TECHNOLOGY & DATA MANAGEMENT S
mall biotech companies often struggle with financial pressures, especially in a challenging funding environment marked by rising costs and limited capital.
Early-phase clinical trials further strain resources, jeopardizing product development and company stability. This article introduces a practical pricing model that aligns cost decisions with the sponsor’s goals for trial quality, financial efficiency, and sustainability. Grounded in ICH GCP and FDA’s Risk-Based Monitoring (RBM) guidance, the model can be used to streamline monitoring efforts, reduce costs, accelerate time-to-market and enhance data quality.
Benefits of Risk Assessment Frameworks As outlined in the article Risk Assessment in Clinical Trials, prioritizing critical data elements that ensure the integrity of the study dataset is crucial for producing a robust final report. By combining base cost analysis with data variable prioritization, sponsors can develop an optimal portfolio of actions to reduce uncertainty and enhance efficiency. Key risk parameters—Impact, Probability, and Detectability—can be utilized to calculate a Risk Score for variables monitored during the study maintenance phase, facilitating earlier risk identification, reducing delays, and enhancing overall efficiency.
The formulation includes:
I = Impact: The consequence or severity of an error (1 = Low, 2 = Moderate, 3 = High). P = Probability: The likelihood of an error occurring (1 = Low, 2 = Moderate, 3 = High). D = Detectability: Inversely proportional to probability and impact, it refers to how easily an error, defect, or issue can be noticed or recognized during the clinical trial. A high level of visibility means problems are quickly apparent, reducing risk. (1 = High, 2 = Moderate, 3 = Low).
Where: Risk Score (RS) = Impact (I) x Probability (P) × Detectability (D).
40 | Outsourcing in Clinical Trials Handbook
Calculate Base Cost per Variable • BC = 2,560,000 / 420 = 6,095.24
Calculate Risk Scores by Category • Low Risk Costs = 70 × 6,095.24 × 1 ≈ $426,667
• Moderate Risk Costs = 70 × 6,095.24 × 2 ≈ $853,337
• High Risk Costs = 70 × 6,095.24 × 3 ≈ $1,280,000
Results and Cost Savings By prioritizing high- and moderate-risk data variables, a sponsor could achieve a study management cost reduction of approximately 17% ($426,667). Alternatively, the sponsor could reallocate resources to address
By integrating Base Cost (BC), one can calculate a study’s Risk Priority Weighted Cost (RPWC) for all data variables:
Where: n is equal to the sum of variables monitored and managed, and BCi
cost, impact factor, probability factor, and detectability factor for each data variable (i), respectively.
, Ii, Pi, and Di
Application Example Consider a hypothetical clinical study costing $6.8M, with $2.56M allocated for study maintenance costs, including clinical site monitoring ($1.97M, 28%) and data management ($0.591M, 8%) services for 210 study data variables. In real-world scenarios, the variables Base Cost (BC), Impact (I), Probability (P), and Detectability (D) are unlikely to be evenly distributed. For brevity and simplicity, the following simulation assumes an even distribution of I, P, and D to illustrate the calculation of an average BC across all data variables and Risk Scores categorized as Low, Moderate, and High.
Calculate Risk Score • RS = (70×1) + (70×2) + (70×3) = 420
are base
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