Tools4Patient Introduces unik-me Platform for Administration of Psychological Questionnaires in Clinical Trials
Tools4Patient (T4P) introduces unik-me, our proprietary platform to administer psychological questionnaires to patients in clinical trials.View
Tools4Patient launches COV-IQ to evaluate the impact of the COVID-19 pandemic on patients in ongoing clinical trials
Tools4Patient launches COV-IQ, a new platform aiming to evaluate the impact of COVID-19 on clinical trial patients. COV-IQ aims to quantify the effect of emotional stress, change in trial conduct and changes in social structure on each trial subject.View
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Osteoarthritis (OA) is common musculoskeletal disease with increased incidence and prevalence associated with aging. It affects around 10 % of the population and is 10 times more common than rheumatoid arthritis (RA).Read More
Are clinical trials patients’ reactions to crisis related to their personality? Application to the COVID-19 pandemic.
Not only are patient visits to clinical sites more difficult (or impossible), patients are also dealing with uncertainty, stress and anxiety. While keeping ongoing trials running is a top objective for many, understanding how this myriad of factors will affect trial data is paramount.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).
Learn the importance of considering patient psychological traits, expectations, perception of patient relationship with the trial physician and staff, and social structure in efforts to understand the impact of the COVID-19 pandemic on clinical trials.
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.
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