Skin And Skin Structure Infections (SSSI) Caused By Bacteria is an indication for drug development with over 20 pipeline drugs currently active. According to GlobalData, preregistered drugs for Skin And Skin Structure Infections (SSSI) Caused By Bacteria have a 87.5% 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 Skin And Skin Structure Infections (SSSI) Caused By Bacteria 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.
Skin And Skin Structure Infections (SSSI) Caused By Bacteria overview
Skin and Skin Structure Infections (SSSIs) caused by bacteria encompass a spectrum of infections affecting the skin and underlying tissues, varying from mild to severe and instigated by diverse bacteria. Notable culprits include Staphylococcus aureus, including methicillin-resistant strains (MRSA), Streptococcus pyogenes (group A Streptococcus), and other streptococcal species. SSSI can manifest as cellulitis, erysipelas, impetigo, folliculitis, furuncles, and abscesses, with distinct clinical presentations. Risk factors include compromised immune function, chronic conditions, skin injuries, and surgery. Diagnosis relies on clinical evaluation and occasionally laboratory tests. Antibiotics tailored to the causative bacteria are pivotal for treatment, especially in severe cases or suspected MRSA infections. Prevention involves wound care, hygiene, and managing underlying conditions to avert complications like deep tissue infections or sepsis.
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For a complete picture of PTSR and LoA scores for drugs in Skin And Skin Structure Infections (SSSI) Caused By Bacteria, 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.
