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Clinical Trials of Antidepressants

How Changing the Model Can Uncover New, More Effective Molecules

  • Martin M. Katz

Part of the SpringerBriefs in Psychology book series (BRIEFSPSYCHOL)

About this book

Introduction

This brief guide takes current clinical trial protocols to task and replaces them with a contemporary framework for improving next-generation antidepressants and their underlying science. Innovative models are based on a nuanced, neurologically-informed understanding of drug mechanisms and the component cognitive, mood, and behavioral aspects of depression. The book reconceptualizes not only the clinical trial process but the clinical concept of depression itself as essential to bringing pharmaceutical research and development up to date, boosting efficiency and effectiveness, finding new molecules, and reducing waste. Case studies and a review of salient depression scales illustrate the potential benefits of such wide-scale change. 

Included in the coverage: 

    Why now the need for a new clinical trials model for antidepressants?
  • Aims and basic requirements of clinical trials: conventional and component-specific models.
  • Methods for measuring the components and the profile of drug actions: the multivantaged approach.
  • Achieving the ideal clinical trial: an example of the merged componential and established models.
  • Prediction and shortening the clinical trial.
  • The video clinical trial. 

Clinical Trials of Antidepressants will interest a varied audience, including clinical investigators, academic and pharmaceutical company scientists, clinical trial organizations, psychiatrists, outpatient physicians, psychotherapists, clinical psychologists, psychology graduate students, medical students, and government agencies such as the FDA.

Keywords

depression major depressive disorders clinical trials antidepressants tricyclic drugs SSRIs clinical assessment methods video technology VIBES multivantaged method components of psychopathology dimensions of depression diagnostic-specific model component-specific model

Authors and affiliations

  • Martin M. Katz
    • 1
  1. 1.Health Science Center at San AntonioUniversity of TexasUSA

Bibliographic information