InSyBio Chronic Pain Precision Relief @Salonpas Tool
Approximately 10% of chronic pain patients being administered with traditional topical analgesic therapies are non-responders and do not get pain relief from them. 7 out of 10 are estimated to be able to reduce their pain scores in 14 days after being treated with Salonpas® Pain Relieving Patch. Moreover, 6 out 10 patients using traditional topical analgesics and improving their pain condition will enjoy a further improvement and decrease of the total number of drugs administered to them when using the Salonpas® Pain Relieving Patch.
The InSyBio Chronic Pain Precision Relief @Salonpas Tool allows the classification of the patients in the above groups with more than 90% accuracy enabling patients to select the most suitable treatment for them. In general, the use of InSyBio Chronic Pain Precision Relief tools for selecting the most suitable chronic pain relief method can improve the chronic pain condition of more than 98% of the patients.
The InSyBio Chronic Pain Precision Relief @Salonpas Tool allows the classification of the patients in the above groups with more than 90% accuracy enabling patients to select the most suitable treatment for them. In general, the use of InSyBio Chronic Pain Precision Relief tools for selecting the most suitable chronic pain relief method can improve the chronic pain condition of more than 98% of the patients.
InSyBio Precision Chronic Pain Relief Tool has been developed for the US population, and is mainly intended for use in the US. All medical decisions need to be taken by a patient in consultation with their doctor. The authors and the sponsors of this tool accept no responsibility for clinical use or misuse of the machine learning empowered prognostic scores or any other detail displayed in our tool.
The predictions are based on InSyBio's machine learning models whose initial training and evaluation has been conducted on data from the Relief and the Opera studies. Prediction models have currently been evaluated in 817 patients with an accuracy of discriminating between responders and non-responders exceeding 90%. For more details on the Relief and OPERA study read the following articles:
- Gudin, J., Mavroudi, S., Korfiati, A. & Hurwitz, A. Personalized Pain Therapy: Artificial Intelligence (AI) Utilized to Predict Patient Response to OTC Topical Analgesics. Anesth Pain Res. 2021; 5 (1): 1-11. Correspondence: Peter Hurwitz, Clarity Science LLC, 750.
- Gudin, J. A., Dietze, D. T., & Hurwitz, P. L. (2020). Improvement of Pain and Function After Use of a Topical Pain Relieving Patch: Results of the RELIEF Study. Journal of Pain Research, 13, 1557.
- Gudin, J., Mavroudi, S., Korfiati, A., Theofilatos, K., Dietze, D., & Hurwitz, P. (2020). Reducing Opioid Prescriptions by Identifying Responders on Topical Analgesic Treatment Using an Individualized Medicine and Predictive Analytics Approach. Journal of Pain Research, 13, 1255-1266.
- Gudin JA, Brennan MJ, Harris ED, et al. Changes in pain and concurrent pain medication use following compounded topical analgesic treatment for chronic pain: 3- and 6-month follow-up results from the prospective, observational Optimizing Patient Experience and Response to Topical Analgesics study. J Pain Res. 2017;10:2341.
- Gudin JA, Brennan MJ, Harris ED, Hurwitz PL, Dietze DT, Strader JD. Reduction of opioid use and improvement in chronic pain in opioid-experienced patients after topical analgesic treatment: an exploratory analysis. Postgrad Med. 2018;130(1):42-51.