Identification of CPPs based on CQAs & Mechanistic Process & Product Understanding: A Case Study

Transcription

1 Identification of CPPs based on CQAs & Mechanistic Process & Product Understanding: A Case Study Ajit S. Narang, Ph.D. Bristol-Myers Squibb, Co. 2 nd FDA/PQRI Conference on Advancing Product Quality Bethesda, MD October 5-7, 215 1

2 Overview Identification of Drug Product CQAs and CPPs: Prior knowledge Risk assessment Product & process knowledge Correlational studies, e.g., DoE Mechanistic studies, e.g., degradation kinetic modeling Case study: Brivanib Alaninate tablet development, wet granulation Stability risk assessment: impact of residual water Control strategy during processing Bioavailability risk assessment Drug-excipient binding interaction Drug self-association Process monitoring and control strategy PATs: FBRM probe, DFF sensor, & NIR

3 Bioavailability Pharmaceutical Development Stability Manufacturability

4 Composition of Brivanib Alaninate Tablets Ingredient % w/w Intra-granular Brivanib alaninate 5 Hydroxypropyl cellulose 4 Croscarmellose sodium 3 Microcrystalline cellulose 23.5 Water for Granulation 46 Extra-granular Crospovidone 3 Microcrystalline cellulose Colloidal silicon dioxide.5 Magnesium stearate 1.25 Opadry reddish brown or yellow 3% (weight gain) Tablet strength: 4 mg (8 mg core tablet weight) 4

5 Manufacturing Process Flowchart Add BMS , Intra-granular MCC, HPC and CCS Mix High Shear Mixer Granulation High Shear Mixer 25 L Fuji high shear granulator Wet Mill Compress into Tablets Fluid bed drying Add EG MCC, xpvp, Cab-O-Sil Add Mg Stearate and blend Bin Blender Milling 5

6 QbD Methodology RA Perform product risk analysis to identify CQAs PPs & MAs List relevant material attributes and process parameters that can potentially impact CQAs Unit Ops Perform process risk analysis to identify attributes and parameters to be studied DoE etc. Conduct development studies CQAs & CPPs Identify critical attributes and parameters CS Establish control strategy 6

7 Formulation Ruggedness Study Design Key Responses Granulation: -Particle size -Flow -Compaction properties -Adhesion tendency Tablets: -Visual defects -Dissolution -Friability -Disintegration 4.5% CCS 1.5% 1.5% 2 3 split plot design Center Point 4.5% HPC 1.5%.5% Mg Stearate 2.5 kg batch size

8 Design Space Studied During Process DoE High Shear Granulation 49% Water Level Wet Massing Time 1s 5s 44% 3.6m/s 6m/s Impeller Tip Speed

9 Quality Attributes Potency Content uniformity Appearance Impurities Dissolution Process Parameters Each unit operation Interactions Mechanistic process understanding - Basis of effect of process parameters In-process material attributes Mechanistic product understanding

10 RA: Tablet Potency & Content Uniformity 1

11 RA: Tablet Appearance 11

12 RA: Impurities 12

13 Water Content: Hydrolysis of Prodrug Rate of hydrolysis % RH/1 Moisture in core tablets posses long term stability risk Brivanib Alaninate is moisture sensitive Degradation rate increases when the moisture level is high This poses a risk to stability over long periods of time Over short periods of time (~24h) Brivanib Alaninate is stable in the presence of water Control of tablet moisture before packaging is essential to slow degradation rate 13

14 Target Moisture Level.2 Rate of formation of Parent (%/day) Moisture Content (%wt. gain/wt. dry) Acceptable Degradation Rate (Parent below limit for 2 years) % RH/1 Final Moisture Target Parent Formation Rate Desorption Isotherm 25 C %RH/1 14

15 Moisture control option 1 Humidity control method Low humidity processing environment prevents moisture pickup Water added for granulation Granulation dried to <1.3% Low humidity environment Low humidity environment Low humidity environment Alu bags High Shear Mixer Wet Granulation Fluid Bed Drying Blending and Compaction Film Coating Packaging 15

16 Moisture control option 2 Coating control method Uses coating step to remove moisture absorbed during previous process steps Does not require current facilities to be modified Water added for granulation Granulation dried to <1.3% Potential for moisture pickup Moisture driven off during coating Limits: Preheating: <1.6% Final: <1.8% Low humidity environment Alu bags High Shear Mixer Wet Granulation Fluid Bed Drying Blending and Compaction Film Coating Packaging 16

17 RA: Dissolution Effect of Material Attributes & Process Parameters 17

18 RA: Dissolution Impact of Material Attributes API particle size affects drug release rate. 18

19 RA: Dissolution: Wet Granulation Process Parameters DoE study enabled the identification of process parameters that impact product dissolution. 19

20 RA: Dissolution Impact of Process Parameters w/material Attributes Dissolution of tablets manufactured with worst case combination of API particle size & wet granulation process parameters 2

21 RA: Dissolution: Material Attributes Mechanistic Basis of Effect of Process Parameters Identification of in-process MAs that impact DP Qas enables focus of control strategy development. 21

22 PAT Tools to Support Control Strategy NIR for Granule Water Content during Fluid Bed Drying Real-time measurement of granule water content during drying. 22

23 Lasentech FBRM C35 Probe Chord Length Rotating focused-laser measures chord length Proven technology for particles suspended in liquids Measures particles in contact with probe sapphire tip Probe placed directly in solution or powder flow Probe Tip Enlargement

24 1% HPC Square Weighted (Mass) % HPC-Dry A: Water - 4% HPC - 1% PH12 Chord Length Distribution by FBRM 5% HPC 3% HPC-Dry B: Water - 4% HPC - 3% PH Time (minutes) 3% HPC Chord Length (um) 5% HPC-Dry C: Water - 4% HPC - 5% PH12 1 Square Weighted (Mass) Square Weighted (Mass) Time (minutes) Test 1: 1% HPC batch 1 Chord Length (um) 15 Time (minutes) Chord Length (um) 1 Test 2: 3% HPC batch Test 3: 5% HPC batch 24

25 Drag Flow Force (DFF) Sensor (i) (ii) (iii) Measures wet mass consistency that correlated with granule densification/porosity 25

26 Number of Peaks 1% HPC % HPC-Dry A: Water - 4% HPC - 1% PH12 DFF Sensor Peak distribution statistics 5% HPC 3% HPC-Dry B: Water - 4% HPC - 3% PH Time (minutes) 3% HPC Force (N) 5% HPC-Dry C: Water - 4% HPC - 5% PH12.1 Number of Peaks Number of Peaks Time (minutes) Force (N).1 15 Time (minutes) Force (N).1 Test 1: 1% HPC batch Test 2: 3% HPC batch Test 3: 5% HPC batch

27 Control Strategy 27

28 Acknowledgements Sherif Badawy Kevin Macias Valery Shevrev & Vadim Stepnaiuk, Lenterra, Inc. Tim Stevens Sailesh Varia Dilbir Bindra Keirnan LaMarche Ganeshkumar Subramanian Judy Lin Pankaj Shah

29 Selected Publications and Acknowledgements Panakanti R and Narang AS (212) Impact of excipient interactions on drug bioavailability from solid dosage forms. Pharm Res 29: Narang A, Yamniuk A, Zhang L, Comezoglu SN, Bindra DS, Varia S, Doyle M, and Badawy S (212) Reversible and ph-dependent weak drug-excipient binding does not affect oral bioavailability of high dose drugs. J Pharm Pharmacol 64: Badawy SIF, Narang AS, LaMarche K, Subramanian G, and Varia SA (212) Mecahnistic basis for the effects of process parameters on quality attributes in high shear wet granulation. Int J Pharm 439: Narang AS, Badawy S, Ye Q, Patel D, Vincent M, Raghavan K, Huang Y, Yamniuk A, Vig B, Crison J, Derbin G, Xu Y, Ramirez A, Galella M, and Rinaldi F (215) Role of self-association and supersaturation on oral absorption of a poorly soluble weakly basic drug. Pharm Res 32: Badawy SIF, Narang AS, LaMarche KR, Subramanian G, Varia SA, Lin J, Stevens T, and Shah PA (215) Integrated application of quality-by-design principles to drug product development: case study of brivanb alaniante film coated tablets. J Pharm Sci (under revision). Narang AS, Sheverev VA, Stepaniuk V, Badawy S, Stevens T, Macias K, Wolf A, Pandey P, Bindra D, and Varia S (215) Real-time assessment of granule densification in high shear wet granulation and application to scale-up of a placebo and a Brivanib Alaninate formulation. J Pharm Sci 14: Narang AS, Sheverev V, Freeman T, Both D, Stepaniuk V, Delancy M, Millington-Smith D, Macias K, and Subramanian G (215) Process analytical technology for high shear wet granulation: wet mass consistency reported by in line drag flow force sensor is consistent with powder rheology measured by at line FT4 powder rheometer. J Pharm Sci (under revision).