Bioprocessing of High Concentration Protein Solutions: Quality by Digital Design Approach

Lead Research Organisation: University of Manchester
Department Name: Chem Eng and Analytical Science

Abstract

There is a need for underpinning research to support industrial development of novel protein therapeutics for more convenient delivery by subcutaneous injection (SC). This is an increasing priority for biopharmaceutical companies such that patients can administer the medicines at home, rather than having to visit hospital for a lengthy infusion. The challenge for bioprocessing research is to dissolve the dose of protein required in a small volume, usually 1 ml, that can be self injected. The protein therefore must be soluble up to 300 mg/ml, and it is desirable that the liquid can be stored at 2-8 C for 2 years or more without precipitation, aggregation or other instability. In addition, the liquid must not be too viscous, otherwise the injection will require too high a pressure or may take too long to administer. There is also a need to prevent damage to the protein during the process of forcing the liquid through a narrow needle, into the tissue under the skin.

The proposed research will develop methods for use by industry to screen protein formulations for viscosity and other flow properties, using small quantities of protein. This will enable methods for viscosity reduction to be developed. It is known that similar proteins differ widely (by a factor of two or more) in their viscosity at similar concentrations, and that alterations in co-solvent can reduce the viscosity of a formulation. To achieve this, we propose to apply comprehensive rheological characterisation, RheoChip rheometry, and advanced modelling as a platform, which can be used by industry to select the protein and formulation for development of the final dosage form, at an earlier stage than it is possible today. This should save time and cost in development of many new protein medicines. The research will build on existing methods, which are already well established for rheological characterisation of water soluble polymers and BSA solutions, and adapt and apply them to the bioprocessing and injectability of high concentration protein biopharmaceutical solutions. Comprehensive rheological characterisation of protein solutions has not yet been published. In addition, there is the potential for this new knowledge to be applied in industry to improve the production of biopharmaceutical proteins, as high concentrations may be reached during bioprocessing, e.g. freeze drying, tangential flow filtration (TFF) etc. and there can be difficulties in processing viscous solutions, e.g. nanofiltration for virus removal may be impractical. The deliverables of the project will be the form of instrumentation, rheological characterisation methods more relevant than current viscosity measurement, and computational tools.

The project has five work packages (WPs). WP1 and WP2 will focus on development of new enabling technologies. The output of WP1 will be the first high throughput characterisation platform for screening protein formulations under the flow conditions encountered in bioprocessing while requiring minimal sample. WP2 will construct a computational platform for predictive modelling of concentrated protein fluid flows. WP3 and WP4 will critically validate these enabling technologies using both model and industrially relevant protein solutions under the complex flows, including TFF and SC injection. The output will be an integrated approach for design and optimisation of (nonlinear) scale-up protein production, based on high throughput rheological data obtained from Rheo-chip and predictive modelling of protein flows and protein stability during processing. WP5 will correlate the rheological properties and flow behaviour of concentrated protein solutions with the effects of excipients and/or formulation conditions on the conformational stability and self-association in dilute solution. This will help to establish the molecular determinants of high viscosities and flow induced protein aggregation leading to rational design of high throughput screens.

Technical Summary

Future trends in treating various chronic diseases with recombinantly-produced therapeutic proteins (such as monoclonal antibodies) require frequent and high dose of active protein ingredient in a small volume of liquid (e.g. >100mg/ml for subcutaneous (SC) injections using prefilled syringe or auto-injection device). SC injections will improve the convenience of administration of products for patients, and reduce healthcare costs by greatly reducing the time for the patient to stay in hospital. The convenience of SC administration drives for the development of concentrated protein medicines and poses fundamental challenges for bioprocessing in terms of solubility, stability, manufacturability and drug deliverability.

We will address those fundamental challenges by translating a novel Rheo-chip technology and state-of-the-art numerical techniques of computational rheology into biopharmaceutical industry. Rheo-chip will enable high throughput rheological characterisation of protein formulation, fast evaluation of their stability under industrial and clinical relevant flow conditions using small sample volumes. It will become a unique formulation-screening platform for evaluation of the stability, manufacturability and drug deliverability of protein solutions. The simulation platform can account for spatial distribution of protein aggregates in complex flows. Its uniqueness is to link molecular scale protein-protein interactions, meso-scale of protein aggregations with the macro-scale nonlinear flow behaviour of protein solutions. By integrated with the Rheo-chip platform, it will enable optimal design of unit operations and manufacturing scale-up as well as syringe design for optimal delivery of concentrated protein products from very early stages of drug development that inherently embrace Quality by Digital Design.

Planned Impact

The proposed project is in response to a Call for Proposal by the Bioprocessing Research Industry Club (BRIC). It is based on extensive consultation with BRIC industrial partners on their unmet needs, and will address the fundamental challenges of manufacturing concentrated protein medicines by translating a novel Rheo-chip technology and state-of-the-art numerical techniques of computational rheology into biopharmaceutical industry. The project has relevance to 4 out of the 5 of the BRIC2 Research Priority Areas, including
1) Bioprocessing research challenges for protein products;
2) High-throughput bioprocess development;
3) Effective modelling of bioprocess;
4) Robust and effective analytics for bioprocessing.
It also addresses two key BRIC2 Business Drivers "the direct commercial and competitive value to existing companies from decreasing the time, cost and risk of product development" and "the reduction in capital investment magnitude and risk to existing companies coming from the ability to design intensive, modular and predictable processes that inherently embrace 'quality by design'."

In particular the high throughput Rheo-chip based characterisation platform will be available to fulfil the unmet needs in bioprocessing industry for rapidly screening the manufacturability of a large number of protein formulations in an early stage of drug development. The small sample requirements of Rheo-chips and the measurement protocols developed from the project will permit rapid screening of the design space, including variables such as protein concentration, temperature, solvent conditions (buffer type, excipient, ionic, strength, pH) and in the presence of air interfaces. In-situ rheological and birefringence/velocity field characterisation of protein solution in Rheo-chips will reveal the dynamic mechanisms of the self-assembly and disassembly of the proteins, as well as establish the hydrodynamic conditions which can trigger the aggregation or instability of proteins, hence the link between protein aggregation and stability on storage with the deformation history and interfacial exposure of the sample can be identified. By critical correlation analysis between Rheo-chip results and measurements of protein-protein interactions, we will search for strongly correlated signature between the nonlinear rheological and flow properties of concentrated protein solutions and protein-protein interactions in dilute solution, hence to explore an approach of rationally designing screens to minimize sample use, which combine a small number of rheological measurements on concentrated protein samples with a larger number of measurements of protein-protein interactions in dilute solution.

The predictive simulation platform will be available for design and optimisation of scale-up manufacturing and subcutaneous injection, hence to maximise protein yield and stability, and to accelerate development with reduced costs and risks. The uniqueness of the proposed micro- & macro-coupling computational model is to link molecular scale protein-protein interactions, meso-scale of protein aggregations with the macro-scale nonlinear flow behaviour of protein solutions. Large scale modelling of concentrated protein solutions in ultra-TFF operations, simulations of the turbulence enhancements, sensitivity analysis will allow us to identify the properties of concentrated protein solutions that control fouling, flux and retention during filtration. Therefore the impact of the project on UK and international companies developing and manufacturing therapeutic proteins are expected to be very significant. The ultimate beneficiaries are patients, who will receive treatment in a less invasive and more convenient form. In addition there is the potential of cost savings for healthcare providers such as the NHS when patients are able to self inject subcutaneously, rather than visit hospital for intravenous injection.

Publications

10 25 50
 
Description Formulations with high concentrations of therapeutic proteins (such as monoclonal antibodies) are often required to meet patient dose requirements when treating chronic diseases. Such high concentrations can be a cause of poor rheological properties, phase separation and increased physical degradation of proteins through irreversible aggregation. Overcoming these issues is fundamental for finding formulations that can be delivered through subcutaneous administration and for ease of manufacturing throughout the downstream processing and formulation steps. These challenges were addressed in this work by developing a novel microfluidics technology (called the Rheo-Chip) combined with state of the art computational method. The overarching aim of the work was to develop the Rheo-chip technology as a tool to be used at early stages of drug development and discovery when not much protein material is available. The technology would allow for predictability of manufacturability and design of syringe delivery and unit operations such as filtration.
The key discoveries and developments are as follows:
1. We have designed a novel micro-fluidics chip with superior rheological characterization capabilities. There are many advantages of the rheo-chip when compared to traditional rheometers. The sample consumption is minimized requiring only 0.5 mL of solution for a full rheological characterization in commonly encountered flow geometries that are not accessible with commercial rheometers. In addition, the rheometer can be run with and without an air-water interface. The small diameter channels in the Rheo-chip allow accessing the high shear rates encountered in bioprocessing, which are not possible with commercial rheometers due to inertial effects becoming significant. In addition, most commercial rheometers contain a free air-water interface which gives rise to an apparent rise in the low shear viscosity due to changes in the surface rheology from protein interfacial adsorption. The capability of tuning the air-water interface in the Rheo-chip allowed us to show that shear alone cannot be the cause of physical instability or protein aggregation. The geometry of the microfluidics channel can be designed to mimic flow geometries representative of bioprocessing. In particular, we mimicked the delivery through syringes and in dead-end filtration flows. Lastly, we have engineered into the rheo-chip, the capability to carry out oscillatory flow measurements, which are needed to extract key parameters for concentrated protein solutions exhibiting shear thinning behaviour.
2. We have developed a computational platform for extracting properties from the rheo-chip under different flow conditions that can then be used for industrial flow modelling. In order to simulate the flow of protein solutions we have developed a theoretical approach based on the so-called two fluid model. A numerical solver for the continuity and momentum balance equations derived from this model has been developed using the OpenFOAM platform - a popular open source finite volume code for computational fluid dynamics. Before utilising this continuum approach the model needs to be validated against a microscopic solution method. Towards this goal a solver using the immersed boundary method was developed in OpenFOAM. In contrast to the continuum two fluid model described above, in this approach the proteins are directly modelled as interacting hard spheres immersed in the solvent. This is a difficult problem involving multiple internal boundary conditions, short-range lubrication forces and long-range hydrodynamic interactions. These technical challenges were resolved (Wei et al., 2016a, 2016b) and the code has been made freely available to all researchers in the OpenFOAM codebase
3. Design of syringe injection and dead-end filtation flows: We have designed the rheochip to mimic syringe injection processes and dead-end filtration using model proteins such as albumin as well as therapeutically relevant antibody molecules. Implementing a computational model requires determining the flow field within the microfluidics channel, which has been achieved using micro-particle imaging velocimetry (micro-PIV) experiments. A key outcome of the work was the discovery of shear-thinning behaviour of the protein solutions at typical shear rates used in the syringe injection. The rheo-chip data was used through an iterative process with the computational modelling to guide the experimental design of flow conditions such that the measured rheo-chip pressure drop could be directly related to a syringe injectability force. The forces were actually determined with a commercial syringe injection unit in a collaboration with Novozymes.
4. Predicting concentrated solution properties from dilute solution measurements: There is an urgent need in formulation development to predict concentrated solution properties (eg rheology, phase separation, cloudiness) from measurements made on dilute solutions to minimize sample consumption. Towards this end, we have implemented a suite of complementary experiments to characterize the rheological properties (by the rheo-chip), the thermodynamic behaviour (by static and X-ray light scattering), and transport properties (eg mutual and self-diffusion coefficients, by dynamic static light scattering and fluorescence correlation spectroscopy, respectively). We have shown how simplified models to describe proteins parameterized against the dilute solution behaviour (or protein-protein interaction measurements) can be used for predicting the concentrated thermodynamic and transport properties (Corbett et al 2017). As part of this work, we also showed the limitations of using SAXS experiments for probing protein-protein interactions and the protein solution structure. As yet, a model for rheological properties has not been developed, but nevertheless, we have shown how other concentrated solution properties can be used as indicators for high viscosities or shear thinning behaviour.
Exploitation Route With the Rheo-Chip technology, we are further extending our studies to build a larger dataset of proteins exhibiting different rheological behaviour to further our understanding for the molecular underpinnings of high concentration viscosities. In particular, we are focusing on systems that exhibit transient cluster formation, which occurs either near to phase boundaries or at low ionic strength for charged proteins. These conditions are expected to cause more complex rheological behaviour and increased shear thinning behaviour. Using this data, we will be able to test and refine theories we have developed for the transport properties and are developing for viscosity.
The two fluid model is being further developed by Professor Yuan (at University of Guangzhou) to model diffusion of particles (eg proteins) through semi-permeable membranes. This work is necessary for modelling tangential flow filtration to account for a layer of protein that builds up on the membrane surface (called the concentration polarization layer). The layer of protein controls the transport properties across the membrane and ultimately determines the flux of the solution through the membrane as a function of the imposed flowrate or pressure drop.
Sectors Healthcare,Pharmaceuticals and Medical Biotechnology

 
Description A patent application entitled "Rheometry Apparatus, US 20130125627A1" has been awarded to cover the Rheo-Chip Technology. A key output of the BRIC project was integrating the oscillatory flow capabilities into the Rheo-Chip providing it with capabilities unique to any microfluidics device. As such, much time and effort has been spent exploring opportunities for commercializing the Rheo-Chip Technology through discussions with instrument manufacturers, Wyatt Technology, Malvern Instruments, and Sirius Analytics, who all expressed interest. However, it was concluded that the distinct advantages of the rheo-chip (oscillatory flow, removable pressure sensors, cheaper consumables), would not increase the marketability enough to compete against the rheometers already available through large instrument manufacturers within biopharma. We are still exploring extending the rheo-chip capabilities through integrating in situ detection of aggregates by fluorescent correlation spectroscopy (FCS) and raster image correlation spectroscopy (RICS). A key to success will be further refining the oscillatory flow measurements to higher frequencies, targeting the rheo-chip to a larger market (fine chemicals, home-care and beauty products, small-molecule pharmaceuticals), and developing additional in situ monitoring by confocal microscopy and scattering methods. Alfredo Lanzaro has taken a position at Lund University in the lab of Peter Schurtenberger and will continue developing the Rheo-Chip within that group, who now own a license for the technology. The main impact from the knowledge gained and discoveries of the project are and will be in biopharmaceutical research and development sectors, in particular, formulation groups and downstream processing specialists. Through a collaboration with Novozymes, we showed how the Rheo-Chip could be designed to mimic their Syringe Injection Device for measuring injection forces relevant for subcutaneous delivery of therapeutics. Instrument manufacturer Wyatt Technology provided free loans of equipment (a dynamic light scattering plate reader and the Optim), in exchange for developing the kit as a high throughput rheometric measurement to complement the Rheo-Chip measurements. Some of these advances still need further development before translation to an industrial setting in the form on-going projects. Through a collaboration with Malvern Instruments, we are now exploring how their novel viscosizer technology can complement concentrated solution studies from the Rheo-Chip with dilute solution measurements of rheological behaviour. Further, the models for extrapolating dilute solution measurements to predict concentrated solution rheology are being further developed in a collaboration with MedImmune. Our close relationships with industry and academic experts has facilitated the dissemination and communication of results for instance through meetings with the industrial advisory board (including GSK, UCB, FujiFilm Diosynth, Arecor, Wyatt, Albumedix)) as part of our EPSRC future formulation of complex products grant (led by UCL) or bi-annual project meetings involving all partners of our EU ITN training grant (including Roche, Wyatt, MedImmune, Novozymes, Danish Technical University, LMU Munich, University of Lund). The pharmaceuticals sector in the UK consists of over 500 companies and includes the top 20 global pharmaceutical companies with an estimated turn-over of £32.4 billion. The business employs over 70,000 people, where 23,000 are employed in highly skilled research and development. The benefits gained by the industry from academic research, in terms of expertise, know-how, and intellectual property, have contributed significantly to the strength of the sector in the past. It is imperative to continue the collaborative efforts. The academic and industrial network of contacts we established through the BRIC community provided the foundation for follow-on funding to establish larger consortia. This concerted effort is needed to maximize the impact from academic research in addressing the key challenges faced by the industry. A good illustration is given by the need for a database comprising experimental data for a large number of therapeutic molecules in different formulation conditions taken with state of the art methods used in development. This data would be invaluable for developing improved and more efficient screening protocols and enable predictive algorithms. While such a large dataset does exist, it is not publicly available due to industrial confidentiality agreements. Through the consortia, more than 30 therapeutics have now been made available for a systematic screen that is currently being undertaken. The data is being used to populate our own publicly available webserver, which is being refined throughout the process for predicting therapeutic manufacturability. The screening programme is providing immediate benefits to the industrial members of the consortia in terms of enhanced knowledge of their therapeutics, but the webserver also provides a route for exploitation of the findings by the wider community. We envision the consortia are setting an international standard for the benefits of academic research driven by industrial needs within the biopharmaceuticals sector. Lastly, a gap of young bioformulation scientists has been emphasized by industry directors at recent UK formulation meetings. The grant has trained two PDRAs, Daniel Corbett, whom is employed as a researched on a MedImmune funded formulation grant and Alfredo Lanzaro, whom is working with Peter Schurtenberger at Lund University on a project to further develop the Rheo-Chip Technology. The project is also indirectly related to training a large number of scientists through helping establish the follow-on projects and numerous case studentships.
First Year Of Impact 2015
Sector Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology
Impact Types Economic

 
Description EPSRC Future formulation of complex products
Amount £2,380,872 (GBP)
Funding ID EP/N025105/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 07/2016 
End 06/2021
 
Description EU Innovative Training Networks, Call: H2020-MSCA-ITN-2015
Amount € 4,067,740 (EUR)
Organisation European Commission 
Department Horizon 2020
Sector Public
Country European Union (EU)
Start 02/2016 
End 02/2021
 
Title A publicly available database for solubility prediction of biopharmaceuticals 
Description A key stumbling block to predicting solubility or aggregation propensity is the lack of comprehensive database relating behaviour to structure along with a suite of tools/algorithms for mining the data and testing predictions. Towards this end, we have developed a publicly accessible web server that uses our in-house and freely available software and algorithms for solubility prediction, in a user-friendly graphics window. The software is used to calculate a variety of different properties from protein amino acid sequence and/or protein structural data. Properties calculated for sequences include: amino acid compositions; combinations of charges to give net predicted charge, fraction charged, predicted isoelectic point, ratio of conservative amino acids; propensity for disorder; and ß-strand/sheet forming propensity. These properties are calculated as averages over the entire sequence and as minimal/maximal values in windows of 21 and 51 amino acids along the sequence. For structures and structural models, properties calculated include: patch non-polarity, calculated as non-polar solvent accessible surface area (SASA) divided by polar SASA, size distribution of charged patches (positive and negative, including the largest patches) from Finite Difference Poisson Boltzmann (FDPB) calculations; average contact order for heavy atoms in the protein, relating to the degree of close packing as an empirical proxy for structural stability. Charge patches are dependent on ionic strength and pH, features that are also part of FDPB calculations, which allows us to account for ionic strength and/or pH effects on solubility. The philosophy of our website is to make all software available both to use online, and as downloadable code for in-house use. 
Type Of Material Antibody 
Year Produced 2016 
Provided To Others? Yes  
Impact none as yet 
URL http://www.protein-sol.manchester.ac.uk/
 
Description European Network Collaboration 
Organisation Ludwig Maximilian University of Munich (LMU Munich)
Country Germany 
Sector Academic/University 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation Lund University
Country Sweden 
Sector Academic/University 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation MedImmune
Country United States 
Sector Private 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation Novozymes
Country Denmark 
Sector Public 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation Technical University of Denmark
Country Denmark 
Sector Academic/University 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation University of Copenhagen
Country Denmark 
Sector Academic/University 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description European Network Collaboration 
Organisation Wyatt Technology Corporation
Country United States 
Sector Private 
PI Contribution We helped write the successful proposal for the Marie Curie ITN training grant, which supports 15 PhD students across the consortium. 4 of the PhD students will be enrolled at Manchester.
Collaborator Contribution Each of the members of the consortium is contributing towards generating an unprecedented dataset for use in biopharmaceutical formulation design. Contributions cover skills and expertise, as well as access to experimental equipment and protein availability.
Impact The collaboration has just commenced this year. PhD students will start in July 2016
Start Year 2014
 
Description MedImmune 
Organisation MedImmune
Country United States 
Sector Private 
PI Contribution I have spent a part time sabbatical visiting MedImmune during 2013. We recently were awarded a BBSRC LINK grant at the end of 2014 for studying biopharmaceuticals formulation.
Collaborator Contribution MedImmune are supporting 2 PDRAs at Manchester over a four year period
Impact See publication outcomes
Start Year 2011
 
Title Addition to OpenFOAM project 
Description The software developed in the project has been uploaded to the OpenFOAM project, which is free and publicly available. 
Type Of Technology New/Improved Technique/Technology 
Year Produced 2016 
Impact The main developments include corrections and improvements to the immersed boundary layer method and the two-fluid model for simulations of particles (eg proteins) under flow.