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.

PF614-MPAR overview

PF614-MPAR, a combination of PF614 and nafamostat is under development for the treatment of pain and opioid abuse and addiction. The drug candidate is developed based on opioid overdose protection platform MPAR (Multi Pill Abuse Resistance). The Bio-MD technology is designed to effectively deter prescription drug abuse at a molecular level and MPAR is designed to provide another layer of protection for Bio-MD products. PF614 solution is co-administered with nafamostat, as an immediate release (IR) solution or extended release (ER) capsule formulation. It acts by targeting mu-type opioid receptor (MOR1) and is administered by oral route.

Ensysce Biosciences overview

Ensysce Biosciences is a biotechnology company. It offers proprietary abuse-resistant opioid prodrug technology. The company’s pipeline products include PF614- TAAP oxycodone for pain, respiratory diseases, PF8001 / PF8026- TAAP amphetamine to deter prescription drug abuse at the molecular leveln, OUD is to abuse deterrent technology for Opioid Use Disorder. The company offers services such as clinical programs, preclinical programs, TAAP technology, pain medications, drug delivery, MPAR technology, proprietary prodrug technology, abuse resistant technology among others. It provides its products and services to healthcare, medical and pharmaceutical sectors. Ensysce Biosciences is headquartered in San Diego, California, the US.

For a complete picture of PF614-MPAR’s drug-specific PTSR and LoA scores, buy the report here.

This content was updated on 15 September 2023

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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.

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