Connuousmanufacturingoftabletsandcapsules …...2 An industry in transition • Change drivers –...
Transcript of Connuousmanufacturingoftabletsandcapsules …...2 An industry in transition • Change drivers –...
Con$nuous manufacturing of tablets and capsules The Emerging Paradigm
By Fernando Muzzio, Dis$nguished Professor, Rutgers University
Director, NSF Engineering Research Center on Structured Organic Par$culate Systems
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An industry in transition
• Change drivers – Patent expirations – Biologicals and biosimilars – Emerging markets
• Game changers in development – Outsourcing, re-shoring, CROs & CMOs
• Manufacturing megatrends – Continuous manufacturing – Personalized/precision medicine
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Why Continuous Manufacturing? • Reduced cost
• Smaller equipment • No scale up • Faster development • Great savings in API and excipients during development • Lower cost of quality assurance • Reduced processing @me
• Increased robustness and reliability, beGer quality • Flexible batch size (no validated batch size, can adjust to market demand in real @me) • BeJer quality control • Meaningful PAT and integrated closed loop control: real @me release • Enhanced containment and environmental control • More uniform processing: Prevented segrega@on and agglomera@on • No wasted batches
Continuous Manufacturing Landscape - today
• FDA actively promoting it (Advanced controls and enhanced process understanding required)
• Most brand companies have implemented systems • Pfizer, GSK, J&J, Vertex, Novartis, Abbvie, Lilly, BMS
• FDA has multiple filings
• Generic companies (Teva, Actavis, Dr. Reddy) getting involved • One domestic manufacturer in China (Hisun) has announced plans to implement
a CM factory in south China
• Leading contract manufacturer (Patheon) is building a GMP facility
• Equipment companies demonstrating enormous interest • GEA, Bosch, Glatt, Bohle, Hosokawa, Fette, Lodige, Gericke, Ktron, Schenk, others
• Academia actively involved • Rutgers & ERC – since 2002 – focus on solid dose manufacturing
• MIT – Novartis project – focus on end to end implementation
• RCPE (Graz, Austria) – focus on HME
• Ghent - focus on wet granulation
• CMAC – UK – focus on API and crystallization
Summary of Rutgers Accomplishments in Continuous Manufacturing
• Promoted FDA support for CM
• Demonstrated feasibility – implemented first integrated line (2008) and built first closed-loop control line (Inspire, 2011)
• Developed approach to minimize feeder variability during refill
• Developed RTD framework for design of continuous mixers and for traceability of materials in integrated line
• Developed integrated flowsheet modeling methodology
• Demonstrated integrated closed loop control of feeders, RC, mixers, TP
• Integrated PAT approach for continuously moving powder
• Demonstrated arrested segregation in DC CM
• Created Integrated Product/Process Development Paradigm
Current State of Solid Dose CM Technology
• Integrated lines available from multiple vendors • GEA Consigma line – mechanically integrated, standardized
• Glatt, Bohle also offering integrated systems
• Equipment components available from many sources • Feeders: Ktron, Gericke, Schenk, Brabender, others
• Mixers: Glatt, Lodige, Hosokawa, Gericke
• Granulators & driers: Glatt, Lodige
• Tablet presses, roller compactors, capsule filling, extruders, mills – same as batch processing
• Control systems: Siemens, Emerson, equip. vendors
• PAT: mainly NIR and PSD
• Missing or underdeveloped components – see next slide
Research Needs in Continuous Manufacturing • We need effective tools to measure ROI and NPV • Modeling methods to support integrated design, risk assessment,
optimization, and process control need further work • Distributed control systems not yet standard • Continuous functional coating not yet available • PAT instrumentation incomplete
• Powder density • Tablet/capsule Content Uniformity • Tablet dissolution
• Low flow rate systems unavailable • Capsule products • Inhalables • Hot Melt Extrusion • Pilot lines for development
• Role of material properties and process parameters not fully understood • Regulatory expectations unclear • Standard filing and review documents unavailable
• Increased regulatory expectations regarding process understanding and control will drive adoption of CM with advanced controls
• Research pharma will get increasingly involved via new and existing products
• Generics will get involved following Teva
• Chinese and Indian manufacturers will get involved following Hisun
• CMOs will adopt the technology to supply customers
• Our prediction: 50% penetration by 2025 – accounting for: • $300 billion per year worldwide in market value of manufactured products
• $100 billion in investments required to upgrade manufacturing systems
• New excipients, new formulation modalities, new technology platforms
Continuous Manufacturing Market: The next 5 years
Process map Three main routes to solids: -‐ direct blending -‐ dry granula$on -‐ wet granula$on
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Process map Three main routes to solids: -‐ direct blending -‐ dry granula$on -‐ wet granula$on
Slide 10
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API
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EX
Material Proper,es-‐Process Parameters Interrela,on: Rutgers Con,nuous Line
Tablet Press
Blender
Feeders
Mill
Modeling in Pharmaceutical Development
The goal is to model pharmaceu$cal processes in silico and use these tools for op$miza$on
Integrated Process Model “Flowsheets”
Reduced Order Model
Opera,ng Parameters & Design
Material Proper,es
Unit Ops Models
e.g., Flow, Bulk Density, Angle of Repose
y = f (x,a,t,m,n)dydt
= g(x,a,t,m,n)M
M
e.g., Feeders
min f (x)st. h(x) = 0 g(x) ≤ 0
Op,miza,on
Predic,ve Modeling
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1 1
k k
i i ii i ij i ji i i j
y x x x xβ β β β ε= = <
= + + + +∑ ∑ ∑∑
Interrela,on between Process Parameters and Material Proper,es
Direct Compression
• More properly termed “direct blending” • Can go into tablets, capsules, vials, etc.
• Feeding and blending is the heart of the process
• Ques$ons: • Can we achieve homogeneity? • Does the blend flow? • S$cking (electrosta$cs?) • Segrega$on?
Direct Compaction for Segregating Systems
• Continuous blenders exhibit superior quality to batch blenders
Formulation d50 (µm) Bulk Density (g/cc)
Mustard 1298 0.7103 Microcrystalline Cellulose PH 101
50 0.3
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
1 5 10 30 50
Rela,v
e Stan
dard Devia,o
n
Mustard concentra,on (wt %)
Mixing Performance
Batch (experimental)
Batch (sta$s$cal)
Con$nuous (experimental)
Con$nuous (sta$s$cal)
Critical Material Properties
• Particle size and size distribution (tablet density, porosity, cohesion)
• Powder Density (flow, weight)
• Cohesion (flow, weight uniformity)
• Moisture Content
• Hydrophobicity (wetting)
• Electrostatics (flow, sticking, agglomeration)
• Segregation tendency (composition)
• Shear sensitivity • Hydrophobicity (overlubrication)
• Electrostatics (dynamic charging)
• Attrition
A Standardized Development Approach:
• Create a decision tree for DCCM - Question-driven, supported by
- Materials characterization - Models - Table-top Unit op tests - Minimum number of confirmation experiments in the
integrated line at desired conditions - Useful for selecting ingredients - Enables fast screening of formulations (goal: 1 week turn
around) - Uses minimum amounts of material - Framework for accumulating knowledge
Tablet Press
Lubricant
Feeders
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API
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Mill
Cri,cal ques,ons to process in DC line
Blenders
Q1: Can we feed each ingredient at the required flow rate?
Q3: Can we “delump” all agglomerates?
Q4: Can we achieve blend homogeneity?
Q5: Are blend flow proper$es good enough to support Weight Uniformity?
Q6: Can we get tablets at target hardness and dissolu$on at reasonable high flow rate?
Q2: Can we feed each ingredient with variability below certain threshold?
Q1: Can we feed each ingredient at the required flow rate?
• Predict feeder performance using the regime map. The feeder performance (op$mal tooling, etc.) of each ingredient can be predicted through the process knowledge of its similar materials.
Q3: Can we delump?
• Approach: -‐ Observa$ons in feeder -‐ Surface energy of ingredients before feeding -‐ Impedance/Dielectrophoresis tes$ng of materials before and
afer feeders -‐ Sieving/Icon tes$ng afer feeders -‐ PCA/PLS analysis
Observa$ons in feeders
• S$cking inside bowl • Bearding • Changes in flow or density during feeding • Agglomera$on during feeding
API 2 API 3 APAP
Silicon Dioxide at feeder outlet
Surface Energy: Inverse Gas Chromatography • Reten$on Time is
associated with Solid-‐Gas Interfacial Energy.
• Non-‐Polar component with non-‐polar gases.
• Polar component is the difference obtained with polar gases.
Lactose
Tribo-‐Electrosta,cs • Feeder jamming • Par$cle Agglomera$on • Par$cles s$cking to walls of
container • Flow problems • Tablet weight variability • Segrega$on
Problems arising form par,cle charging
• Material flows from a hopper, feeder, mill, or blender into a faraday cup
• Charge is monitored versus mass
LaMarche, Keirnan R., et al. "Electrosta$c charging during the flow of grains from a cylinder." Powder Technology 195.2 (2009): 158-‐165.
Cellulose adhered to the end of a rod
Oscilloscope
Amplifier
Frequency generator
Faraday Cup
Impedance Mesaurement
0
5000000
10000000
15000000
20000000
1 10 100 1000 10000 100000
Frequency (Hz)
Impe
danc
e (o
hms)
Display on Oscilloscope
Impedance Measurement
Amplifier ElectrodeTeflon
Isolation
Powder
Grounded Cup
TriaxConnector
Oscilloscope
1 kΩ
Amplifier ElectrodeTeflon
Isolation
Powder
Grounded Cup
TriaxConnector
Oscilloscope
1 kΩ
API Excipient
0 5 10 15 20 25 30 35 40 45 500
0.2
0.4
0.6
0.8
1
Time (Sec)
E(t)
(1/s
) Pulse
0 50 100 1500
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
Time (Sec)
E(t)
(1/s
)
Axial motion and dispersion
Q4: can we achieve blend homogeneity?
Q5: Are blend flow proper,es good enough to support Weight Uniformity??
Change formula$on
Characteriza,on Techniques: Flow Proper,es
• FT4 Shear Cell: cohesion, UYS, MPS, and flow function
• FT4 Stability/ Variable Flow Rate
• Basic Flowability Energy, Stability Index, Flow rate index, SE
• FT4 Compressibility: bed density as a function of applied normal stress, compressibility index
Material Proper,es-‐Process Parameters Interrela,on Lubricated Blend
Raw Material Proper,es (RMP)
Cohesion1. Compressibility Electrosta,cs Surface Energy
PSD
Process Parameters
RPM1a
RPM1b
Process Parameters
RPM2 (Mill)
Screen Size
Process Parameters
RPM3 (Blender)
Intermediate Material Proper,es (IMP)
Lubricity4 Compactability4.
Cohesion4 Agglomera,on4
Blend Homogeneity4 Bulk Density4
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API
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Lubricant
Feeders
Mill
Process Parameters
RPM5 (Feed Frame)
RPM6 (flow Rate)
Chute Height (CH)
Thickness Gap (ThG)
Pre Compac$on (PC)
Fill Cam [FC]
Product Material Proper,es (RMP)
Thickness Weight Variability Density (porosity) Content Uniformity
Hardness Dissolu,on
Product
3/2/16
Tablet Press
Blender
Feeders
mill
API
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RTR Sensing Approach
Content/Density Blend Uniformity
NIR, Raman
LT
Thickness
Density
US
Hardness
NIR
Dissolu,on (check)
Feed forward control
Force
Weight
Compression Gap
Cross-‐check
Content (check)
Moving Forward
• C-SOPS focusing even strongly on continuous manufacturing
• International Institute for Advanced Pharmaceutical Manufacturing (C-SOPS+RCPE+CMAC) has been launched
• Major Partnership between Rutgers and Janssen ($6 million in 2015) open for participation to other companies
• Integra Manufacturing Systems - a new company that provides support to the industry in implementing CM
• Major grant from FDA to Rutgers ($4 million) to develop science-based regulation for continuous manufacturing (Materials, RTR, Sensing and Control)
• At J. Woodcock’s request, C-SOPS has organized a regulatory working group that is developing a proposed CM guidance
Proposed new FDA/BARDA Standardiza$on Project:
• Accelerate product and process development by: - Create a “Integrated development pathway” - Decompose manufacturing trains into smaller standard
modules - Standardize the equipment, the formulations, the control
requirements, and the development process
Goals • Create Integrated CM plaoorms that enable:
– Easy adop$on of CM – Fast development of products and processes – Low cost, high quality manufacturing
• Create knowledge based needed for: – Fast and reliable implementa$on of CM plaoorm – Equipment transla$on – Science-‐based regula$on – Ability to respond quickly to medical emergencies
• Conduct case studies to: – Demonstrate effec$veness of the technology – Provide implementa$on examples demonstra$ng that products and processes
can be developed in parallel in less than 8 weeks.
A Comprehensive plaoorm includes:
• A Standard Pathway for development and approval: Integrated Pharmaceu$cal Product and Process Development template that enables rapid product development and rapid regulatory assessment
• Standardized equipment that is fully understood and easily and flexibly configured (modular approach) and integrated with standard communica$on protocol (OPC)
• Standard formula$ons that can be applied to a wide range of APIs within a known range of material proper$es
• Standardized modular sensing and control infrastructure that enable effec$ve process control
• Performance standards and methods for specifying and modifying material proper$es of APIs and excipients to enable desired product CQAs and required process performance
Developing the Standard Pathway
• Define a generic template for integrated product/process development (i.e., “what needs to be done”)
• Define DOE methods, supported by predic$ve models and materials databases, for simultaneous development of product, process, and analy$cal/control methodology (i.e., “how does it get accomplished”)
• Specify standard, model/sta$s$cally-‐based tes$ng requirement needed to demonstrate product quality, process performance, and real-‐$me quality assurance (i.e., “how do we know that it works”)
• Implement well defined, shared expecta$ons and standards between industry and regulators (i.e., “if it works, it should be approvable”)
Current Batch Development Paradigm
Formula$on batches ~ 1 kg Formula$on
Process Dev. Batches ~ 5 kg Process
Analyt. Dev. batches ~ 5 kg Analy$cal Method
Scaled up batches – 30 Kg to 1000 kg Scaled up Process
Robustness batches ~ 5 kg Robust/stable Form/Method/process
Valida$on batches – 30 Kg to 1000 kg
Validated/verified Process
Takes 2-‐3 years and uses thousands of Kg of materials Each step is performed at risk – Formula$on is “op$mized” without knowledge of manufacturability, process is “op$mized” without knowledge of scaleability, etc. Does not use DOE for analy$cal development – subop$mal accuracy and robustness Does not support RTR
Integrated development paradigm
• Performs product, process, and analy$cal development simultaneously and at scale, thus achieving robust product and process design with lower risk
• Takes <2 months, uses much less material (order of magnitude decrease) • Uses DOE for Analy$cal Method development (more reliable)
Master DOE at manufacturing scale – formula$on variables, Process variables, robustness
Formula$on Dev. Process Dev.
Process Analy$cal Method, including RTR: non-‐destruc$ve
transmission spectroscopy, followed by dissolu$on and hardness tes$ng OF THE
SAME TABLETS
Analy$cal Method Dev.
Formula$on
Standardized Equipment • Organized into four (4) connectable/exchangeable modules with
specified inputs and outputs • Supported by predic$ve models for module performance as a
func$on of input material proper$es and process parameters • Equipped with standard sensing and control capabili$es • Can be “plugged” into supervisory control infrastructure through
OPC
Feeder/mill/blender module
Feed frame/
tablet press module
Direct Compac$on
Feeder/mill/blender module
Feed frame/tablet press module
Feeder/mill/blender module
Roller compactor/mill module
Wet Granula$on
Feeder/mill/blender module
Feed frame/
tablet press module
Feeder/mill/blender module
Wet granulator/drier/mill module
Designing for flexibility: Standardized Modules • Line always start with a feeder/blender module and always end
with a table$ng module • Tablet press is always fed by a feeder/blender module • Addi$onal modules are always “sandwiched” between feeder/
blender modules
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Feeder/mill/blender module
Feed frame/
tablet press module
Direct Compac$on Roller Compac$on
Feeder/mill/blender module
Feed frame/
tablet press module
Feeder/mill/blender module
Roller compactor/mill module
Wet Granula$on
Feeder/mill/blender module
Feed frame/
tablet press module
Feeder/mill/blender module
Wet granulator/drier/mill module
Standard Formula$ons • Collec$on of master formulas, developed for different “product families”, based
on achieving blend and finished product proper$es • Within each standard formula$on, establish a database of material proper$es
for ingredients and blends • For each standard formula$on and each standard equipment design, establish
predic$ve models rela$ng material proper$es and process parameters to intermediate blend proper$es and product performance
• For each master formula, defined an “opera$onal envelope” in terms of API material proper$es and API content
• Once the opera$onal envelope is determined in terms of API and excipient proper$es, materials can be systema$cally modified to “fit within the envelope”
• This knowledge enables: – Defini$on of meaningful acceptance specifica$ons for raw materials – Determina$on of sensing and measurement required for quality assurance – Design of an effec$ve control architecture – Determina$on of required performance standards for control system
Standardized Sensing and Control Infrastructure • Overall sensing and control requirements are specified, based on mul$-‐$er risk-‐
based framework • Each module has standard sensing and local-‐level control, what is needed is to
connect them into an integrated network capable of complying with overall performance requirements
• Control plaoorm and measurement requirements can be specified and integrated based on models and verified experimentally
• Sensing and control requirements need to match risk level – Low risk $er (known product with history of successful manufacture, high dose
product, low toxicity, no risk of dose dumping, known materials, simple process, simple formula$on)
– Medium risk $er (new product with low risk factors, or exis$ng product with known risk and manageable factors such as high dose with risk of dose dumping, medium level of complexity in process and/or formula$on)
– High risk $er (highly potent low dose compounds, new product with unknown or high risk factors, high risk of dose dumping, high risk of agglomera$on, highly complex formula$on and/or process)
Opportuni$es for USP
• Standardize ingredient characteriza$on methods • Standardize product characteriza$on methods • Standardize equipment performance requirements • Standardize sensing methodologies • Standardize control capabili$es • Standardize the product/process development methodology