Post-Operative Pain is an indication for drug development with over 130 pipeline drugs currently active. According to GlobalData, preregistered drugs for Post-Operative Pain have a 72.73% likelihood of approval (LoA) indication benchmark. GlobalData’s report assesses how phase transition success rate (PTSR) and likelihood of approval (LoA) scores for pipeline drugs in Post-Operative Pain compared to historical benchmarks. Buy the report here.
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GlobalData tracks drug-specific phase transition and likelihood of approval scores, in addition to indication benchmarks based off 18 years of historical drug development data. Attributes of the drug, company and its clinical trials play a fundamental role in drug-specific PTSR and likelihood of approval.
Post-Operative Pain overview
Post-operative pain is a common consequence following surgical procedures, stemming from tissue trauma and inflammatory responses. Its intensity varies depending on factors such as the type and extent of surgery, individual pain tolerance, and pre-existing conditions. While essential for alerting the body to potential harm, unmanaged post-operative pain can delay recovery, impair function, and increase the risk of complications like chronic pain. Multimodal pain management approaches, combining pharmacological interventions such as opioids, nonsteroidal anti-inflammatory drugs (NSAIDs), and local anesthetics with non-pharmacological techniques like regional anesthesia, nerve blocks, and physical therapy, aim to alleviate pain, enhance comfort, and promote early mobilization and rehabilitation.
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For a complete picture of PTSR and LoA scores for drugs in Post-Operative Pain, buy the report here.
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GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData’s Likelihood of Approval analytics tool dynamically assesses and predicts how likely a drug will move to the next stage in clinical development (PTSR), as well as how likely the drug will be approved (LoA). This is based on a combination of machine learning and a proprietary algorithm to process data points from various databases found on GlobalData’s Pharmaceutical Intelligence Center.
