Development of Continuous Crystallisation Processes for Consistent Crystal Products

Transcription

1 Development of Continuous Crystallisation Processes for Consistent Crystal Products Alastair J. Florence, CMAC, University of Strathclyde Drug Delivery and Formulation Forum, Berlin May 2016

2 Drivers for Change in Manufacturing Do we have the correct architecture for manufacturing in the industry? Now is the time to look at new infrastructure with smaller, more agile facilities for end to end manufacture.

3 CMAC Manufacturing Research Centre Co-created with industry to address long-term manufacturing challenges and skills needs EPSRC Centre for Innovative Manufacturing Key National Research Platform Partnership approach to industry-academic collaboration to deliver critical mass of: Research Training & Skills Knowledge Exchange / Industry Facilities Tier 1s GSK, AZ, Novartis and Bayer + Tier 2/technology providers eg PSE, PEL, Mettler Multidisciplinary academic partners - critical mass of expertise and facilities

4 Demand Led Research Scope Accelerate the adoption of continuous processing in pharmaceutical manufacturing synthesis crystallisation isolation/drying secondary manufacture Improve particulate based product supply via continuous processes Develop understanding of complex interactions between process, materials and quality Develop flexible continuous process technologies and understanding to deliver: Robustness Consistency Manufacturability Performance

5 Production of Particles and Controlling Particle Attributes for Performance

6 Problems with Pharmaceutical Particles Process parameters Physical transformations Process parameters Physical transformations Molecular attributes Particle attributes Bulk attributes But molecules may adopt many possible solid forms = different size, shape, surfaces, microstructure What particle is required? How to make? Crystal structure prediction is developing Complex transformation dynamics Limited structure-property-process relationships Measurement gaps at molecular length/time scale Surfaces poorly understood Microstructure (e.g. defects) difficult to measure

7 Poor Crystallisation Control 300 µm Fines in crystallisation of form of L-glutamic acid e.g. variable filtration times Mixture of carbamazepine forms II and III due to in situ transformation variable dissolution rates Encrustation on UV probe compromise measurement Uncontrolled growth on reactor walls (encrustation/ fouling) compromise heat transfer Supersaturation, secondary nucleation, attrition, agglomeration, encrustation and transformations can impact on measurement, uniformity and quality

8 Continuous Manufacturing Laboratory-scale, modular processing systems Synthesis to formulated product Particular focus on primary to secondary interface Opportunities for more integration via alternative configurations Deliver the right particle performance

9 Workflows and Tools for Continuous Crystallisation Development Implement a consistent, systematic approach across programme

10 Stage 2: Solvent Screen Transmission at B.P. -10 C. 100% = completely dissolved Transmission at 20 C. 100% = completely dissolved solvents out of 54 fall within design space and carried on to next stage Description Assess solubility from library of solvents Broad range of solvent types and functionality Methodology 50 g/l of API mixed with solvent Dissolution evaluated at 3 temperatures: 20 C B.P. 10 C Mid point Selection Criteria for solvent screen Parameter Transmission at (B.P. 10) C Transmission at 20 C Design space > 95 % < 95 % ICH Class 3 or 2

11 Stage 3: Solvent Selection Description Assess T- dependence Chemical and physical stability assessed Methodology Concentrations 2.5 to 20 wt% T = 5 C to (B.P. 10) C Slow heating ramp (0.1 C/min) T cycling avoided Imaging used High agglomeration Low agglomeration Fouled Nonfouled

12 Stage 3: Solvent Selection Parameter Design space Chosen solvent Upper temperature 90 C 80 C Lower temperature 5 C 5 C Yield 90 % 90 % Solid fraction 10 to 25 % w/w 17 % Metastable zone width > 5 C 20 C Form and chemical stability at elevated temp. > 24 hr > 24 hr Agglomeration Low to none Low to none Fouling None None Only 1 solvent out of 11 from previous stage met design space criteria: 3-methyl-1-butanol (iso-amyl alcohol)

13 Robust approach for calibration of methods required (C, T, particles) Stage 4. In-line monitoring of crystallisation e.g. spectroscopic approaches Solubility determination Temperature dependent calibration using PLS modelling

14 Stage 5: System understanding Description ID process conditions for desired performance. ID limits Inform platform selection, mixing, etc. Metastable zone widths Growth rates. Bulk and single crystal Methodology Range of tests developed to assess: Metastable zone Secondary nucleation Growth rate Fouling Agglomeration Secondary nucleation: Seeded vs. unseeded Agglomeration Fouling induction times S = 1.75 z y x S = 2.00

15 Continuous Crystallisation Various Tools e.g Continuous oscillatory baffled crystalliser Static mixer (Kenics) Lawton, Steele, et al. (2009) Organic Process Research & Development 13, Stirred tank (MSMPR) cascade Alvarez & Myerson (2010) Crystal Growth & Design 10, Segmented tubular flow reactor Continuous secondary nucleator and tubular crystalliser Quon, Zhang, et al. (2012) Crystal Growth & Design 12, Eder, Schrank, et al. (2012) Crystal Growth & Design 12, Wong, Cui, et al. (2013) Crystal Growth & Design 13,

16 Stage 5: System understanding Results Parameter Metastable zone width Min. supersaturation for secondary nucleation Chosen solvent 22 to 35 C S = 1.7 to 2.2 Growth rate 1.5 to 3 µm/min Agglomeration Fouling induction time Low to none S = 1.75: 278 min S = 2.00: 107 min Achievable supersaturation limited by heat transfer 1 stage 1L MSMPR 3 stage 15L MSMPR COBC PFR Primary/secondary nucleation indistinguishable Secondary nucleation Growth Primary nucleation Couple system understanding and crystalliser characterisation to determine design space for operation Residence time governed by equipment volume and pump specification

17 Stage 6: Process understanding Mass frac. Volume % Supersaturation Description Experimental DoE coupled with PBE to establish design space Concentration Solubility Supersaturation Methodology Batch seeded cooling experiments used as basis for parameter estimation Covering a range of seed mass, cooling rate and power input Time (s) Expt. Seed mass (g) Cooling rate ( C/min) Power input (W/kg) Seed Product - expt CE diameter 10 (μm) 1000

18 Volume frac. Stage 6: Process understanding Parameter estimation - power law growth model Seed Product - expt. Product - model Expt. 8 - PSD comparison Particle size (μm)

19 Volume % Stage 7: Proof of concept Description Using model and knowledge gained from the workflow, perform a series of crystallisations to demonstrate concept Size band 1 - Dv50 ~ 30 μm, 3.5 kg Generated through the nucleation of supersaturated solution in rotor-stator wet mill 10 L seed miniplant module with IKA MagicLab in recycle loop. Cooled following profile from Optimax experiment at constant supersaturation 12 1 Litre scale Litre scale A 10 Litre scale B Particle size (μm)

20 Temperature ( C) Stage 7: Proof of concept Seed addition Temperature profile COBC profile (model) Constant S profile Size band 2 Dv50 ~70 μm, 3.5 kg Continuous seeded crystallisation in COBC module. 6.1 % seed loading, 166 min residence time, 1180 min operating time (excluding startup) Size band 3 Dv50 ~ 155 μm, 6.5 kg Continuous seeded crystallisation in COBC module. 9.9 % seed loading, 166 min residence time, 2127 operating time (excluding start-up) Residence time (min)

21 Stage 7: Proof of concept (COBR) Extensive use of PAT during runs for validation: FBRM (particle size/growth), IR (concentration); PVM (shape; size); Raman (form)

22 Stage 7: Proof of concept (COBR) Extensive use of PAT during runs for validation: FBRM (particle size/growth), IR (concentration); PVM (shape; size); Raman (form)

23 Stage 7: Proof of concept MSMPR campaign Dv50 ~ 80 μm, 2.5 kg Continuous seeded crystallisation in 3 stage MSMPR using 2 L vessels Stage temperatures: 63.8, 48.3 and 32.5 C (maintain S < 1.35) 7.1 % seed loading, 172 min residence time, 980 operating time (excluding start-up)

24 Volume fraction Volume fraction Stage 7: Proof of concept 0.25 Szie band 1 Size band 2 Size band 3 PFR Size bands Size band 1 Stage 1 Stage 2 Stage MSMPR PSDs Particle size (μm) Particle size (μm) 4 lots of particles with different PSDs targeted 30, 50, 70, 80 and 155 mm Samples will be characterised for continuous secondary processing

25 Continuous Filtration CRD GSK Falcon robotic platform and Bespoke rotary drum filter (Paracetamol API) (Impurities) Acetanilide Metacetamol (Ethanol / water) Falcon - Accurately quantify filtration and washing perfomance Drum filter - scaled to take output from COBCs and isolate product stream with washing.

26 Scale-up of co-crystallisation process from 0.3g (vial) 30g (OBC) 1kg (COBC) SEM XRPD vs. batch Pawley fit to XRPD data from reclaimed sample of co-crystals (a, b, c (Å) = , , ; β ( o ) = , Rwp = 4.120) Phase pure co-crystal product Consistent particle size Zhao et al., CrystEngComm, 2014,16,

27 Getting The Right Form Manipulating properties through continuous spherical agglomeration Dealing with poor powder flow Particles (10s mm) Loose aggregates (100s mm) Intergrown, spherical agglomerates ( mm) Transform difficult particles into well behaved granules

28 Getting The Right Form Manipulating properties through continuous agglomeration Material prep. Wetting and Nucleation Coalescence and Consolidation BL Droplet Formation Microfluidic system Mixing Coalescence Consolidation Crystal Wetting High shear Mixer CSTR Key Process Parameters:- Time, Shear rate PAT controlled Temperature Multistage continuous processing to deliver modified attributes

29 Getting The Right Form Manipulating properties through continuous spherical agglomeration Granular API form of aspirin 500 mm Significantly improved flow properties Suitable for direct compression

30 Flexible Process Streams (OSD) Inputs ex Conti Cryst / excipient Formulation processes/ Transformation Dose Form Tablets/Capsules/Pil ls/structured doses Extrusion (melt/wet) Compression, moulding, 3D printing, capsule etc. Wet granulation Batch/Cont/TS Direct compression (batch/cont blend) Roller Compaction

31 Exploiting Informatics Exploiting ELN / networked instrument base to accumulate systematic data across different systems Complement mechanistic models with informatics-based tools Applied also to solubility, nucleation, fouling, agglomeration, polymorphism, solvate formation

32 Acknowledgements Academics Professor Gavin Halbert Dr Blair Johnston Dr Alison Nordon Dr Chris Price Professor Chris Rielly Dr John Robertson Dr Jag Srai Professor Jan Sefcik Post Docs Dr Cameron Brown Dr Tomas Harrington Dr Anna Jawor-Bacynska Dr Pól MacFhionnghaile Dr Thomas McGlone Dr Ebeneezer Ojo Dr Elke Prasad Dr Humera Siddique Dr Vijay Srirambhatla Dr Rene Steendam Dr Anna Trybala ICT-CMAC Dr Murray Robertson Researchers Bilal Ahmed Maria Bruiglia Michael Chrubrasik Natalia Dabrowska Andrew Dunn Clarissa Forbes Dimitris Fysikopoulos Raaz Gurung Fraser Mabbott John McGinty Francesca Perciballi Hector Polyzois Vishal Raval Vaclav Svoboda Stephanie Yerdelen