Appetite (Eating) Disorders is an indication for drug development with over 30 pipeline drugs currently active. According to GlobalData, preregistered drugs for Appetite (Eating) Disorders have a 66.67% 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 Appetite (Eating) Disorders 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.

Appetite (Eating) Disorders overview

Appetite (eating) disorders are psychological conditions that affect how people think and behave regarding food and their body weight and shape. They can cause serious health problems and even death if not treated. Some of the most common types are anorexia nervosa, bulimia nervosa, binge-eating disorder, and avoidant restrictive food intake disorder. People with these disorders may have symptoms such as extreme restriction or bingeing of food, purging behaviors, fear of weight gain, distorted body image, and physical complications. Eating disorders can be caused by various factors, such as genetics, environment, personality, trauma, and culture. Treatment options may include psychotherapy, medication, nutrition counseling, and hospitalization.

For a complete picture of PTSR and LoA scores for drugs in Appetite (Eating) Disorders, 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.