Methicillin-Resistant Staphylococcus aureus (MRSA) Infections is an indication for drug development with over 170 pipeline drugs currently active. According to GlobalData, preregistered drugs for Methicillin-Resistant Staphylococcus aureus (MRSA) Infections have a 100% 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 Methicillin-Resistant Staphylococcus aureus (MRSA) Infections 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.
Methicillin-Resistant Staphylococcus aureus (MRSA) Infections overview
Methicillin-resistant Staphylococcus aureus (MRSA) infections that are acquired by persons who have not been recently (within the past year) hospitalized or had a medical procedure (such as dialysis, surgery, catheters) are known as community-acquired MRSA (CA-MRSA) infections; others are hospital-aquired (HA-MRSA). Risk factors for MRSA infection are hemodialysis, weakened immune system, admission to hospitals, and wounds. Symptoms include skin rashes, fatigue, chest pain, fever, and swelling. MRSA can be managed by the use of antibiotics and by maintaining hygienic conditions.
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For a complete picture of PTSR and LoA scores for drugs in Methicillin-Resistant Staphylococcus aureus (MRSA) Infections, 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.
