Procedure for Formulation Optimization Using Design of Experiments (DoE)
| Department | Research and Development (R&D)/Quality Assurance (QA)/Quality Control (QC)/Formulation Development |
|---|---|
| SOP No. | SOP/Ointment/188 |
| Supersedes | V 1.0 |
| Page No. | Page X of Y |
| Issue Date | [Insert Issue Date] |
| Effective Date | [Insert Effective Date] |
| Review Date | [Insert Review Date] |
1. Purpose
The purpose of this Standard Operating Procedure (SOP) is to define a systematic approach for optimizing pharmaceutical ointment formulations using Design of Experiments (DoE). The goal is to achieve robust and high-quality formulations by statistically analyzing the impact of different formulation parameters.
2. Scope
This SOP applies to all personnel involved in the formulation development, quality assessment, and process optimization of ointments in the Research and Development (R&D), Quality Assurance (QA), and Quality Control (QC) departments.
3. Responsibilities
- Formulation Scientist: Designs and conducts DoE studies for formulation optimization.
- QA Officer: Ensures compliance with statistical modeling and optimization guidelines.
- QC Analyst: Performs analytical testing on experimental batches.
- Process Engineer: Monitors scale-up and manufacturing feasibility.
- Regulatory Affairs Specialist: Ensures regulatory compliance in formulation optimization.
4. Accountability
The R&D Manager is accountable for ensuring that all formulation optimization activities comply with GMP, FDA, ICH Q8, WHO, and company policies.
5. Procedure
5.1 Introduction to Design of Experiments (DoE)
- DoE is a statistical tool used for:
- Identifying key formulation variables.
- Understanding interactions between ingredients.
- Optimizing formulation parameters
to meet quality targets.
Common DoE models used in formulation studies:
- Factorial Design (Full or Fractional).
- Response Surface Methodology (RSM).
- Taguchi Design.
5.2 Identifying Critical Formulation Variables
- Identify **Critical Material Attributes (CMAs)** and **Critical Process Parameters (CPPs)**, such as:
- API concentration.
- Emulsifier concentration.
- pH adjusters.
- Mixing speed and temperature.
- Perform **Risk Assessment** to prioritize variables for DoE.
- Document variable selection in the **DoE Experimental Design Log (Annexure-1).**
5.3 Setting Up the DoE Model
- Define the **objective function** (e.g., optimizing viscosity, spreadability, drug release).
- Determine the **independent and dependent variables**:
- Independent variables: API %, emulsifier %, viscosity modifier.
- Dependent variables: Spreadability, bioavailability, stability.
- Select an appropriate **experimental design** (Full Factorial, RSM, etc.).
- Use **DoE software (e.g., Minitab, Design-Expert)** for statistical modeling.
5.4 Conducting Experimental Trials
- Prepare formulation batches based on **DoE matrix.**
- Conduct **preliminary screening** to eliminate non-viable formulations.
- Record batch preparation details in the **DoE Formulation Trial Log (Annexure-2).**
5.5 Analyzing DoE Results
- Evaluate responses using:
- Contour plots and 3D surface graphs.
- Statistical analysis (ANOVA, Regression modeling).
- Identify **optimized formulation based on desirability function.**
- Document findings in the **DoE Data Analysis Report (Annexure-3).**
5.6 Scale-Up and Validation of Optimized Formulation
- Confirm feasibility of the optimized formulation at **pilot-scale.**
- Ensure consistency in **stability testing and performance parameters.**
- Validate process parameters to meet **Quality Target Product Profile (QTPP).**
5.7 Regulatory Compliance and Documentation
- QA must review and approve all DoE data before **final formulation selection.**
- Ensure documentation complies with **ICH Q8 – Pharmaceutical Development.**
- Maintain records for **five years** for regulatory audits.
6. Abbreviations
- API – Active Pharmaceutical Ingredient
- GMP – Good Manufacturing Practices
- QA – Quality Assurance
- QC – Quality Control
- ICH – International Council for Harmonisation
- FDA – Food and Drug Administration
- DoE – Design of Experiments
- ANOVA – Analysis of Variance
- QTPP – Quality Target Product Profile
7. Documents
- DoE Experimental Design Log (Annexure-1)
- DoE Formulation Trial Log (Annexure-2)
- DoE Data Analysis Report (Annexure-3)
8. References
- ICH Q8 – Pharmaceutical Development Guidelines
- FDA Guidance on Pharmaceutical Quality by Design (QbD)
- WHO Guidelines on Formulation Development
9. SOP Version
Version 2.0
10. Approval Section
| Prepared By | Checked By | Approved By | |
|---|---|---|---|
| Signature | |||
| Date | |||
| Name | |||
| Designation | |||
| Department |
11. Annexures
Annexure-1: DoE Experimental Design Log
| Date | Independent Variables | Dependent Variables | DoE Model | QC Review |
|---|---|---|---|---|
| 02/02/2025 | API %, Emulsifier % | Viscosity, Spreadability | Full Factorial | Approved |
Annexure-2: DoE Formulation Trial Log
| Date | Batch No. | Formulation Parameters | Test Results | QA Approval |
|---|---|---|---|---|
| 02/02/2025 | OINT-1001 | API 2%, Polymer 5% | Optimal | Approved |
12. Revision History
| Revision Date | Revision No. | Details | Reason | Approved By |
|---|---|---|---|---|
| 02/02/2025 | 2.0 | Expanded DoE Analysis | Improved Compliance | QA Head |