Fungal Infections is an indication for drug development with over 200 pipeline drugs currently active. According to GlobalData, preregistered drugs for Fungal Infections have a 94.74% 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 Fungal 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.

Fungal Infections overview

Fungal infections are diseases caused by different types of fungi that can affect various parts of the body, such as the skin, nails, hair, mouth, lungs, or brain. Fungi are eukaryotic organisms that can exist as yeast, molds, or both forms. Some fungi are harmless or beneficial, while others can cause infections in humans, especially in people with weakened immune systems. Fungal infections can be classified as primary or opportunistic, depending on whether they can infect healthy or immunocompromised hosts. Fungal infections can also be localized or systemic, depending on whether they affect only one area of the body or spread to multiple organs. Fungal infections are usually diagnosed by examining samples of the affected tissue under a microscope or by culturing the fungus in a laboratory. Antifungal drugs are used to treat fungal infections, either by applying them directly to the infected site or by taking them orally or intravenously.

For a complete picture of PTSR and LoA scores for drugs in Fungal 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.