CLINICAL STRATEGY
UNDERSTANDING DOWNSTREAM
EFFECTS FOR YOUR PRODUCT
Elevate Your Clinical Strategy For Commercial Success
Having a strong clinical strategy is essential to successfully bring a new pharmaceutical asset to market. To do so, you must have a thorough understanding of all possible outcomes across the development spectrum, including potential risks, benefits, and uncertainties.
However, quantitatively capturing the risks, benefits, and uncertainties of any clinical study is difficult to do with common excel-based modeling practices. Instead, potential clinical outcomes should seamlessly connect to and inform the downstream commercial opportunity. Assessing an asset's clinical strategy throughout the development process can have profound impacts downstream on budget requirements, launch probability, and commercial viability. This inevitably leads to facing major challenges:
Missing target recruitment dates and managing prolonged recruitment timelines
Difficulty incorporating competitive scenarios into the clinical design
Inability to enable ”tweaking” of recruitment plans from static data
Our Approach
People
The Captario team holds a variety of essential competencies, including advanced statistics, applied mathematics, data analytics, and decision theory.
Our experienced analysts will:
1. Guide you to superior decision-making
2. Assess how to deliver new medicines fast and cost-effectively
3. Determine the best path forward for your product or portfolio based on the output results from our informed analysis
Processes
Captario uses a three-phase process when analyzing your portfolio:
1. Align the problem and engagement to leverage Captario SUM®
2. Leverage the modeling and simulation capabilities of Captario SUM®
3. Provide answers to your key questions with customized visualizations and outputs from Captario SUM®
Tools
Apply any desired level of modeling rigor fit for your specific questions:
1. Basic Modeling: Models reflect single point assumptions, simple ranges of inputs, and fixed time series of data
2. Expression-Based Modeling: Modeling practices based on expressions and interdependencies
3. Advanced Statistical Modeling: Application of advanced statistical principles from independent biostatistics experts
Related Reading
Clinical Effect – A Key Aspect in Drug Development
Understanding the forecasting process and making decisions based on those predictions is not done easily. Without time-machines or real fortune tellers to give us the answers of what will happen, we’re left with the practice of modeling the future, and subsequently base our decisions on what those models tells us. As these results provide the basis for our decisions, the models must be sufficiently realistic and describe the most important components of the decision reality.