Gram-Negative Bacterial Infections is an indication for drug development with over 700 pipeline drugs currently active. According to GlobalData, preregistered drugs for Gram-Negative Bacterial Infections have a 95.24% 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 Gram-Negative Bacterial 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.
Gram-Negative Bacterial Infections overview
Gram-negative bacterial infections are caused by a group of bacteria that have a distinctive outer membrane and stain red when exposed to a chemical process called Gram staining. These bacteria can cause various types of infections, such as pneumonia, meningitis, urinary tract infections, bloodstream infections, and wound infections. Some of the common gram-negative bacteria include E. coli, Pseudomonas aeruginosa, Klebsiella, Acinetobacter, and Salmonella. Gram-negative bacteria are often resistant to multiple antibiotics and can release toxic substances called endotoxins when they die. Therefore, gram-negative bacterial infections can be difficult to treat and can lead to serious complications.
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For a complete picture of PTSR and LoA scores for drugs in Gram-Negative Bacterial 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.
