Case Study: Implementation of Design Space Concepts in Development of an Active-Coated Tablet Robert A. Lipper, Ph.D., Divyakant Desai, Ph.D., San Kiang, Ph.D. Bristol-Myers Squibb Pharmaceutical Research Institute Real World Applications of PAT and QbD in Drug Process Development and Approval – September 11, 2006 – Arlington, VA
QbD is about connecting the molecule and the patient .
Science-based product/process design begins with the API molecular entity and is geared to meet patient needs for pharmacotherapy which is safe, effective, convenient and of consistently high quality.
All products are designed and developed to be of high quality ; QbD provides a structured framework for documenting and presenting development rationale, experience and knowledge of the formulation and the process, and to ensure manufacture of products consistently fit for patient use.
HPMC- and PVA-based coating formulations were evaluated.
Opadry II, a PVA-based coating formulation, provided the best stability
Tablets were most stable when pH of the coating suspension was adjusted to around 2 for all three layers
Three layer-coated tablets were more stable than those coated with two layers (i.e., omission of either inner or outer layer decreased stability)
Elements of QbD: Preliminaries to Studying the Coating Process
Placebo cores are subjected to 100% on-line weight check; controlled to 200 mg ± 2%.
A round biconvex tablet shape was chosen for durability, ease of coating and improved content uniformity.
The process for dissolution of API in the coating vehicle was qualified using a UV fiber-optic probe.
A re-circulation loop was designed in the tank to prevent sedimentation of pigments in the coating dispersion. A Raman probe was used to confirm the homogeneity of the coating dispersion. (Mixing design was optimized before undertaking spray characterization.)
Brooks air flow controllers are used for monitoring atomization air feed into the spray guns.
Proprietary Information In-Line Raman Monitoring for Coating Suspension System Design
Identify spray system hardware, configuration and operating parameters to produce:
Flat, focused spray pattern with uniform droplet size and intensity (narrow RSD)
Uniform and stable spray cone
Characterize spray with two-camera imaging system (Off-line)
Profile camera measures spray cone angle, spray intensity, and spray axis angle
Droplet camera measures droplet size distribution (DV50 and DV90), mean droplet speed, and droplet density
Effect of various parameters (Off-line)
Nozzle operation under controlled air flow rates
Solid content in coating suspension
Comparison of Nozzle Types I and II : Selection criteria: flat, focused spray pattern with uniform droplet size and intensity. Cone angle of (A) Type I and (B) Type II nozzles Effect of Nozzle Type A B
Cone angle, droplet size, and droplet density are affected by suspension formulation (API-to-polymer ratio) and flow rate. Spray parameters are customized to assure content uniformity at different API-to-polymer ratios.
Droplet size and cone angle decrease with increased air flow rate
Too high a ratio of pattern air to atomizing air can create a hollow spray cone which (in this case) would adversely affect content uniformity
Air volume is much preferred over air pressure to control the droplet size distribution and pattern of the spray, and is independent of coater scale or “plumbing”
Spray Characterization: Summary
Coating Control: Use of Raman to Monitor the Inner Layer A U Wave number (cm-1) Opadry A.U. Coating Progress Tablet Core
Setup of Raman Probe for In-Line Coating Monitoring
Pan size: 36”
Pan speed: 12 rpm
Distance from the bed: ~ 4 inches
Scan time: 24 sec
Coating Kinetics of the Inner Layer Followed by In-Line Raman Spectroscopy El Hagrasy, A., Chang S-Y., Desai, D. and Kiang, S. American Pharmaceutical Review 9(1):40-45 (2006) Bed Temperature Adjustment Coating Initiated
First coating layer can be monitored using a Raman probe (feasible to do at-line as well) and/or weight gain
Second coating layer (active layer): API deposition can be monitored using weight gain and/or an off-line rapid HPLC or UV fiber-optic method
Third coating layer can be monitored using an off-line Raman probe and/or weight gain
The process has been successfully scaled using 24 inch, 36 inch, 48 inch, and 60 inch Compu-Lab coaters (Batch sizes: 14 to 215 kg)
Classification of Process Variables PAR = Proven Acceptable Range; NOR = Normal Operating Range; EOF = Edge of Failure *If frank failures are observed, EOF should be estimated Inherently Variable Tightly Controllable Non-Critical Critical Fix Fix, determine PAR (EOF*) Determine target, NOR and PAR Determine target, NOR, PAR (EOF*)
Formulation and Process Optimization DOE Design: API Film Coated Tablets 2^(5-1) Fractional Factorial with 3 Center Points Designs – 19 Runs
Creating the Process Design Space: Process Parameters Studied Screening for Parameter Ranges for Optimal Content Uniformity Atomizing/Pattern Air Volume Air Volume Inlet Air Temperature Spray rate % API in suspension API/Opadry Ratio Spray rate % API in suspension Critical Parameters: API application rate was most critical for content uniformity . 60 75 0.75 5 0.75 8 1:1 1:8 200 300 525 600 50 55 60 105 DOE
Summary of Potency and Content Uniformity Results of Second Layer Coated Tablets
Based on risk assessment around the chosen formulation and processing approach, content uniformity and potency of tablets are considered to be the most critical product quality attributes
Variables were systematically analyzed for their potential to influence the critical quality attributes
Controlled experiments including DOE were conducted around the key variables to establish reliable operating ranges
The process has been shown to be capable of consistently achieving content uniformity RSD of 2.8-3.9%
Utilization of Design Space for Tech Transfer Coating Suspension Homogeneity Nozzle Characterization Coating Process
Optimal design of mixing tank
Real-time Imaging Technology
Final Product Coating Suspension Homogeneity Nozzle and tablet flows Characterization
Optimization of spray pattern
Specify process parameters to enhance tech transfer
Real-time monitoring of the coating kinetics
Effect of process variables on coating uniformity
Fast check of coating uniformity
Develop an index of mixing efficiency
Determination of coating end point
Minimize risk of sedimentation
Continuous verification of TiO 2 content
DEM and PBE models are being developed to predict coating uniformity and coating weight in production coater
Raman / NIR
DEM-1M model PBE-2 zone model RSD model for Production Coater Workflow for Coating Process Model PAT applications Thermodynamics & mass transfer Formulation 1.Predict RSD 2.Reduce DoE batches 3.Provide added insight to design space for CMC Nozzle optimization Feed tank optimization and scale-up At-line uniformity analysis tablet velocity characterization
A product design approach was chosen to address the chemical instability of the API in traditional formulations
A clear and complete process understanding is being created during product development to assure process robustness
Several PAT techniques, some with potential for in-line process control, are being utilized to develop a deeper process understanding
Reliable operating ranges have been established for key process variables
Process understanding gained through the QbD approach is being leveraged in scale-up and technology transfer
Project Leads: Divyakant Desai San Kiang Formulation and Drug Product Process: William Early Charles Van Kirk Howard Stamato Srinivasa Paruchuri Sanjeev Kothari API Process: Steven Chan John Korzun Analytical R&D: Harshad Patel Leon Liang Xujin Lu PAT: Arwa El-Hagrasy Don Kientzler Wei Chen Shih-Ying Chang Technical Operations: Howard Miller Megan Schroeder DEM modeling: Fernando Muzzio (Rutgers University) Regulatory Sciences: Steve Liebowitz Acknowledgements
Formulation and Process Optimization DOE - API versus Polymer Amounts -- Each batch was coated up to 10-mg potency. Tablets corresponding to 2.5-mg and 5-mg were collected at the appropriate times (theoretical weight gain) and results were treated separately. -- Effectively, three separate DOEs were performed for the three strengths: 2.5 mg, 5 mg and 10-mg, respectively. 20 16 2 1:8 20 16 4 1:4 16 8 8 1:1 Total Solids Dissolved / Suspended Opadry II White API % w/w in Coating Suspension API/Polymer Ratio 10 10 5 5 2.5 2.5 40 10 20 5 10 2.5 80 10 40 5 20 2.5 Opadry II White API Opadry II White API Opadry II White API 10 mg Tablets 5 mg Tablets 2.5 mg Tablets Amount per Tablet (mg)
Representative Tablet Formulations 7 mg Color D 7 mg Color C 7 mg Color B 7 mg Color A Opadry II Color 200 mg 200 mg 200 mg 200 mg Inert Core Outer Layer 10 mg 20 mg 20 mg 8 mg Opadry II White 10 mg 5 mg 2.5 mg 1 mg API Middle Layer 6 mg 6 mg 6 mg 6 mg Opadry II White Inner Layer 10 mg 5 mg 2.5 mg 1 mg Ingredient