Drug Substance Algorithm

A detailed overview of the algorithm used to forecast drug substance requirements for clinical trials forecasting.

Purpose & Value

The primary goal of this forecasting process is to provide a reliable estimate of the total drug substance required throughout the lifecycle of associated clinical trials. This enables:

Informed Production Planning: Determine the necessary manufacturing volume and timing.
Supply Chain Optimization: Ensure sufficient material is available when and where it's needed.
Budget Management: Accurately estimate costs associated with drug substance procurement and product manufacturing.
Risk Mitigation: Identify potential shortfalls early by understanding demand drivers.
Resource Allocation: Optimize the use of valuable drug substance across different trials and products.

Forecasting Methodology Overview

The calculation aggregates demand across all relevant clinical trials linked to the specific drug substance via the final drug products (e.g., tablets, vials) used in those trials.

The process involves several key steps:

Data Aggregation: Gathers comprehensive information about the drug substance, the drug products it's used in, and the structure of all associated clinical trials. This includes:
- Trial protocols (treatment arms, patient distribution).
- Visit schedules (frequency and type: consistent or custom intervals).
- Kit details (amount of substance per kit, kits administered per visit).
- Manufacturing parameters (potential yield loss for each drug product).
Patient Data Integration: Incorporates the total number of patients planned or enrolled in each relevant trial.
Demand Calculation (Trial by Trial): For each trial, and specifically for each treatment arm within that trial, the system calculates the substance required for each relevant kit configuration. This calculation considers:
- Patients per Arm: (Total Trial Patients) × (% Participants in Arm / 100)
- Visits per Patient: The number of visits where the specific kit is administered (defined by the arm's schedule - either a total count for consistent intervals or implicitly 1 for each custom interval record).
- Kits per Visit: The number of kits of this type given to a patient during a single relevant visit.
- Substance per Kit: The quantity of the active drug substance contained within a single kit.
The core calculation for the base requirement of a substance for a specific kit configuration within a treatment arm is:

Base Requirement = (Substance per Kit) 
                   × (Kits per Visit) 
                   × (Visits per Patient) 
                   × (Patients per Arm)

(Note: This calculation is performed for every active kit type associated with the drug substance within each treatment arm, summing the results for the trial total.)
Yield Loss Adjustment: Manufacturing processes often involve some loss of material. To ensure enough final product is produced, the calculated Base Requirement is adjusted upwards based on the Potential Yield Loss (%) defined for the specific drug product.
The formula for the adjusted requirement is:

Adjusted Requirement = Base Requirement / (1 - (Potential Yield Loss % / 100))

Example: If the Base Requirement is 90mg and the Potential Yield Loss is 10%, the Adjusted Requirement is 90mg / (1 - 0.10) = 90mg / 0.90 = 100mg. This means 100mg must enter the process to yield the required 90mg.
Results Summarization:
- Provides a detailed breakdown of substance requirements per trial, showing the contribution of each drug product used within that trial (both base and adjusted amounts).
- Presents an overall summary, aggregating the total required amount (both base and adjusted for yield loss) for each distinct drug product across all associated trials.

Key Inputs

To perform an accurate forecast, the system relies on detailed and up-to-date information regarding:

Drug Substance: Base properties (e.g., measurement unit).
Drug Product: Manufacturing yield loss percentage.
Clinical Trials:
- Overall structure and treatment arms.
- Percentage of participants per arm.
- Total patient recruitment numbers.
- Visit schedules (number/timing of visits per arm or custom interval definitions).
- Kit details (substance quantity per kit, kits per visit, type - e.g., active vs. placebo).
Linkages: Clear connections between the drug substance, the drug products, and the trials where they are used.

Key Outputs

The process generates a comprehensive forecast report detailing:

Total Substance Required (per Drug Product): The overall quantity needed for each specific drug product across all trials, both before and after accounting for manufacturing yield loss.
Trial-Specific Requirements: A breakdown showing how much of the substance (via its products) is allocated to each individual trial.

This output provides actionable insights for supply chain managers, clinical operations teams, and financial planners involved in the clinical trial process.

Purpose & Value

The primary goal of this forecasting process is to provide a reliable estimate of the total drug substance required throughout the lifecycle of associated clinical trials. This enables:

Informed Production Planning: Determine the necessary manufacturing volume and timing.

Supply Chain Optimization: Ensure sufficient material is available when and where it's needed.

Budget Management: Accurately estimate costs associated with drug substance procurement and product manufacturing.

Risk Mitigation: Identify potential shortfalls early by understanding demand drivers.

Resource Allocation: Optimize the use of valuable drug substance across different trials and products.

Forecasting Methodology Overview

The calculation aggregates demand across all relevant clinical trials linked to the specific drug substance via the final drug products (e.g., tablets, vials) used in those trials.

The process involves several key steps:

Data Aggregation: Gathers comprehensive information about the drug substance, the drug products it's used in, and the structure of all associated clinical trials. This includes:

Trial protocols (treatment arms, patient distribution).
Visit schedules (frequency and type: consistent or custom intervals).
Kit details (amount of substance per kit, kits administered per visit).
Manufacturing parameters (potential yield loss for each drug product).

Patient Data Integration: Incorporates the total number of patients planned or enrolled in each relevant trial.

Demand Calculation (Trial by Trial): For each trial, and specifically for each treatment arm within that trial, the system calculates the substance required for each relevant kit configuration. This calculation considers:

Patients per Arm: (Total Trial Patients) × (% Participants in Arm / 100)
Visits per Patient: The number of visits where the specific kit is administered (defined by the arm's schedule - either a total count for consistent intervals or implicitly 1 for each custom interval record).
Kits per Visit: The number of kits of this type given to a patient during a single relevant visit.
Substance per Kit: The quantity of the active drug substance contained within a single kit.

The core calculation for the base requirement of a substance for a specific kit configuration within a treatment arm is:

Base Requirement = (Substance per Kit) × (Kits per Visit) × (Visits per Patient) × (Patients per Arm)

(Note: This calculation is performed for every active kit type associated with the drug substance within each treatment arm, summing the results for the trial total.)

Yield Loss Adjustment: Manufacturing processes often involve some loss of material. To ensure enough final product is produced, the calculated Base Requirement is adjusted upwards based on the Potential Yield Loss (%) defined for the specific drug product.
The formula for the adjusted requirement is:

Adjusted Requirement = Base Requirement / (1 - (Potential Yield Loss % / 100))

Example: If the Base Requirement is 90mg and the Potential Yield Loss is 10%, the Adjusted Requirement is 90mg / (1 - 0.10) = 90mg / 0.90 = 100mg. This means 100mg must enter the process to yield the required 90mg.

Results Summarization:

Provides a detailed breakdown of substance requirements per trial, showing the contribution of each drug product used within that trial (both base and adjusted amounts).
Presents an overall summary, aggregating the total required amount (both base and adjusted for yield loss) for each distinct drug product across all associated trials.

Key Inputs

To perform an accurate forecast, the system relies on detailed and up-to-date information regarding:

Drug Substance: Base properties (e.g., measurement unit).

Drug Product: Manufacturing yield loss percentage.

Clinical Trials:

Overall structure and treatment arms.
Percentage of participants per arm.
Total patient recruitment numbers.
Visit schedules (number/timing of visits per arm or custom interval definitions).
Kit details (substance quantity per kit, kits per visit, type - e.g., active vs. placebo).

Linkages: Clear connections between the drug substance, the drug products, and the trials where they are used.

Key Outputs

The process generates a comprehensive forecast report detailing:

Total Substance Required (per Drug Product): The overall quantity needed for each specific drug product across all trials, both before and after accounting for manufacturing yield loss.

Trial-Specific Requirements: A breakdown showing how much of the substance (via its products) is allocated to each individual trial.

This output provides actionable insights for supply chain managers, clinical operations teams, and financial planners involved in the clinical trial process.