Coupling a Continuous Flow Reactor System to a Platform for Improved Process Development and Optimization - An Approach to Defining FDA's QbD

Transcription

1 Coupling a Continuous Flow Reactor System to a Platform for Improved Process Development and Optimization - An Approach to Defining FDA's QbD Brian Marquardt, Wesley Thompson, Michael Roberto, Charles Branham and Thomas Dearing Applied Physics Laboratory University of Washington Seattle, WA U.S. Food and Drug Administration

2 Analytical Sampling for Online Applications

3 Why Use Continuous Flow Reactors? High Throughput Experimentation For Discovery and screening Process development Process optimization Process control Production Eliminate chemical engineering production problems related to scaling up batch systems Increase production through use of many parallel microreactors to achieve volume

4 Example: Esterification of Methanol Acetic Acid + Methanol H + Methyl Acetate + H 2 O Intensity ROI Standard Raman spectra Acetic Acid Methanol M ethyl Acetate Raman Shift (cm -1 )

5 Batch Runs at Different Temperatures Relative Intensity º 55º 45º 35º 25º 15º 5º 50 PCA analysis of the formation of acetate monitored by Raman spectroscopy reaction time 1.5 hours Reaction Time (min.) Total experiment time ~ 1 week (includes charging reactors, cleaning, ) 90

6 Continuous Rxn. with Temp. Step Temp 40 C Temp 25 C with residence time module flow rate: ml/min (residence time ~ 2.5 min) (25 C 40 C) methyl acetate acetic acid With control of flow reactor parameters and analytics, fast optimization is possible

7 Product Yield vs. Temperature PCA Analysis on data after mixing: 1 st PCA scores Increase in reaction yield after each temperature step Range = C without residence time module flow rate: 0.89 ml/min (residence time ~ 5 min) 1 week of batch data reproduced in less than three hours by continuous flow

8 Result: Estimated Response Surfaces

9 Challenges To Using AF Reactors EDUCATION!!!!!! Interfacing modular units Sampling and screening Analytical characterization Data handling Process modeling and feed back control (particularly if they are used for production)

10 Analysis of Advanced Flow Reactors Problems with performing online measurements Gas formation in sample lines Temperature change before reaching analyzer Phase change between reactor and analyzer Sensor placement at optimal position Automated flow and pressure control Most PAT problems are due to sampling not measurement device Need better systems to sample processes

11 Application of Sampling Systems To Microreactors Example of bringing analytics to a process and the challenges with integrating them

12 What is NeSSI? Industry-driven effort to define and promote a new standardized alternative to sample conditioning systems for analyzers and sensors Standard fluidic interface for modular surface-mount components ISA SP76 Standard wiring and communications interfaces Standard platform for micro analytics

13 What does NeSSI Provide Simple Lego-like assembly Easy to re-configure No special tools or skills required Standardized flow components Mix-and-match compatibility between vendors Growing list of components Standardized electrical and communication (Gen II) Plug-and-play integration of multiple devices Simplified interface for programmatic I/O and control Advanced analytics (Gen III) Micro-analyzers Integrated analysis or smart systems

14 NeSSI Raman Sampling Block Parker Intraflow NeSSI substrate Sample conditioning to induce backpressure to reduce bubble formation and the heated substrate allows analysis at reactor conditions

15 NESSI AF Reactor Sampling/Calibration Pump 1 Reactor Feed 1 Product Stream Reactor Feed 2 Real-time Calibration waste prod Pump 2 Analyzer Suite Application of sampling systems and analytics to optimize and control AF reactor

16 Phase I Background and Past Accomplishments

17 Demonstrating QbD - Phase I Goal: to improve reaction monitoring and optimization through the use of continuous glass flow reactors, NeSSI and analytics Funded by the FDA to demonstrate the benefits of improved reactor design, effective sampling and online analytics to increase process understanding (QbD) Partners: FDA, Corning, CPAC, MEPI, Kaiser, Parker QbD Project began November 2008 Process Reactions June 2009

18 CF Reactor and Raman Analyzer 4 channel, 785 nm Kaiser Optical Systems Rxn2 probes placed at different reactor zones

19 Raman Analysis of CF Reactor Monitor reaction with 4 channel 785 nm Raman system NeSSI sampling systems (1-4) equipped with Raman ballprobes Online GC also used as post quench online analyzer (4)

20 Chloroformate Chemistry Organic Acid Chloride Organic Carbonate + dimer O O OH pyridine Cl + O HO toluène O O OH + N.HCl 2-ethylhexyl chloroformate butane-1,2-diol 2-ethylhexyl 2-hydroxybutyl carbonate OH O Cl + O O O O O O O O O O 2-ethylhexyl chloroformate 2-ethylhexyl 2-hydroxybutyl carbonate dimmer dimer Carbonate and dimer formation

21 NeSSI Ballprobe - Raman/NIR/UV Ballprobe Specs. Hastelloy C-276 Ti, SS, Monel Sapphire optic Std. temp range: C Pressure: Bar Matrix Solutions:

22 NeSSI Sampling System for Reactor Raman Probe monitor clean bypass

23 NeSSI and Raman Probe Images

24 Design of Experiments Information 31 Experiments total Temperature steps Reaction with no toluene Changes in butanediol ratio Changes in pyridine ratio Propanediol instead of butanediol Simulated Reactor problems Pump failure Less heat exchange Poor dilution of chloroformate

25 Raman Peaks of Interest for Rxn. Chloroformate Toluene Carbonate Dimer Toluene

26 3D Plot of Raman Reaction Data (Low cm -1 ) GC Results (%) Test R-OH 2EHCF R-Cl Carbonate Dimer Ch. 1 Toluene Chloroformate Toluene

27 Reaction Profiles for 2 DoE Steps GC Results (%) Test R-OH 2EHCF R-Cl Carbonate Dimer Normalized Signal Intensity Test 1 Test Normalized Signal Intensity Carbonate ---- Chloroformate Sample Number

28 DoE Run1 Channel 1 Data (Reactor) Run1Ch1LowPCA Density 1 Density 2 Density Run1Ch1LowPCA Feed 1 Feed 2 Feed Run1Ch1LowPCA Pressure 1 Pressure 2 Pressure Run1Ch1LowPCA Ambient Temp. Quench Temp. Reactor Temp

29 Phase I Summary Data collected and organized 17 days in Toulouse France Analysis and modeling Evaluation of various modeling protocols PCA, MCR, ALS Calibrate to GC results (PLS) Phase II of project Acquire reactor at CPAC Focus on reactor control Implement more sensors Real-time product work-up Begin to implement models for process feedback control

30 Phase II Continuous Process Understanding and Control

31 FDA Project - Phase II Dec. 20, 2010 Dec. 19, 2011 Process Understanding Chemistry Determine, evaluate and test reactions in CF reactors Pharmaceutical industry relevant chemistry Emphasis on process not specific chemistry Determine CRF (Critical Response Factors) and Levels Sampling & DoE Coupling analytics at ml scale Reaction monitoring w/online analytics Reaction/Process Modeling and Control Determine Control Mechanisms Initiation of Process Control

32 Esterification of Benzoic Acid and Subsequent Hydrolysis

33 Esterification Acid and alcohol form an ester Benzoic acid and methanol or ethanol Protection technique for carboxylic acids Flow rate, temperature dependant 1.0 to 20.0 µl/min 25 to 175 degrees C Forms water as a product C. Wiles, 2009

34 Hydrolysis of Esters Esters undergo hydrolysis in basic conditions Possible to implement as 2 nd rxn after esterification Deprotection technique suitable for continuous flow conditions Again, flow and temperature dependant Slower flow rate, higher temp for best results C. Wiles, 2009

35 Analytical Control System Design Optimization Control Process Modeling Data Fusion Analytics and Data Handling Hardware Control and Monitoring (Software) Hardware NeSSI, Raman, Other PAT, Reactor

36 Corning Advanced-FlowTM LF Low-Flow Capability (1-10 ml/min) Corning has introduced a reduced flow-rate reactor that retains the outstanding mixing and heat exchange performance of its Advance-FlowTM glass reactors while providing: Low internal volume (2 ml flow) High flexibility Metal-free reaction path Scalability Compatibility with analytics T, Flow and Pumping control LF platform will be the larger reactor platform for our Phase II FDA project

37 Reactor with NeSSI and Analytics at CPAC

38 Hardware Control and Monitoring Set control variables Flow rates Pressure Temperature Monitored variables Flow rates Pressure Temperature Raman

39 System Control and Analytics HPLC Pump (Flow Rate) Back Pressure Regulator Flow Meter Pressure Gauge Thermocouple Raman Other PAT Control Analytics Reactant 1 HPLC Pump (Flow Rate) Back Pressure Regulator Flow Meter Pressure Gauge Thermocouple Raman Other PAT Reactant 2 Temperature Control Flow Meter Pressure Gauge Thermocouple Raman Other PAT Needle Valve Product

40 NeSSI Reagent Sampling System NeSSI Product Sampling Sys.

41 Completed Awaiting Hardware Q Step Temp & Flow Continuous Temp & Flow Linear Step Custom Step Flow Software / Control Temperature Continuous Flow Large Scale Goals Feedback Mechanisms Monitoring System Calibration of Flow and Temp Pressure Raman Cost-effective Flow Rate Flow Rate Chemistry / Production Determine Yield Optimize system Pressure Automated Process? Temperature

42 Reactor, Sampling and Analytics

43 Full System w/ Control

44 Process Analytical Technology Possibility for multiple analytical techniques Raman ATR Infrared Micro-GC Many others (refractive index, LC, fluorescence, etc.) Modular system All techniques compatible with NeSSI hardware All measurements performed serially in NeSSI system System allows for screening of effective analytics Interchangeable

45 Kaiser Multi-Channel Raman

46 Mettler Toledo - React-IR

47 Thermo/C2V Fast Micro-GC as well as

48 Mechatest Sampling Solutions NeSSI Liquid Sampler Compliant with ANSI/ISA mm (1.5 in.) footprint. Three Port configuration: Sample Inlet, Bypass and Vent. Quick and safe operation, low dead volume design with bypass. Manual or Automatic sampling In-line Sampling Closed Loop and Emission Free Sampling Easy in operation

49 Analytics Validation Validation will be performed off-line with gas chromatography-mass spectrometry (GC-MS) Offline validation by GC-MS will allow for quantitative multivariate modeling of the online PAT suite This will provide the data for data fusion, reaction modeling and process control

50 Reaction Modeling/Control Monitoring of flow, temperature, and pressure at multiple points will allow for complete understanding of physical system Matching Raman data with CRF s to investigate product formation under varying conditions Precise temperature information across the entire reactor space will allow for effective characterization of reaction thermodynamics Thermal mass balance Heat capacity

51 In Progress Organizing publication of Phase I results Custom designing NeSSI sampling and analytics apparatus for Phase II Designing LabVIEW software interface for hardware control Interfacing control software with new analytical hardware Perform batch chemistry of reactions for validation and comparison to CF results

52 Challenges Pure product Can workup be done on-line? Neutralization Salt generation Separation of phases Continuous generation of products Esters and carboxylic acids Loop through with continuous workup Add excess acid or base to catalyze next step? Continuous, excessive salt generation may degrade equipment (plugging???)

53 Thanks U.S. Food and Drug Administration Moheb Nasr Christine Moore David Morley Sharmista Chatterjee Corning Glass Parker Pierre Woehl Sergio Pissavini Jérémy Jorda Mike Cost Kaiser Optical Systems CPAC Ian Lewis Hervé Lucas Bruno Lenain University of Washington Applied Physics Lab La Maison Européenne des Procédés Innovants Annelyse Conté U.S. Food and Drug Administration MEPI