNP was 7.2 years.

The 20 patients in the “Influenced” group followed the studied placebo-reinforcing procedure
consisting of positive expectation directed information about the placebo in the form of a video. The
patient then underwent pre-treatment heat pain stimuli. After the pain stimuli, patients were given their
first placebo capsule and underwent a new heat pain conditioning approximately one hour after
dosing. The post-treatment heat pain conditioning protocol was intentionally modified from the pretreatment, one as the mean intensity was reduced to induce the patient’s belief in analgesic efficacy.

The 21 patients randomized to the “Sham” group followed the Sham procedure consisting of no
expectation of improvement, neutral social observational learning and no modulation of pain stimuli.
Those patients watched a video presenting only neutral properties of T4P1001 drug (placebo). Both
groups were given capsules to be taken twice a day over 4 weeks as add-on therapy to their regular
analgesic.

The weekly mean of the average pain score (APS; computed on a 11-point numerical rating scale) at
baseline was 5.3. After four weeks of placebo treatment, across groups, 12 patients (30%) had an
important decrease of their average pain of more than a 20% from baseline. Overall, the mean APS
decreased significantly by 0.7 (effect size=-0.50; p-value=0.0047) to 4.6. The 20 patients in the
“Influenced” group had a significant decrease by 0.9 (95%CI=[0.2,1.6]; p-value=0.0167) of their mean
APS. The decrease was less important in the sham group with a decrease by 0.5 (95%CI=[-0.2,1.1]; pvalue=0.12785). However, the difference of decrease between the two procedures was not significant
(p-value=0.4162).

The global magnitude of the mean placebo effect was considered as moderate but in accordance with
published meta-analysis in chronic pain. This relatively mild placebo response could be explained by
the mode of administration. The placebo given as an add-on therapy may have decreased the
expectation associated to efficacy of the treatment. Yet, one third of the patients demonstrated a
strong placebo response.

If the patients following the “Influenced” procedure seemed to have a more important decrease of
APS, they were not significantly different from the “Sham” group. This marginal difference 0.9 vs 0.5 (respectively for influenced and sham group) should be put into perspective with individual variation.
Indeed, both groups had a wide range of placebo responses and a high variance. The “Influenced”
group responses ranged between -2.0 and 4.4 (sd=1.49). The “Sham” patients were comprised
between -1.1 and 5.4 (sd=1.43). This high individual variation combined with small sample sizes could
explain better the likelihood of an observed center effects than a true investigator bias.

To control the increasing placebo response affecting the assay sensitivity in RCTs, many study level
factors have been studied such as number and type of patients, study design and outcome
measurement. An other aspect investigated here on peripheral neuropathic pain patients is the
potential influence of clinical investigator sites on the placebo response. We tried to mimic and
maximize it while manipulating the patient expectation and conditioning through two different
procedures. Our results, however, show that the “true” site effect is marginal compared to the intrinsic
placebo fluctuations. This advocates for a better characterization of the individual placebo response.
The prediction of the placebo responders may be used in RCTs to stratify patients within groups, and
thereby to increase the assay sensitivity.