Opium (Opioid) Addiction is an indication for drug development with over 110 pipeline drugs currently active. According to GlobalData, preregistered drugs for Opium (Opioid) Addiction have a 85.71% 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 Opium (Opioid) Addiction 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.

Opium (Opioid) Addiction overview

Opioid addiction develops after using opioids regularly for a period of time. Prolonged use of opiates can lead to nerve damage within the brain that causes cells to stop producing endogenous opiates (natural painkillers, known as endorphins). This can lead to an inability of the body to stop pain, because there are no endorphins to mask the pain initially. The degeneration of the nerve cells that reduce pain can lead to a physical dependence on opiates as an external supply source. Signs and symptoms include increased general anxiety, euphoria, psychosis, depression, high blood pressure, decreased appetite, physical agitation, difficulty sleeping, and pain in the bones. The predisposing factors include age, a personal history of substance abuse, family history of substance abuse, cigarette dependency, and psychological stress.

For a complete picture of PTSR and LoA scores for drugs in Opium (Opioid) Addiction, 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.