Alongside putative disease-modifying therapies, the late-phase pipeline in Alzheimer’s disease (AD) features several therapies for the treatment of behavioral symptoms in AD. Symptoms such as psychosis and agitation can cause significant patient and caregiver distress and contribute to nursing home placement. Owing to the lack of approved therapies to manage these symptoms in AD patients, physicians prescribe an array of drugs from a range of drug classes, but the drugs are often associated with unwanted side effects and safety risks. This study examines the drug and class-level prescribing patterns for key neuropsychiatric therapies—antipsychotics, mood stabilizers, anxiolytics, and benzodiazepines—in patients diagnosed with AD to provide context for developers of new brands that may enter a mostly generic but entirely off-label market arena.

Questions Answered

  • Which neuropsychiatric drugs/drug classes are most commonly prescribed to AD patients? What have been the recent quarterly trends in prescribing?
  • What percentage of AD patients receive a key therapy within two years of diagnosis, and how quickly? What percentage of patients progress to later lines of therapy within two years of diagnosis?
  • What percentage of AD patients are treated with monotherapy versus combination therapy across the key drug classes queried? What are the most commonly used combinations?
  • What are the product-level compliance and persistency rates among drug-treated patients?

Markets covered: United States

Real-world data: Longitudinal patient-level claims data analysis

Key drugs covered: Antipsychotics (e.g., quetiapine), mood stabilizers (e.g., divalproex sodium), anxiolytics (e.g., buspirone), benzodiazepines (e.g., alprazolam)

Key analysis provided:

  • Brand / therapy use across a longitudinal patient sample.
  • Newly diagnosed patient analysis.
  • Treatment initiation and progression.
  • Line of therapy analysis.
  • Combination therapy analysis.
  • Source of business for recently treated patients.
  • Persistency and compliance analysis.
  • Product-level patient flowcharts.

Product Description

Treatment Algorithms: Claims Data Analysis provides detailed, quantitative analysis of the treatment journey and brand usage across lines of therapy and overall using real-world, patient-level claims data so that marketers can accurately assess their source of business, benchmark usage against competitors, and quantify areas of opportunity for their marketed or emerging brand.

Table of contents

  • Detailed, Expanded Analysis: Treatment Algorithms - Claims Data Analysis: Neuropsychiatric Therapies in Alzheimer's Disease (US)
    • Treatment Algorithms CDA: Alzheimer's Disease (US) February 2019

Author(s): Ruchita Kumar, Ph.D

Ruchita has joined as a Lead Analyst in the Central Nervous System and Ophthalmology team at Decision Resources Group. She comes with eight years of experience in handling various types of commercial assessment projects. She has worked on variety of opportunity assessment and market intelligence projects involving preparation of disease narratives, epi-based forecasts, patent landscapes, social media analysis and building brand performance reports across different therapy areas. She earned a in design and development of modified release dosage forms of anti-diabetic drugs from the University Institute of Pharmaceutical Sciences, Panjab University, Chandigarh.


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