The CMAC workflow approach Since the development of the seminal workflow for seeded continuous cooling crystallisations, a number of workflows have been developed within CMAC that cover various processes including early stage crystallisation development, impurity rejection, and isolation

Benyahia, Brahim

Brown, Cameron

Chong, Magdalene

Johnston, Blair

Li, Wei

McGinty, John

Nordon, Alison

Rielly, Chris

Robertson, Murray

Sefcik, Jan

University of Strathclyde Institutional Repository

6 1WWW.CMAC.AC.UKCMAC POSTER COLLECTION6 0A Structured Approach to Implementation of Measurements: Crystallisation in the Mefenamic Acid MicroFactoryMagdalene Chong,ab Wei Li,c Cameron Brown,ad John McGinty,ae Murray Robertson,adBlair Johnston,ad Jan Sefcik,ae Brahim Benyahia,c Chris Riellyc and Alison Nordonaba EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, University of Strathclyde, Glasgow, UK; b WestCHEM, Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow, UK; c EPSRC Future Continuous Manufacturing and Advanced Crystallisation Research Hub, Department of Chemical Engineering, Loughborough University, Loughborough, UK; d Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK; e Department of Chemical and Process Engineering, University of Strathclyde, Glasgow, UKReferences 1. Mol. Syst. Des. Eng., 2018, 3, 518-549; 2. CrystEngComm, 2020, 22, 7475-7489; 3. Org. Process Res. Dev., 2020, 24, 1443–1456; 4. Org. Process Res. Dev., 2021, 25, 1143-1159. Acknowledgements The authors would like to thank the EPSRC for funding the FutureContinuous Manufacturing and Advanced Crystallisation Research Hub (Grant Ref: EP/P006965/1). The authors acknowledge that some of the work presented was carried out in the CMAC National Facility, housed within the University of Strathclyde’s Technology and Innovation Centre, andfunded with a UK Research Partnership Institute Fund (UKRPIF) capital award, SFC ref. H13054, from the Higher Education Funding Council for England (HEFCE).The CMAC workflow approachSince the development of the seminal workflow for seededcontinuous cooling crystallisations,1 a number of workflows havebeen developed within CMAC that cover various processesincluding early stage crystallisation development,2 impurityrejection,3 and isolation.4A workflow for implementation of measurementsThe proposed workflow outlines stages and decisions normallyundertaken in developing a measurement strategy. However, thesuggested approach places measurement requirements at theforefront of all decision-making. The proposed structure thereforeensures all stages and subsequent decisions return to themeasurement requirements outlined in Stage 1 of the workflow.Case study: 5-stage crystallisation of mefenamic acidThe mefenamic acid MicroFactory includes a 5-stagecrystallisation in 2-butanol/heptane (90:10 w/w). This crystallisationwill be used to illustrate the decision making for in situmeasurements according to the proposed workflow.Stage 1 Outline measurement requirements Stage 2 Outline equipment capabilityAre measurement requirements met by equipment capability? Single stage YES Multi-stage (equipment limitations) NODecision 1Parameter to measure Proposed in situ measurementMu0 (number of crystals) Focussed beam reflectance measurement (FBRM)D43 (volume mean size, crystals) Particle vision measurement (PVM)C (concentration) Ultraviolet (UV) spectrometryLimitation: Unable to carry out measurements in all vessels.• Use a sensitivity analysis approach to prioritise probe placements.Physical constraints/challenges:• Fitting of all probes into vessels.• Positioning of instrumentation to maintain access to crystalliser.• Ensuring equipment will not be disturbed (detrimental to data quality).Additional constraint:• Cannot accommodate Stage 5 proposal (subsequent equipment limitation).• Compromise and revised probe placements required.Stage 3 Prioritise measurement requirementsSensitivity analysis approach Stage 1 Stage 2 Stage 3 Stage 4 Stage 5Model parameters for maximum sizeFBRMUV UVFBRMProcess parameters for minimum sizeFBRMUVPVMFBRMPVMUVProcess parameters for maximum size UVPVMFBRM FBRMPVMUVProposalFBRMUVFBRMUVFBRMPVMFBRMPVMUVRevised proposal: considering physical constraintsFBRMUVFBRMUVFBRMPVMFBRMPVMFinal proposal for probe placementsFBRMUVFBRMUVFBRMPVMAre revised measurement requirements met by equipment capability? YESDecision 2Stage 4 Evaluate data strategy Stage 5 Assess if needs are metEvaluation: Significant fouling observed in Stage 1.• Relocate Stage 1 in situ monitoring to Stage 5 instead?Ongoing activities for improvements to future runs.Stage 1 Stage 2 Stage 3 Stage 4 Stage 5Suggestion for future runsFBRMUVFBRMPVMFBRMUVIs quantitative or qualitative information required?What is the required measurement frequency?How important is the measurement?What is the required accuracy and precision?What are the monitoring requirements?For the property to be measuredWhat is the equipment availability and usage?What are the physical limitations (e.g. probe dimensions, fibre lengths?)What is the required purpose of the equipment?How is instrument performance monitored?What are the monitoring requirements?Instrumentation considerationsIs the required data acquired?Is the data from direct or indirect measurements?How is the data acquired?Is any data processing required?Is the data in the correct structure and format?Considerations regarding dataCrystal nucleation rates from induction time measurements and microfluidic devices.Daniel M Powell1, Jan Sefcik1,2, Michele Zagnoni3 & Joop H ter Horst4IntroductionNucleation is one of the key processes in crystallization of pharmaceutical products as it determinesvarious crystal product quality attributes such as crystal size distribution and crystal structure.Therefore, understanding the fundamentals of nucleation is key to attaining control over these properties.Nucleation refers to the generation of a new phase of nanoscopic clusters of molecules from asupersaturated mother liquor.Microfluidic devices are a promising tool for the analysis of crystallisation kinetics due to their ability tocreate and control a large number of droplets of known composition in isolated, controlled conditionsquickly.Recent work within CMAC has shown that concentration is enhanced at interfaces, particularlyoil/solution interfaces (McKechnie et al.). This is of particular significance for work in microfluidicdevices, where crystallising droplets are in constant contact with oil and often have significantly greatersurface to volume ratio. In this work nucleation rates were calculated from small scale (1 ml) inductiontime measurements using a technique developed by Jiang et al. These results are to be compared withthose gained from micro scale nucleation measurements in a microfluidic device. This work endeavoursto present microfluidics as a tool for simple, quick acquisition of nucleation rate data and analyse theeffect of solution oil/interface on nucleation rate.MethodsSolubility determination conducted through equilibrium concentration method. Vials of solution withexcess DL-phenylalanine were brought to equilibrium, filtered and evaporated to determine solubility.Induction time measurements taken at known supersaturation under isothermal conditions in the Crystal16 multiple reactor system.S = C / C* (C* is predicted from pH-dependent solubility model determined from fitting experimentalsolubility to predictive model)No Crystals         100% Crystals           0%TimeTemperatureTransmissivityTindCrystal 16 Multiple reactor system Representation of transmissivity of vials Induction time experimental profileSolubility Model0204060801001201401601802007 7.5 8 8.5 9 9.5 10 10.5 11Solubility (mg/g)pHpH dependent solubility 2 Solubility repeats Predicted SolubilitySolubility was initially determined experimentallyin the Crystal 16 and was compared to apredictive model:𝐶𝐶 = 𝐶𝐶𝐶𝐶𝐶𝐶 1 + 10−𝑝𝑝𝑝𝑝𝑝𝑝+𝑝𝑝𝑝𝑝This model is the starting point for solubilityprediction. However, this model does notaccommodate solution activity and assumesinfinite anion solubility. To improve accuracy,solution activity must be incorporated and anupper limit given to anion solubility.Induction time results00.10.20.30.40.50.60.70.80.910 5000 10000 15000 20000ProbabilityInduction time (s)Cumulative Probability12345Future WorkNext steps are to fully develop the solubility model. As nucleation rate is a function of supersaturation, accurate solubility is essential to analysing nucleation rate. A comprehensive understanding of induction time across the pHrange is necessary to accurately map the effect of supersaturation on nucleation rate. Microfluidic nucleation rate experiments will be performed to analyse the difference between the small scale, 1 ml induction time measurementsand the nano-scale 0.5 nl experiments. This data will then be compared to assess the effect of the oil/water interface on nucleation.Expt SupersaturationRatioNucleationRate (particles/m3/s)Growth Time (s)1 1.31 545 6752 1.26 120 34503 1.33 1400 2004 1.30 755 8155 1.30 775 795The probability of forming a nucleus in a time interval is described by the Poisson distribution. The average number of nucleiformed in a certain volume at constant supersaturation over a time interval is linearly related to the nucleation rate. The probabilitythat a nucleus is formed in a time interval is described by the equation (Jiang et al.):𝑃𝑃 𝑡𝑡 = 1 − exp −𝐽𝐽𝐽𝐽 𝑡𝑡 − 𝑡𝑡𝑔𝑔where is the stationary nucleation rate, is the volume and is the detection time. The time taken for crystals to grow largeenough to be detected is given by .Slight differences in pH caused by dissolution of amino acid lead to changes in supersaturation ratio which is the primary driver ofnucleation.Left: Induction times of DL-Phenylalanine in pH adjusted water at isothermal conditions at S = 2.43 (1), 2.28 (2), 2.55 (3), 2.39 (4), 2.44 (5). Right: Cumulative probability distribution P(t) of experimentally obtained induction time for DL-phenylalanine in pH-adjusted water.Microfluidic work.Microfluidics can be used as a tool for high throughput experimentation. Droplet microfluidics allows for thesimultaneous production of hundreds of independent droplets of known solution composition that can bemonitored simultaneously.YT-junction design. Solution and antisolvent are mixed at the Y component into a supersaturated solution. Aqueous in oil droplets are formed at the T component and progress onward to the storage chamber. QR code: animation of Y junctionOil inletAntisolvent inletSolution inletDroplet formation Droplets of supersaturated solution are formed at the YT-junction designelement before being transported to a storage matrix where they can beobserved for crystal nucleation. Droplets are of 0.5 nL volume.Due to the linear relationship between nucleation rate and volume onewould expect to require a significantly greater nucleation rate at thesevolumes. The main driver of nucleation being supersaturation ratio, onewould expect to require a supersaturation ratio increased by orders ofmagnitude.Experimental solubility determined in Crystal 16 at 20 °C. Modelled solubility as a line.1.251.261.271.281.291.31.311.321.331.340 5000 10000 15000 20000Supersaturation RatioInduction time (s)Induction times12345Solubility determinationMicrofluidic Nucleation RateNucleation rate determinationInduction Time measurements1234Assessing the effect of oil/water interfaces on crystal nucleationKey Project steps.1. Jiang, S. and ter Horst, J.H. (2011). Crystal Nucleation Rates from Probability Distributions of Induction Times. Crystal Growth & Design, 11(1), pp.256–261.2. McKechnie, D., Anker, S., Zahid, S., Mulheran, P.A., Sefcik, J. and Johnston, K. (2020). Interfacial Concentration Effect Facilitates Heterogeneous Nucleation from Solution. The Journal of Physical Chemistry Letters, 11(6), pp.2263–2271.1. EPRSC Future Manufacturing Hub for Continuous Manufacturing and Advanced Crystallisation, 99 George St, Glasgow, G1 1QH2. The University of Strathclyde, Chemical and Process Engineering, 75 Montrose St, Glasgow, G1 1XL3. The University of Strathclyde, CMP, Electrical and Electronic Engineering, 75 Montrose St, Glasgow, G1 1XL4. Université de Rouen, Laboratoire Sciences et Méthodes Séparatives, Place Emile Blondel, 76821 Mont Saint Aignan Cedex, Rouen, Francedaniel.powell.2018@uni.strath.ac.ukPOSTER 60POSTER 59 ------CMAC ' ~ FUTURE MANUFACTURING RESEARCH HUB 41&1 Outline equipment capability ~ I I I I I I I I Astrazenecai- ~♦Chiesi ♦ Decis ion 1 -Are measurement requirements met by equipment capability? Decis ion 2-Are revised measurement requirements met by equipment capability? Decis ion 3 -Are data requirements met? Decis ion 4 -Are measurement requirements met? Imperial College London UNIVERSITY Of J!! Q loughborough ,:, univ.rstty - ~11, V> ahefl'leld, _ @ Strathdyde ....... 

A structured approach to implementation of measurements : crystallisation in the mefenamic acid MicroFactory

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A structured approach to implementation of measurements : crystallisation in the mefenamic acid MicroFactory

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