OLP-1002 is under clinical development by OliPass and currently in Phase II for Osteoarthritis Pain. According to GlobalData, Phase II drugs for Osteoarthritis Pain have a 41% phase transition success rate (PTSR) indication benchmark for progressing into Phase III. GlobalData’s report assesses how OLP-1002’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.
OLP-1002 overview
OLP-1002 is under development for the treatment of neuropathic pain, osteoarthritis pain, rheumatoid arthritis pain, trigeminal neuralgia and chemotherapy induced peripheral neuropathy. The therapeutic candidate is administered subcutaneously. The therapeutic candidate acts by targeting SCN9A (sodium voltage-gated channel alpha subunit 9) gene. It is based on peptide nucleic acid (PNA) technology. It was also under development for the treatment of erythromelalgia
OliPass overview
OliPass, formerly CTI Bio, is a biopharmaceutical company. It develops skin therapies. The company’s pipeline products include SCN9A, PCSK9, VEGF, HIF-1a, Dystrophin and PTP1B. It provides OliPass peptide nucleic acid (OliPass PNA), a platform for artificial nucleic acid therapeutics. The company also develops antisense therapy and exon skipping to inhibit mRNA variants that express proteins lacking the physiological function of the original protein. Olipass is headquartered in Yongin, Gyeonggi, Korea.
For a complete picture of OLP-1002’s drug-specific PTSR and LoA scores, 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.
