Pharmaceutical Product Strategy details a cutting-edge approach to the challenges involved in product launches, the brand planning process, and the modeling of patient, physician, and prescription behavior that are vital for product success.

Features:

• Provides an operational approach that quantifies key relationships and identifies the importance of each when formulating a Brand Plan
• Contains illustrations of numerous DM structures that let you see the examples of the approach in a wide variety of situations
• Explores optimization, Monte Carlo analysis, real options, robust decision making, and bounding-cutting-edge tools that can be applied to the basic DM framework
• Details the concept of product treatment attractiveness and choice models, conjoint analysis, competitive sets, data collection/estimation, and market estimation
• Includes an example of a market model that provides sample metrics, forecasting options, and scenario analysis possibilities
• Extends the DM framework to issues of pipeline portfolio management and risk analysis

Contents

Traditional Approaches to Brand Planning: The Discounnect Between Product Strategies and Commercial Evaluations

• Typical Approach for Strategic/brand Planning in the Pharmaceutical Industry
• Limitations Found in the Existing Brand Planning Process

Dyanamic Modeling Approach to Brand Planning: Operationally Understanding Key Marketplace Dynamics

• The Link between Structure and Behavior
• Three Key Sectors of the Dynamic Modeling of Pharmaceutical Marketplaces
• Overview of Dynamic Modeling Advantages

The Dynamic Modeling Language

• Dynamic Modeling
• Advantages of the Dynamic Modeling Approach
• Dynamic Modeling Language

Patient Flow Sector of the Standard Template Dynamic Model

• Properties of Disease Indications Fitting into the Standard Template Dynamic Model
• Epidemiology
• Introduction to Extended Standard Template Example
• Compliance/Persistency
• Treatment Options
• Key Treatment Change Dynamics Captured by MECE Formulation
• Key Insights from Treatment Change Matrix Data
• Patient Flow Allocation

Extensions of the Standard Template

• Stages of Diagnosis
• Nonchronic Diseases
• Misdiagnosis Stage
• Progression of Lines of Therapy
• Disaggregation

Data for the Standard Template Dynamic Model

• Patient Stock Data
• Sources of Patient Stock Data
• Patient Flow Data

Specific Models of Patient Flow Dynamics

• Event-Based Decision Tree
• Medical Procedures
• Trial-Repeat Models

Dynamic Models of Doctor Adoption of Newly Released Pharmaceuticals

• Doctor Adoption of Pharmaceutical Products
• Calibration of Structure to Historical Data
• Expanding the Dynamic Model to Include Causal Factors of External Influence
• Segmentation

Treatment Attractiveness of Pharmaceutical Products

• Assumptions Involved in Treatment Attractiveness Scoring
• Determining Aggregate Treatment Attractiveness
• Determining Factors of Treatment Attractiveness
• Determining Importance of Treatment Attractiveness Factors
• Determining if Importance of Treatment Attractiveness Factors Changes Over Time
• Determining Ratings of Treatment Attractiveness Factors
• Calculation of Treatment Attractiveness
• Treatment Attractiveness by Patient Segmentation
• Steps in the Treatment Attractiveness Process
• Extension: Reducing the Number of Treatment Options in the MECE Set

Integrating the Three Sectors of the Standard Template Dynamic Model

• Logit Choice Algorithms
• Extending to Other Patient Flow Allocations
• An Alternate Approach to Switching Treatment Algorithms
• Incorporating Doctor Adoption/Prescribing Behavior
• Bringing the Three Sectors Together

Strategy Testing Using Integrated Standard Template Model

• Strategy Framework for New Compound Introductions
• Recap of Example Dynamic Model Market Conditions
• Patient Flow Metrics
• Patient Flow Allocations
• Combining Patient Flow Metrics and Allocation
• Doctor Adoption Metrics
• Combining Case, Place, and Pace Strategies

Dynamic Modeling of First Mover Advantage and Network Effects

• Accelerated NCE Development
• Reinforcing Feedback Effects
• Case Study: Illustrative Example of Analyzing Network Effects Using Dynamic Modeling
• Using Dynamic Modeling to Estimate First Mover Advantage
• Summarizing Network Effects and First Mover Advantage

Dynamic Modeling of New Marketplaces: Techniques for Dealing with Uncertainity

• Case Study: Using Dynamic Modeling in Latent Marketplaces
• The Role of Uncertainty in Mental and Dynamic Models
• Bounding the Possibilities: Stock/Flow Structure
• Approaches for Coping with Uncertainty in Model Relationships
• Managing Uncertainty around Dynamic Modeling Parameters

Integrating Standard Template Dynamic Models Across Indications

• Overlap of Patients
• Misdiagnosis
• Physician Prescribing Feedback
• Patient Feedback between Indications

Dynamic Modeling of Pharmaceutical Pipeline Portfolio Issues

• Establishing a Dynamic Model Framework for Drug Development
• Populating the Stock/Flow Framework
• Modeling Terminology: Continuous vs. Agent-Based Models
• Incorporating Compound Failure Rates
• Analysis of Pipeline Dynamics
• Dynamic Modeling vs. Alternative Analysis Tools
• Extensions of the Basic Structure
• Taking a Compound to the OTC Market
• In-Licensing Compounds
• Out-Licensing Compounds
• Line Extensions from Parent Compounds
• Incorporating Probability Distributions for Input Parameters
• Calculating Compound Revenue Using the Standard Template
• Computing Resource Requirements
• Strategy Tests Using the Dynamic Model Simulation

Index

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