“Modeling of Peripheral Neuropathic Pain and Osteoarthritis Placebo Response” presented at the International Society for CNS Clinical Trials and Methodology
Dr. Dominique Demolle, CEO of Tools4Patient, recently presented data at the 16th Annual Scientific Meeting of the International Society for CNS Clinical TrialsView
Tools4Patient’s Placebell©™ technology has been selected as a finalist in the 2019 Clinical Trials Innovation Challenge sponsored by IQVIA, Lundbeck, and LEO Innovation Lab.View
There are currently no future events.
See our events archive for our previous event attendance.
Evidence has accumulated in recent years that the placebo response is a significant issue in evaluating efficacy of drugs for rheumatoid arthritis (RA). RA is a chronic disease characterized by inflammatory synovitis and progressive joint destruction.Read More
While the opioid crisis may be creating opportunity for development of novel therapies to treat chronic pain, drug development in this area has historically struggled. According to a BIO report released in 2018, only two novel NCEs were approved for pain indications from 2007-2017 while other analgesia approvals during this period were reformulations of existing compounds or drugs with approval history prior to 2007.Read More
Modelling of PNP and OA Placebo Response: Working towards a unique model of the placebo response in chronic pain?
In analgesia randomized clinical trials (RCTs), the magnitude and the variability of the placebo response negatively impacts the ability to demonstrate superiority of active compounds compared to placebo. The first objective of this analysis was to investigate parameters influencing the placebo response in PNP as a way to control for this major confounding factor.
Identification Of Peripheral Neuropathic Pain Sensory Phenotypes Based On Specific Combinations Of Symptoms Identified With The NPSI (Neuropathic Pain Symptom Inventory)
One way to better personalized the treatment of peripheral neuropathic pain (PNP) would be to identify specific sensory phenotypes of patients responding to different classes of drugs.
Leveraging Historical Data For High-dimensional Covariate-adaptive Randomization, A Machine Learning Approach.
There is a continuous growth in data collected in clinical trials. Many of those patient’s characteristics are potential confounding factors. Ideally, these factors should be accounted for in the randomization process to balance study arms and reduce the variability of the estimated treatment effect.
Interview with Erica Smith, VP of Business Development at Biotech Showcase, San Francisco (January 2019).
Interview with Daniel Levine and Erica Smith, VP of Business Development on The Bio Report podcast (June 2019).
The Characterization of Individual Patient Placebo Response: Impact on the Clinical Study Power
A sophisticated method to identify placebo responders and reduce data variability due to the placebo response, providing drug developers with a tool to manage the placebo response without excluding high placebo responders.
Sign up to join our regular newsletter.
Be the first to receive the latest innovations and news from Tools4Patient.