Varicellovirus Infections is an indication for drug development with over 70 pipeline drugs currently active. According to GlobalData, preregistered drugs for Varicellovirus 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 Varicellovirus 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.
Varicellovirus Infections overview
Varicella-like viruses are cell-associated herpesviruses of the genus Varicellovirus, related to the human virus. It is an alpha herpes virus that causes chickenpox and herpes zoster (shingles). Varicella is characterized by a maculopapular, vesicular rash that can be pruritic and evolves into dried crusts (scabs) over a 3- to 7-day period. Reactivation of the dormant virus results in the characteristic painful dermatomal rash of herpes zoster, which is often followed by pain in the distribution of the rash (postherpetic neuralgia). In children, chicken pox manifests with fever and irritability, followed by vesicular rash eruption. The rash eventually crusts and heals. Chicken pox also can occur in adults without natural or vaccine induced immunity to VZV.
For a complete picture of PTSR and LoA scores for drugs in Varicellovirus 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.
