MOv18 IgE is under clinical development by Epsilogen and currently in Phase I for Ovarian Cancer. According to GlobalData, Phase I drugs for Ovarian Cancer have a 73% phase transition success rate (PTSR) indication benchmark for progressing into Phase II. GlobalData’s report assesses how MOv18 IgE’s drug-specific PTSR and Likelihood of Approval (LoA) scores compare to the indication 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.

MOv18 IgE overview

MOv18 IgE is under development for the treatment of ovarian cancer, breast cancer and lung cancer. The drug candidate is administered through intravenous route. The drug candidate is a chimeric IgE antibody targeting alpha-folate receptor.

Epsilogen overview

Epsilogen is a pharmaceutical drug development company. The company specializes in drug development for immunoglobulin E (IgE) antibodies in therapeutic areas of cancer, and the treatment for solid tumors including greater potency, enhanced tumor access and a long tissue half-life. Its service offering includes clinical trial programs, drug discovery programs, and research and development. The company is also developing IGEG platform technology, is a combination of immunoglobulin E (IgE) and immunoglobulin G (IgG) antibody molecules. Epsilogen is headquartered in London, England, the UK.

For a complete picture of MOv18 IgE’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 20 February 2024

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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.