Classification of crystallization outcomes using deep convolutional neural networks

The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine learning algorithms are trained and tested on different parts of this data set. We find that more than 94% of the test images can be correctly labeled, irrespective of their experimental origin. Because crystal recognition is key to high-density screening and the systematic analysis of crystallization experiments, this approach opens the door to both industrial and fundamental research applications

Enabling precision manufacturing of active pharmaceutical ingredients: workflow for seeded cooling continuous crystallisations

Continuous manufacturing is widely used for the production of commodity products. Currently, it is attracting increasing interest from the pharmaceutical industry and regulatory agencies as a means to provide a consistent supply of medicines. Crystallisation is a key operation in the isolation of the majority of pharmaceuticals and has been demonstrated in a continuous manner on a number of compounds using a range of processing technologies and scales. Whilst basic design principles for crystallisations and continuous processes are known, applying these in the context of rapid pharmaceutical process development with the associated constraints of speed to market and limited material availability is challenging. A systematic approach for continuous crystallisation process design is required to avoid the risk that decisions made on one aspect of the process conspire to make a later development step or steps, either for crystallisation or another unit operation, more difficult. In response to this industry challenge, an innovative system-wide approach to decision making has been developed to support rapid, systematic, and efficient continuous seeded cooling crystallisation process design. For continuous crystallisation, the goal is to develop and operate a robust, consistent process with tight control of particle attributes. Here, an innovative system-based workflow is presented that addresses this challenge. The aim, methodology, key decisions and output at each at stage are defined and a case study is presented demonstrating the successful application of the workflow for the rapid design of processes to produce kilo quantities of product with distinct, specified attributes suited to the pharmaceutical development environment. This work concludes with a vision for future applications of workflows in continuous manufacturing development to achieve rapid performance based design of pharmaceuticals

Enabling precision manufacturing of active pharmaceutical ingredients: workflow for seeded cooling continuous crystallisations

Continuous manufacturing is widely used for the production of commodity products. Currently, it is attracting increasing interest from the pharmaceutical industry and regulatory agencies as a means to provide a consistent supply of medicines. Crystallisation is a key operation in the isolation of the majority of pharmaceuticals and has been demonstrated in a continuous manner on a number of compounds using a range of processing technologies and scales. Whilst basic design principles for crystallisations and continuous processes are known, applying these in the context of rapid pharmaceutical process development with the associated constraints of speed to market and limited material availability is challenging. A systematic approach for continuous crystallisation process design is required to avoid the risk that decisions made on one aspect of the process conspire to make a later development step or steps, either for crystallisation or another unit operation, more difficult. In response to this industry challenge, an innovative system-wide approach to decision making has been developed to support rapid, systematic, and efficient continuous seeded cooling crystallisation process design. For continuous crystallisation, the goal is to develop and operate a robust, consistent process with tight control of particle attributes. Here, an innovative system-based workflow is presented that addresses this challenge. The aim, methodology, key decisions and output at each at stage are defined and a case study is presented demonstrating the successful application of the workflow for the rapid design of processes to produce kilo quantities of product with distinct, specified attributes suited to the pharmaceutical development environment. This work concludes with a vision for future applications of workflows in continuous manufacturing development to achieve rapid performance based design of pharmaceuticals

Continuous flow for materials synthesis, assembly and crystallisation at Diamond: discovery and delivery of high value materials

Continuous crystallisation of the model system Carbamazepine (CBZ) in ethanol in the KRAIC-D (Kinetically Regulated Automated Input Crystalliser - Diffraction) platform on beamline I11 (high resolution powder diffraction) is presented. The effect of introducing a controlled solid interface into the crystallisation process is investigated, where CBZ form III seeds are introduced in polymorphic purity at different seeding positions (pre- and post-nucleation) throughout the length of the KRAIC-D. The video associated with Chapter 4 corresponds with a post-nucleation CBZ form III experiment where a separation of crystal habit is observed as a result of the different interaction with the flow paths in the solution slugs with the segmented flow. The second device is the KRAIC-S (Kinetically Regulated Automated Input Crystalliser - Single Crystal) platform installed at I19 (small molecule single crystal beamline) employed to investigate the continuous crystallisation of paracetamol (PCM) in 60:40 water:isopropanol via a range of experiments including unseeded and seeded cooling crystallisations. The unseeded experiments also looked at the crystallisation at different set points along the KRAIC-S (6.7 m and 8.7 m) to investigate crystal growth and crystal rotation at different length scales. The videos associated with Chapter 5 include single crystals produced from the range of experiments investigated. Each video tracks a different single crystal in a solution slug, where through use of the slug triggering mechanism, whereby an optical trigger prompts translation of the motorised stage to artificially suspend the single crystal in the X-ray beam during data collection. These videos complement the diffraction data and can provide explanation for data collections, which do not achieve cell indexation as the single crystal is shown to move in and out of the X-ray beam in these videos.Videos obtained using Camera positioned by X-ray beam on beamline I19, the small molecule single crystal beamline at Diamond Light Source

OWL-Miner: Concept Induction in OWL Knowledge Bases

The Resource Description Framework (RDF) and Web Ontology Language (OWL) have been widely used in recent years, and automated methods for the analysis of data and knowledge directly within these formalisms are of current interest. Concept induction is a technique for discovering descriptions of data, such as inducing OWL class expressions to describe RDF data. These class expressions capture patterns in the data which can be used to characterise interesting clusters or to act as classifica- tion rules over unseen data. The semantics of OWL is underpinned by Description Logics (DLs), a family of expressive and decidable fragments of first-order logic. Recently, methods of concept induction which are well studied in the field of Inductive Logic Programming have been applied to the related formalism of DLs. These methods have been developed for a number of purposes including unsuper- vised clustering and supervised classification. Refinement-based search is a concept induction technique which structures the search space of DL concept/OWL class expressions and progressively generalises or specialises candidate concepts to cover example data as guided by quality criteria such as accuracy. However, the current state-of-the-art in this area is limited in that such methods: were not primarily de- signed to scale over large RDF/OWL knowledge bases; do not support class lan- guages as expressive as OWL2-DL; or, are limited to one purpose, such as learning OWL classes for integration into ontologies. Our work addresses these limitations by increasing the efficiency of these learning methods whilst permitting a concept language up to the expressivity of OWL2-DL classes. We describe methods which support both classification (predictive induction) and subgroup discovery (descrip- tive induction), which, in this context, are fundamentally related. We have implemented our methods as the system called OWL-Miner and show by evaluation that our methods outperform state-of-the-art systems for DL learning in both the quality of solutions found and the speed in which they are computed. Furthermore, we achieve the best ever ten-fold cross validation accuracy results on the long-standing benchmark problem of carcinogenesis. Finally, we present a case study on ongoing work in the application of OWL-Miner to a real-world problem directed at improving the efficiency of biological macromolecular crystallisation

Improving continuous crystallisation using process analytical technologies: design of a novel periodic flow process

In this thesis novel configurations and operating strategies in the mixed suspension mixed product removal (MSMPR) crystalliser are investigated, aided by integrated process analytical technologies (PAT) and crystallisation informatics system (CryPRINS) tools. The MSMPR is an idealised crystalliser model that assumes: steady-state operation; well mixed suspension with no product classification, such that all volume elements contain a mixture of particles (small and large) and crystal size distribution (CSD) that is independent of location in the crystalliser and is identical of the product withdrawn; and uniform supersaturation thought, leading to constant nucleation and growth rates. Single-stage MSMPR designs with continuous recycle/recirculation and modified heat exchanger were investigated and found to minimise fouling, encrustation and transfer line blockages. In particular, a modified MSMPR with baffled heat exchanger was found to significantly reduce the temperature between incoming feed hot feed solution and the cooled crystalliser, leading to a significant reduction in fouling, encrustation and blockages. In addition, the concept of the periodic mixed suspension mixed product removal (PMSMPR) crystallisation process is demonstrated for the first time viz single- and multi-stage cascaded operations. This method of operation involves the periodic transfer of slurry (addition and withdrawal) at high flow rates from either a single stirred vessel or between a number of stirred vessels arranged in series. The PMSMPR is therefore characterised by periodic withdrawals of product slurry. Similar to the MSMPR, the product withdrawn from a PMSMPR has exactly the same composition as the vessel at the time of removal. The rapid withdrawal of slurry at high flow rates in PMSMPR operation leads to the prevention of particle sedimentation and blockage of transfer lines. The transfer of slurry (to/from) the PMSMPR is followed by a holding (or pause) period when no addition or withdrawal of slurry takes place. The holding period extends the mean residence time of the PMSMPR relative to a typical MSMPR, thereby increasing the yield and productivity of crystallisation as more time is allowed for consumption of available supersaturation viz crystal growth and nucleation. A state of controlled operation (SCO) in the periodic flow process, defined as a state of the system that maintains itself despite regular, but controlled disruptions was characterised using the PAT tools and CryPRINS within an intelligent decision support (IDS) framework. The crystallisation of paracetamol (PCM) from isopropyl alcohol (IPA) using different configurations of a single-stage continuous MSMPR crystalliser that incorporated continuous recycle and recirculation loop, and a novel design with baffled heat exchanger was investigated. Crystallisations of PCM-IPA carried out in the MSMPR without heat exchanger suffered from severe fouling, encrustation and blockage problems due to the high level of supersaturation (S = 1.39) in the crystalliser, which was required for the initial burst of nucleation to generate enough particles for later growth, as well as the large temperature difference between the incoming feed (45 oC) and the crystalliser (10 oC). Using the modified MSMPR design with baffled heat exchanger, the challenges of fouling, encrustation and blockage were significantly reduced due to the rapid lowering of the feed stream temperature prior to entering the crystalliser. In addition, the closed loop system led to conservation of material, which is a great benefit since large amounts of materials would otherwise be required if the MSMPR was operated with continuous product removal. This design is great for research purposes, in particular, to investigate process design and optimisation. Continuous crystallisation of PCM in the presence of hydroxyl propyl methyl cellulose (HPMC) additive was investigated in the modified MSMPR design with heat exchanger. HPMC was found to improve the crystallisation performance, leading to complete avoidance of fouling, encrustation and blockages at a concentration of 0.05 wt%. However, the yield of crystallisation was significantly reduced (28.0 %) compared to a control experiment (98.8 %, biased due to fouling/encrustation) performed without additive addition. Regardless, the productivity of crystallisation was more than four times that achieved in batch linear cooling (LC) (0.62 0.86 g/L-min) and batch automated dynamic nucleation control (ADNC) (0.24 0.25 g/L-min) runs. Aspects of the periodic flow crystallisation of single- and multi-component (co-crystals) molecular systems have also been examined to demonstrate the concept of state of controlled operation . The single component systems studied were PCM and glycine (GLY), each representative of compounds with slow and fast growth kinetics, respectively. The co-crystal systems investigated were urea-barbituric acid (UBA) and p Toluenesulfonamide-Triphenylphosphine oxide (p-TSA-TPPO). UBA is a polymorphic co-crystal system with three known forms (I, II and III). Form I UBA was successfully isolated in a three-stage periodic flow PMSMPR crystalliser. This study demonstrates the capability of periodic flow crystallisation for isolation of a desired polymorph from a mixture. p-TSA-TPPO exists in two known stoichiometric co-crystal forms, 1:1 and 3:2 mole ratio p-TSA-TPPO, respectively. The two crystalline forms exhibit solution mediated transformation, which proves to be a difficulty for separation. For this study, the implementation of temperature cycles in batch and flow control in semi-batch and periodic PMSMPR crystallisers were investigated to isolate pure 1:1 and 3:2 p-TSA-TPPO, respectively. Different regions of the ternary diagram of p-TSA, TPPO and acetonitrile (MeCN) were investigated. The desired co-crystal form was isolated all crystallisation platforms investigated. However, greater consistency was observed in the semi-batch and PMSMPR operations respectively. Periodic flow crystallisation in PMSMPR is a promising alternative to conventional continuous MSMPR operation, affording greater degrees of freedom operation, slightly narrower RTD profiles, consistent product crystal quality (size, shape and distribution), longer mean residence times, higher yield and productivity and significant reduction in fouling, encrustation and transfer line blockages over prolonged operating periods. Furthermore, the PMSMPR is a versatile platform that can be used to investigate a range of different molecular systems. Relative to batch operation, the PMSMPR can operate close to equilibrium, however, this is dependent on the system kinetics. In addition, retrofitting of batch crystallisers to operate as PMSMPRS fairly simple and require only subtle changes to the existing design space. The integrated array of PAT sensors consisted of attenuated total reflectance ultra violet/visible spectroscopy (ATR-UV/vis), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), focused beam reflectance measurement (FBRM), particle vision microscopy (PVM) and Raman spectroscopy. The results from the studies reported here illustrate very well the use of PAT and information system tools together to determine when the continuous and periodic MSMPR operations reaches a steady-state or state of controlled operation (i.e. periodic steady-state). These tools provided a better understanding of the variables and operating procedures that influence the two types of operations

Automation potential of a new, rapid, microscopy based method for screening drug-polymer solubility

For the pharmaceutical industry, the preformulation screening of the compatibility of drug and polymeric excipients can often be time-consuming because of the use of trial-and-error approaches. This is also the case for selecting highly effective polymeric excipients for forming molecular dispersions in order to improve the dissolution and subsequent bio-availability of a poorly soluble drug. Previously, we developed a new thermal imaging-based rapid screening method, thermal analysis by structure characterization (TASC), which can rapidly detect the melting point depression of a crystalline drug in the presence of a polymeric material. In this study, we used melting point depression as an indicator of drug solubility in a polymer and further explored the potential of using the TASC method to rapidly screen and identify polymers in which a drug is likely to have high solubility. Here, we used a data bank of 5 model drugs and 10 different pharmaceutical grade polymers to validate the screening potential of TASC. The data indicated that TASC could provide significant improvement in the screening speed and reduce the materials used without compromising the sensitivity of detection. It should be highlighted that the current method is a screening method rather than a method that provides absolute measurement of the degree of solubility of a drug in a polymer. The results of this study confirmed that the TASC results of each drug-polymer pair could be used in data matrices to indicate the presence of significant interaction and solubility of the drug in the polymer. This forms the foundation for automating the screening process using artificial intelligence

Selective crystallisation facilitated by nanonucleants for downstream bioseparation of a protein mixture

Bioseparation is a major bottleneck in the manufacture of biopharmaceuticals such as proteins. Crystallisation is a cost-effective, rapid, and robust alternative technology to conventional chromatography steps in downstream separation processes. This thesis aims to investigate protein crystallisation as a feasible approach to separate proteins from a mixture for bioseparation. In this work, lysozyme- thaumatin mixture is used as the model binary protein mixture. Both µL-scale hanging-drop vapour-diffusion (HDVD) and mL-scale batch crystallisation methods were employed. We report an experimental evidence of direct selective protein crystallisation from a binary protein mixture solution where both proteins are supersaturated and crystallisable under an identical crystallisation condition. Results from both methods showed that protein impurity, even at low concentration level, would delay target protein crystallisation with an extended induction time. When silica particles were introduced as nanonucleants to facilitate crystallisation, target protein crystallisation was significantly improved with much shorter induction time. It was also indicated that the effectiveness of silica on crystallisation depended on the type of silica particle, silica loading amount, and impurity concentration. This study also revealed the critical role of agitation in obtaining consistent and reproducible results when moving from preliminary qualitative screenings using HDVD method to quantitative batch crystallisation experiments. Apart from improving reproducibility of crystallisation experiments, agitation also had impacts on both crystallisation rate, yield, and crystal size. In conclusion, this work demonstrates that protein crystallisation is a feasible and scalable methodology to separate a target protein from a complex mixture environment.Open Acces

Control of crystalline particle properties by spray drying

Although spray drying has been common place in the pharmaceutical industry for decades, the integration of the technique into continuous manufacturing can offer an extensive array of particle engineering applications. Continuous manufacturing aims to deliver consistent and sustainable drug products of a better and higher quality. Spray drying is a continuous processing technique typically adopted for amorphous solid production. However, the unique conditions of the technique can also can be adapted and applied to crystallisation enabling particle property engineering. The semi-continuous lab-scale Büchi B-290 Mini spray dryer is widely available and has been previously studied extensively for particle engineering and as a development platform for applications including pulmonary drug delivery, sustained release formulations and amorphous solid dispersions.The focus of this work is to engineer and enhance particle properties through the use of the Büchi spray dryer. Particle formation has been investigated, with specific focus in terms of polymorph formation in carbamazepine, to develop a predictive model for crystallisability and for co-spray drying of metformin hydrochloride with mannitol and lactose. Particle formation has been described in terms of theoretical drying kinetics and combined with off line characterisation to determine size and form of product. The metastable polymorph, form IV, of carbamazepine was made reproducibly by spray drying with the combination of rapid evaporation and product isolation shown to be crucial to prevention of solution mediated transformation. The application of non-invasive Raman spectroscopy was also utilised to assess product form. A crystallisability predictive model based on a Random Forest method was successfully produced through combining molecular descriptors with published and experimental outcomes. The model provided up to 79 % accuracy in predicting whether an amorphous or crystalline product would be expected from rapid drying. This shows considerable utility in streamlining process development. Finally, co-spray drying in the Büchi system using a three-fluid nozzle was used to produce multicomponent composite particles comprising of two crystallite phases. The effect of process configuration and material properties on the resultant particles was assessed using particle sizing, SEM, XRPD and Raman mapping. The results were compared on the basis of theoretical drying kinetics to assess the ability to predict the resultant particle morphology. Four multicomponent composite particles were produced by co-spray drying from metformin hydrochloride (MF), mannitol and lactose. MF-mannitol composites produced three-phase physical mixtures with both components present on the particle surfaces. The particle surface compositions were contradictory to the expected particle outcomes from the drying parameters. MF-lactose composite particle also produce three-phase physical mixtures with a relatively equal distribution of components present on particle surface. This is consistent with the expected particle from the drying parameters. The different particle outcomes suggest that co-spray drying of miscible multicomponent feeds using the three-fluid nozzle is highly dependent on the drying parameters for each component due to equal mixing of the feed at atomisation of droplets.Although spray drying has been common place in the pharmaceutical industry for decades, the integration of the technique into continuous manufacturing can offer an extensive array of particle engineering applications. Continuous manufacturing aims to deliver consistent and sustainable drug products of a better and higher quality. Spray drying is a continuous processing technique typically adopted for amorphous solid production. However, the unique conditions of the technique can also can be adapted and applied to crystallisation enabling particle property engineering. The semi-continuous lab-scale Büchi B-290 Mini spray dryer is widely available and has been previously studied extensively for particle engineering and as a development platform for applications including pulmonary drug delivery, sustained release formulations and amorphous solid dispersions.The focus of this work is to engineer and enhance particle properties through the use of the Büchi spray dryer. Particle formation has been investigated, with specific focus in terms of polymorph formation in carbamazepine, to develop a predictive model for crystallisability and for co-spray drying of metformin hydrochloride with mannitol and lactose. Particle formation has been described in terms of theoretical drying kinetics and combined with off line characterisation to determine size and form of product. The metastable polymorph, form IV, of carbamazepine was made reproducibly by spray drying with the combination of rapid evaporation and product isolation shown to be crucial to prevention of solution mediated transformation. The application of non-invasive Raman spectroscopy was also utilised to assess product form. A crystallisability predictive model based on a Random Forest method was successfully produced through combining molecular descriptors with published and experimental outcomes. The model provided up to 79 % accuracy in predicting whether an amorphous or crystalline product would be expected from rapid drying. This shows considerable utility in streamlining process development. Finally, co-spray drying in the Büchi system using a three-fluid nozzle was used to produce multicomponent composite particles comprising of two crystallite phases. The effect of process configuration and material properties on the resultant particles was assessed using particle sizing, SEM, XRPD and Raman mapping. The results were compared on the basis of theoretical drying kinetics to assess the ability to predict the resultant particle morphology. Four multicomponent composite particles were produced by co-spray drying from metformin hydrochloride (MF), mannitol and lactose. MF-mannitol composites produced three-phase physical mixtures with both components present on the particle surfaces. The particle surface compositions were contradictory to the expected particle outcomes from the drying parameters. MF-lactose composite particle also produce three-phase physical mixtures with a relatively equal distribution of components present on particle surface. This is consistent with the expected particle from the drying parameters. The different particle outcomes suggest that co-spray drying of miscible multicomponent feeds using the three-fluid nozzle is highly dependent on the drying parameters for each component due to equal mixing of the feed at atomisation of droplets

Iterative learning control of crystallisation systems

Under the increasing pressure of issues like reducing the time to market, managing lower production costs, and improving the flexibility of operation, batch process industries thrive towards the production of high value added commodity, i.e. specialty chemicals, pharmaceuticals, agricultural, and biotechnology enabled products. For better design, consistent operation and improved control of batch chemical processes one cannot ignore the sensing and computational blessings provided by modern sensors, computers, algorithms, and software. In addition, there is a growing demand for modelling and control tools based on process operating data. This study is focused on developing process operation data-based iterative learning control (ILC) strategies for batch processes, more specifically for batch crystallisation systems. In order to proceed, the research took a step backward to explore the existing control strategies, fundamentals, mechanisms, and various process analytical technology (PAT) tools used in batch crystallisation control. From the basics of the background study, an operating data-driven ILC approach was developed to improve the product quality from batch-to-batch. The concept of ILC is to exploit the repetitive nature of batch processes to automate recipe updating using process knowledge obtained from previous runs. The methodology stated here was based on the linear time varying (LTV) perturbation model in an ILC framework to provide a convergent batch-to-batch improvement of the process performance indicator. In an attempt to create uniqueness in the research, a novel hierarchical ILC (HILC) scheme was proposed for the systematic design of the supersaturation control (SSC) of a seeded batch cooling crystalliser. This model free control approach is implemented in a hierarchical structure by assigning data-driven supersaturation controller on the upper level and a simple temperature controller in the lower level. In order to familiarise with other data based control of crystallisation processes, the study rehearsed the existing direct nucleation control (DNC) approach. However, this part was more committed to perform a detailed strategic investigation of different possible structures of DNC and to compare the results with that of a first principle model based optimisation for the very first time. The DNC results in fact outperformed the model based optimisation approach and established an ultimate guideline to select the preferable DNC structure. Batch chemical processes are distributed as well as nonlinear in nature which need to be operated over a wide range of operating conditions and often near the boundary of the admissible region. As the linear lumped model predictive controllers (MPCs) often subject to severe performance limitations, there is a growing demand of simple data driven nonlinear control strategy to control batch crystallisers that will consider the spatio-temporal aspects. In this study, an operating data-driven polynomial chaos expansion (PCE) based nonlinear surrogate modelling and optimisation strategy was presented for batch crystallisation processes. Model validation and optimisation results confirmed this approach as a promise to nonlinear control. The evaluations of the proposed data based methodologies were carried out by simulation case studies, laboratory experiments and industrial pilot plant experiments. For all the simulation case studies a detailed mathematical models covering reaction kinetics and heat mass balances were developed for a batch cooling crystallisation system of Paracetamol in water. Based on these models, rigorous simulation programs were developed in MATLAB®, which was then treated as the real batch cooling crystallisation system. The laboratory experimental works were carried out using a lab scale system of Paracetamol and iso-Propyl alcohol (IPA). All the experimental works including the qualitative and quantitative monitoring of the crystallisation experiments and products demonstrated an inclusive application of various in situ process analytical technology (PAT) tools, such as focused beam reflectance measurement (FBRM), UV/Vis spectroscopy and particle vision measurement (PVM) as well. The industrial pilot scale study was carried out in GlaxoSmithKline Bangladesh Limited, Bangladesh, and the system of experiments was Paracetamol and other powdered excipients used to make paracetamol tablets. The methodologies presented in this thesis provide a comprehensive framework for data-based dynamic optimisation and control of crystallisation processes. All the simulation and experimental evaluations of the proposed approaches emphasised the potential of the data-driven techniques to provide considerable advances in the current state-of-the-art in crystallisation control