Venous Thromboembolism is an indication for drug development with over 30 pipeline drugs currently active. According to GlobalData, preregistered drugs for Venous Thromboembolism have a 77.78% 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 Venous Thromboembolism 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.
Venous Thromboembolism overview
Venous thromboembolism (VTE) is a condition that occurs when a blood clot forms in a vein and blocks the blood flow. VTE can affect the deep veins of the legs or arms (deep vein thrombosis, or DVT) or the lungs (pulmonary embolism, or PE). VTE can cause serious complications such as tissue damage, organ failure, or death. VTE can be provoked by factors such as surgery, injury, infection, inflammation, or immobility. VTE can be prevented by using anticoagulant medications, compression stockings, or mechanical devices. VTE can be diagnosed by using tests such as ultrasound, computed tomography (CT) scan, or ventilation-perfusion (VQ) scan. VTE can be treated by using anticoagulant medications, thrombolytic medications, or surgical procedures.
For a complete picture of PTSR and LoA scores for drugs in Venous Thromboembolism, 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.
