Searching For Root Causes Under Pressure Using Data Visualization to Focus Investigations Dan Pilipauskas Pfizer Inc.

2 What Will Be Covered Review an investigation of a tablet manufacturing process gone bad Show how intuition can turn an investigation in the wrong direction Show how data visualization with Spotfire can quickly analyze process data and help find the root cause

3 A Real Life Manufacturing Problem Situation – A drug tablet was being produced with acceptable dissolution rates – Production stop and equipment switched to another product for several months – When production of the drug tablet resumed, tablets were being produced with low dissolution rates Why?

4 The Quick Fix Is Tempting “I’ve seen the same issue in another process” “The solution is obvious” “Let’s brain storm solutions” “Management is on our backs, we don’t have time to turn this into a research project” Watch out…when the issue is big, confusing, or frustrating, use a systematic approach and use data to keep intuition in check

5 Critical Elements of a Root Cause Investigation A Thorough Description of the Event Subject Matter Expertise Process Map and Access to Process Data Expertise in Data Analysis and Interpretation Formal Problem Solving Approach Project Management Skills Scientific Method, Skepticism, Creativity

The Manufacturing Process Granulation Excipients Active Ingredient Water Dry Mill Lubricate Tablet Remove Excess Moisture Reduce Size Improve Flow Properties Press Lubricate Granules Into Tablets Solid Mixture

7 Intuitive Leaps Create Myth The active pharmaceutical ingredient changed, of course! But… API Lot vs. Dissolution API Lot % Dissolved FACT Two Lots of API Associated With Low Dissolution…But High Variability Also Raises The Possibility of Variability in the Manufacturing Process. The active ingredient “myth” haunted the team throughout the investigation!

8 Data Visualization: Round 1 What Changes or Factors Are Associated With The Change In Dissolution Rates? 70 Factors For 19 LotsWere Examined With Spotfire XY plots 14 Factors Were Identified As Possibly Being “Associated” With Low Dissolution Rates

9 First Root Cause Candidates RESULTS Broad Candidate List For Root Cause Because of Small Data Set (Low Signal to Noise Ratio) Peak Granulation Power Correlation and Subject Matter Expert to Recognize Importance Were Critical

Granulation Peak Power Amperes Required To Maintain Constant Mixing Speed

11 Granulation Peak Power And Tablet Dissolution Rate Granulation Peak Power Correlated With Tablet Dissolution 10 and 20 mg Tablets Have Identical Manufacturing Processes Dissolution-Power Correlation of Two Strengths Quite Similar HYPOTHESIS Dissolution rate might be set during granulation Combined data set of 10 and 20 mg tablets could help clarify factors

12 Insight With More Data Considerable Lot-to-Lot Variation Existed Before Incident Groupings of Dissolution Rates Near Failures Occurred In Previous Batches At This Point Active Ingredient Is Still Suspected

13 Data Visualization: Round 2 Reasonable Root Cause Candidates Found

14 Confirming The Root Cause Subject Matter Expertise Pointed To Excipient 2 As Having A Likely Influence On Granulation Peak Power and Dissolution Analytical Work Demonstrated How Excipient 2 Varied Granulation With “Good” and “Bad” Excipient Confirmed Its Role In Dissolution Still Collecting Data To Confirm Active Ingredient Is Not the Cause!

15 Conclusion Data visualization key to focusing investigation Usefulness of data analysis can be limited by size of data set and variation in the data Debunking myth saps resources – judiciously propose hypotheses Use a balance of subject matter expertise, data analysis and intuition