Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tablet Hardness
Abstract
:1. Introduction
2. Materials and Methods
2.1. Product Summary
2.2. Process Summary
2.3. Data Collection and Organization
- Batch conditions data (one row per batch): active ingredient batch particle size distribution, granulation water quantity, granulation nozzle type, wet discharge intensity, wet discharge time, drying intensity, inlet air humidity, average tableting speed, average feeder speed, and average compression force.
- Batch evolution data (multiple rows per batch): process variables recorded at regular time points during granulation, wet discharge, and drying.
- Product quality data (one row per batch): granule and tablet quality attributes.
2.4. Data Analysis
2.5. Effectiveness Check of Improvement Actions
- 1.
- Define and Measure phases: batches belonging to campaigns from 2 to 5, where the increased hardness variability and tendency for results close to the lower limit and below it was observed; these were the batches that defined the problem statement and triggered the extensive investigation.
- 2.
- Analyze and Improve phases: batches belonging to campaigns from 6 to 14, where improvement actions were gradually implemented based on the outcome of the statistical analysis performed.
- 3.
- Control phase: additional 46 batches not included in the initial models; part of campaigns from 15 to 19 where all improvement actions were in place.
3. Results and Discussions
3.1. Influence of Process Evolution on Core Tablet Hardness
3.2. Influences of Active Ingredient, Granulation Conditions, and Intermediate Product Properties on Core Tablet Hardness
3.3. Influences of Tableting Process on Core Tablet Hardness
3.4. In-Depth Analysis of Batch Groups Based on Most Significant Process Conditions
3.5. Long-Term Effectiveness of the Proposed Control Strategy
- Waste reduction:
- ○
- Fewer product losses during the prolonged set-up needed for lower hardness batches.
- ○
- Significantly reduced risk of eroded tablets after film-coating, leading to visual sorting for the removal of defective tablets
- ○
- Significantly reduced risk of broken tablets during packaging caused by the low hardness
- Reduction in inter-batch variability through defining more standardized processing conditions.
- Process efficiency improvement through increased tableting throughput, as batches with medium and high hardness can be processed at a higher tableting speed.
- Improved product quality at core tablets in-process control level through a reduction in the deviation rate for hardness values below the acceptable limit.
- Cost reduction through a reduction in overall processing and batch release times.
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
References
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Variable Type | Attribute (Unit of Measure) | Data Source | |
---|---|---|---|
Raw material | API | Particle size distribution (PSD) by laser diffraction (d0.1; d0.5; d0.9) (μm) | Certificate of analysis; one value/batch |
Process parameters | Wet granulation | Mixer speed (rpm) | Equipment report; Datapoints at 30 s interval |
Torque value (Nm) | |||
Quantity of granulation water (kg) | Batch records | ||
Nozzle used for liquid addition (type 1 and type 2—Figure 1) | Batch records | ||
Wet granulate discharge | Inlet air flap position (%) | Equipment report; set point per time interval | |
Wet discharge intensity index (%; WDi) (low values represent high intensity) | Computed from above variable as weighted average of the various the set-points during a batch with their corresponding durations | ||
Wet discharge time (min) | Equipment report | ||
Process parameters | Granule drying | Inlet air flowrate (m3/h) | Equipment report; rounded actual value per time interval |
Drying intensity index (m3/h; Di) (low values represent low intensity) | Computed from above variable as weighted average of the various the set-points during a batch with their corresponding durations | ||
Inlet air humidity (g/kg) | Equipment report | ||
Drying time (min) | Equipment report | ||
Tableting | Tablet press model (TP1/TP2) | Batch records | |
Speed (tablets/hour) | Batch records; data points at 1 h interval | ||
Feeder speed (rpm or %) | |||
Pre-compression force (kN) | |||
Compression force (kN) | |||
Granule properties | Final blend | Particle size analysis by sieving (% retained on 1000; 500; 250; 125 microns sieves and % of fines below 125 microns) | Batch records |
Bulk density (g/mL) | |||
Loss on drying (LOD) (%) | |||
Core tablet properties | Average hardness/batch (N) |
Nr. | Y | X | R2X (cum) | R2Y (cum) | Q2 (cum) | RMSECV |
---|---|---|---|---|---|---|
BLM1 | Tablet hardness (tablet H) | API particle size distribution Granulation pp Water quantity Wet discharge pp Drying pp Granule properties Tableting pp | 0.379 | 0.706 | 0.646 | 11.162 |
BLM2 | Tablet hardness (tablet L) | 0.593 | 0.807 | 0.665 | 9.827 | |
BLM3 TP1-H | Tablet hardness | Granulation conditions Granulation final torque Water quantity Absolute inlet air humidity (drying) Sieve size Granule properties Tablet press type Tableting feeder speeds (%) | 0.644 | 0.835 | 0.635 | 10.203 |
BLM4 TP2-H | 0.446 | 0.765 | 0.678 | 10.572 | ||
BLM5 TP1-L | 0.945 | 0.999 | 0.841 | 4.996 | ||
BLM6 TP2-L | 0.448 | 0.814 | 0.682 | 9.994 |
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Mathe, R.; Casian, T.; Tomuta, I. Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tablet Hardness. Pharmaceutics 2025, 17, 213. https://doi.org/10.3390/pharmaceutics17020213
Mathe R, Casian T, Tomuta I. Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tablet Hardness. Pharmaceutics. 2025; 17(2):213. https://doi.org/10.3390/pharmaceutics17020213
Chicago/Turabian StyleMathe, Rita, Tibor Casian, and Ioan Tomuta. 2025. "Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tablet Hardness" Pharmaceutics 17, no. 2: 213. https://doi.org/10.3390/pharmaceutics17020213
APA StyleMathe, R., Casian, T., & Tomuta, I. (2025). Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tablet Hardness. Pharmaceutics, 17(2), 213. https://doi.org/10.3390/pharmaceutics17020213