The Journal of Supercritical Fluids 173 (2021) 105204 Contents lists available at ScienceDirect The Journal of Supercritical Fluids journal homepage: www.elsevier.com/locate/supflu Application of Quality by Design to the robust preparation of a liposomal GLA formulation by DELOS-susp method a,1 Josep Merlo-Mas , Judit Tomsen-Melero a,b,c,1 , José-Luis Corchero , Elisabet González-Mira , c,d b,c ]] ]]]]]] ]] Albert Font , Jannik N. Pedersen , Natalia García-Arandac,g, Edgar Cristóbal-Lecinac,h, e,2 f Marta Alcaina-Hernandoa,1, Rosa Mendozac,d, Elena Garcia-Fruitósc,d,3, Teresa Lizarragae,2, Susanne Reschi, Christa Schimpeli, Andreas Falki, Daniel Pulidoc,h, Miriam Royoc,h, Simó Schwartz Jr.c,g, Ibane Abasoloc,g, Jan Skov Pedersenf, Dganit Daninoj, Andreu Soldevilae,2, Jaume Vecianab,c, Santi Salaa,1, Nora Ventosab,c, , Alba Córdobaa, ,1 ⁎ ⁎⁎ a Nanomol Technologies S.L., 08193 Cerdanyola del Vallès, Spain b Institut de Ciència de Materials de Barcelona, ICMAB-CSIC, 08193 Bellaterra, Spain c Centro de Investigación Biomédica en Red – Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain d Institut de Biotecnologia i Biomedicina (IBB-UAB), 08193 Cerdanyola del Vallès, Spain e Leanbio S.L., 08028 Barcelona, Spain f Department of Chemistry and Interdisciplinary Nanoscience Center (iNANO), Aarhus University, 8000, Aarhus, Aarhus C Denmark g Functional Validation and Preclinical Research, Drug Delivery & Targeting, CIBBIM-Nanomedicina, Vall d′Hebron Institute of Research (VHIR), Universitat Autònoma de Barcelona (UAB), 08035 Barcelona, Spain h Institut de Química Avançada de Catalunya (IQAC-CSIC), 08034 Barcelona, Spain i BioNanoNet Forschungsgesellschaft mbH, 8010 Graz, Austria j CryoEM Laboratory of Soft Matter, Faculty of Biotechnology and Food Engineering, Technion – Israel Institute of Technology, 32000 Haifa, Israel H IGHL IGH TS GRA PHICA L A B ST RAC T • Robust preparation of liposomal for- mulation by DELOS-susp method. • Implementation of Quality by Design methodology to liposomes preparation. • Influence of critical parameters on Quality quality was studied through DoE ana- by Design lysis. • Design Space was obtained for GLA- loaded liposomes formulation. Abbreviations: BCA, Bicinchoninic acid assay; Chol, Cholesterol; Chol-PEG400-RGD, Cholesterol pegylated with arginyl–glycyl–aspartic (RGD) acid peptide; CMA, Critical Material Attributes; CO2, Carbon dioxide; CoA, Certificate of Analysis; CPP, Critical Process Parameters; CQA, Critical Quality Attribute; Cryo-TEM, Cryogenic Transmission Electron Microscopy; DELOS-susp, Depressurization of an Expanded Liquid Organic Solution into aqueous solution; DLS, Dynamic Light Scattering; DMSO, Dimethyl sulfoxide; DoE, Design of Experiments; DPPC, 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine; EA, Enzymatic Activity; EE, Entrapment Efficiency; EHS, Environment, Health and Safety; EMA, European Medicines Agency; ERT, Enzyme Replacement Therapy; EtOH, Ethanol; FDA, Food and Drug Administration; fsingle, Ratio of monolayered liposomes; GLA, α-ga- lactosidase A enzyme; H2O, Water; HPLC, High Performance Liquid Chromatography; ICH, Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use; LSD, Lysosomal storage disorders; MKC, Myristalkonium chloride; N2, Nitrogen; nanoGLA, GLA-loaded nanoliposomes; NTA, Nanoparticle Tracking Analysis; PEG, Polyethylene Glycol; PLS, Partial Least Squares; PdI, Polydispersity Index; PIC, Pressure Indicator Controller; Pw, Working pressure; QbD, Quality by Design; RGD, Arginine- Glycine-Aspartic acid; SAXS, Small-Angle X-ray Scattering; SbD, Safe by Design; SDS-PAGE, Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis; S-MLS, Static Multiple Light Scattering; TFF, Tangential Flow Filtration; TGX, Trys-Glycine eXtended; TIC, Temperature Indicator Controller; TSI, Turbiscan Stability Index; Tw, Working temperature; USP, United States Pharmacopeia; XCO2, Carbon dioxide molar fraction ⁎ Corresponding author at: Institut de Ciència de Materials de Barcelona, ICMAB-CSIC, 08193 Bellaterra, Spain. ⁎⁎ Correspondence to: Nanomol Technologies SL, Mòdul de Recerca B, Edifici IBB, Campus de la UAB, 08193 Cerdanyola del Vallès, Spain. E-mail addresses: ventosa@icmab.es (N Ventosa), acordoba@nanomol-tech.com (A Córdoba). 1 (www.nanomol-tech.com). 2 (www.leanbiopro.com). 3 Department of Ruminant Production, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), 08140 Caldes de Montbui, Spain. https://doi.org/10.1016/j.supflu.2021.105204 Received 26 October 2020; Received in revised form 12 February 2021; Accepted 14 February 2021 Available online 19 February 2021 0896-8446/© 2021 The Authors. Published by Elsevier B.V. CC_BY_NC_ND_4.0 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 A R T I C L E I N F O A B S T R A C T Keywords: Fabry disease is a lysosomal storage disease arising from a deficiency of the enzyme α-galactosidase A (GLA). Quality by Design The enzyme deficiency results in an accumulation of glycolipids, which over time, leads to cardiovascular, DELOS cerebrovascular, and renal disease, ultimately leading to death in the fourth or fifth decade of life. Currently, Scale-up lysosomal storage disorders are treated by enzyme replacement therapy (ERT) through the direct administration Protein-loaded liposomes of the missing enzyme to the patients. Fabry disease In view of their advantages as drug delivery systems, liposomes are increasingly being researched and utilized α-galactosidase in the pharmaceutical, food and cosmetic industries, but one of the main barriers to market is their scalability. Depressurization of an Expanded Liquid Organic Solution into aqueous solution (DELOS-susp) is a compressed fluid-based method that allows the reproducible and scalable production of nanovesicular systems with re- markable physicochemical characteristics, in terms of homogeneity, morphology, and particle size. The objective of this work was to optimize and reach a suitable formulation for in vivo preclinical studies by implementing a Quality by Design (QbD) approach, a methodology recommended by the FDA and the EMA to develop robust drug manufacturing and control methods, to the preparation of α-galactosidase-loaded nanoliposomes (nanoGLA) for the treatment of Fabry disease. Through a risk analysis and a Design of Experiments (DoE), we obtained the Design Space in which GLA concentration and lipid concentration were found as critical parameters for achieving a stable nanoformulation. This Design Space allowed the optimization of the process to produce a nanoformulation suitable for in vivo preclinical testing. 1. Introduction efficacy studies in mice (200 µg/mL). Besides, the enzyme entrapment efficiency in the liposomes was below 40% [4]. The addition of cationic One of the main challenges to produce advanced materials such as surfactant myristalkonium chloride (MKC) into the formulation in low enzyme-loaded liposomes is the successful implementation of new concentration allowed to increase the drug entrapment efficiency as manufacturing nanotechnologies at industrial scale. The DELOS-susp well as the colloidal stability of the system [7]. However, further work method is a compressed fluid-based technology that allows the re- was required in order to obtain a stable formulation with the proper producible preparation of different nanovesicular systems with re- protein concentration. markable physicochemical characteristics, in terms of homogeneity, In this work we applied the Quality by Design (QbD) approach to morphology and particle size, as well as a high versatility to integrate determine formulation and process parameters that could have an different active compounds, that can lead to innovative nanomedicines important impact on nanoGLA attributes when prepared by DELOS-susp. with enhanced efficiency [1–3]. The QbD methodology is described in Guidelines of the International Lysosomal storage disorders (LSD) are diseases caused by lysosomal Council for Harmonisation of Technical Requirements for Pharmaceuticals dysfunction usually as a consequence of deficiency of a single metabolic for Human Use (ICH) [8–10] and it is strongly encouraged by the Food and enzyme. In the case of Fabry disease, the lack of α-galactosidase A Drug Administration (FDA) and the European Medicines Agency (EMA) to (GLA) enzyme causes the accumulation of glycosphingolipids leading to develop robust drug manufacturing and control methods. Pharmaceutical multiple organ pathology [4]. Enzyme replacement therapy (ERT), QbD is a systematic approach to development that aims to ensure the which is the main current treatment, exhibits several drawbacks mainly quality of medicines, identifying characteristics that are critical to quality related to protein instability and low efficacy [5]. from the patient’s perspective, translating them into the product Critical To overcome the main limitations of the current ERTs (e.g. rapid Quality Attributes (CQAs), and establishing a relationship between man- enzyme degradation, high immunogenicity, short circulation half-life, ufacturing variables and CQAs through a Design of Experiments (DoE). poor biodistribution, and limited efficacy among others [6]) a strategy The goals of the pharmaceutical QbD may include the achievement of under development consists in the encapsulation of the GLA enzyme meaningful product quality specifications as well as the reduction of into nanoliposomes. Such encapsulation aims to protect the enzyme, product variability and defects, to increase efficiencies and to enhance root decrease the degradation and immunogenicity of GLA, and increase its cause analysis [11]. plasma half-life. Moreover, the addition of a targeting peptide on the Another systematic methodology used in pharmaceutical design is liposomal membrane can facilitate cellular up-take via peptide re- the Safe by Design (SbD) approach, which aims to eliminate possible ceptors recognition and could help to improve GLA biodistribution. risks to the human health and the environment at early innovation Thus, GLA-loaded nanoliposomes (nanoGLA) functionalized with Ar- stages, i.e., during the design or planning stage [12]. SbD requires a full ginine-Glycine-Aspartic acid (RGD) peptide and prepared by DELOS- life cycle perspective combined with nanomaterial sustainability susp, have recently been reported to increase enzymatic activity and (environmental, social, and economic) [13] improvements, to avoid the intracellular penetration, showing the great potential of this CO2-based shifting of potential risks across development stages. methodology for the simple production of protein-nanoliposome ther- In this framework, we report here the implementation of the QbD apeutic conjugates [4,7]. Fig. 1 shows the DELOS-susp process and the approach to develop a robust process for the preparation of nanoGLA. In starting materials used to obtain the nanoGLA liposomal formulation. the present work, the process was scaled-up from previous work [4] by a The results obtained in earlier stages of nanoGLA development, al- 7-fold factor, and the liposomal prototype was optimized increasing though being biocompatible and showing interesting in vitro activity, 10-times (i.e. from around 20 to 200 µg/mL) the final concentration of presented some limitations regarding formulation characteristics for GLA enzyme in the nanoformulation. Its physicochemical stability was continuing with their translation towards the clinics. In first place, the improved while meeting the defined quality specifications in order to concentration of GLA enzyme we could load into the nanoliposomes, fulfill the required therapeutic doses for advanced preclinical testing. with robust particle size and PdI, was around 20 µg/mL, far below the Besides, a SbD evaluation of the nanoGLA manufacturing process by minimum required for reaching those doses that will allow to perform DELOS-susp is also presented. 2 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Fig. 1. Schematic representation of the DELOS-susp method for the preparation of GLA loaded nanoliposomes (nanoGLA). The proce- dure includes: a) Loading of an organic solu- tion containing the liposome membrane com- ponents (Cholesterol, DPPC, Cholesterol- PEG400-RGD, MKC) into the high pressure vessel; b) Addition of compressed CO2 until a certain pressure to produce a CO2-expanded solution, where all membrane components re- main dissolved in a single liquid phase; and c) Depressurization of the expanded solution over an aqueous solution containing the GLA en- zyme at atmospheric pressure, obtaining the protein-liposomes nanoconjugates. Figure adapted from [4]. 2. Materials and methods stirring for approximately 15 min to achieve a complete homogeniza- tion and to attain thermal equilibration. A given volume of GLA stock 2.1. Materials solution at 0.28 mg/mL, measured by SDS-PAGE, was dissolved in ul- trapure water to reach the desired enzyme concentration (7, 17 or GLAcmycHis protein (GLA) was synthetized as explained in 27 µg/mL). To form the nanoconjugates, the volumetrically expanded Appendix A. 1,2-Dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) was organic phase was depressurized over the aqueous solution containing purchased from Corden Pharma (Liestal, Switzerland), cholesterol was the GLA. In this way, nanoGLA DELOS-susp batches of 290–500 mL purchased from Panreac Química (Castellar del Vallès, Spain), and myr- were obtained. In this step, a flow of compressed N2 was used as a istalkonium chloride (MKC) from United States Biological (Salem, US). plunger to push down the CO2‐expanded solution from the vessel and to Cholesterol pegylated with arginyl–glycyl–aspartic acid peptide maintain a constant pressure of 10 MPa inside the vessel during de- (Chol-PEG400-RGD) was synthetized as described by E. Cristóbal-Lecina pressurization. Average time per experiment was 60 min and the re- et al. [14]. Ethanol (EtOH) was purchased from Scharlab (Sentmenat, sulting dispersions of nanoconjugates were stored at 4 °C until their Spain), dimethyl sulfoxide (DMSO) from Sigma-Aldrich (St. Louis, US), characterization. The process parameters that were kept constant for all carbon dioxide (CO2) and nitrogen (N2) from Carburos Metálicos experiments are listed in Appendix B. (Cornellà de Llobregat, Spain). Diafiltration column modules of 300 kDa cut-off were purchased from Repligen (Waltham, US). Ultra- 2.2.2. Separation of the free GLA from the nanoGLA liposomal dispersion pure Type I water (H2O), purified using Milli-Q Advantage A10 by diafiltration and concentration process equipment from Millipore Corporation (Burlington, US), was used for The non-conjugated GLA enzyme (with a molecular weight between all studies. 90 and 110 kDa in its dimer form) was separated from the GLA-loaded liposomes obtained by DELOS-susp using a KrossFlo Research IIi 2.2. Methods Tangential Flow Filtration (TFF) System with mPES hollow fiber mod- ules of 300 kDa cut-off, in order to determine the GLA entrapment ef- 2.2.1. NanoGLA preparation ficiency (EE) [4]. A volume of 10 mL of liposomal sample was added to DELOS-susp methodology was used for the nanoGLA preparation the sample container, which was connected to the column and the (Fig. 1). An EtOH:DMSO solution (volume ratio EtOH:DMSO 4:1) con- buffer reservoir. Six diafiltration cycles were performed with ultrapure taining DPPC (from 0.86 to 3.46 mg/mL), cholesterol (from 0.30 to Type I water to eliminate the free molecules and the organic solvent 1.24 mg/mL), Chol-PEG400-RGD (from 0.03 to 0.31 mg/mL), and MKC present in the liposomal samples. (from 0.02 to 0.07 mg/mL) at a working temperature (Tw) of 308 K was Concentration of the intermediate nanoGLA during the optimization loaded into a 50 mL high pressure vessel at atmospheric pressure. The step was performed using the same equipment, materials, and condi- solution was, then, volumetrically expanded with compressed CO2 until tions. A volume of 50 mL of diafiltrated sample was added to the sample a molar fraction (XCO2) of 0.55 was achieved, reaching a working container and submitted to a 7.5 concentration factor, evacuating ca. pressure (Pw) of 9 MPa. The system was kept at 308 K and 9 MPa under 87% of water. 3 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 2.2.3. Characterization of liposomes liquid Ga metal jet X-ray source (Excillum AB, Sweden) and scatterless 2.2.3.1. Mean particle size, PdI and ζ-potential. Liposomal mean size, slits. The wavelength was λ = 1.34 Å and the measurements were polydispersity index (PdI) and ζ-potential were determined by Dynamic performed 1 week after production. The data were analyzed by a model Light Scattering (DLS), using a Zetasizer Nano ZS analyzer (Malvern similar to the one described in [16,17]. The model was expressed so Instruments, Malvern, UK). The measurements were performed at 20 °C that the fraction of bilayers presented as single-layered vesicles, fsingle, with a scattering angle of 173°, immediately after liposomes’ preparation, was a fit parameter. and 1 and 2 weeks after the production. 2.2.3.5. Entrapment efficiency. The entrapment efficiency (EE) was 2.2.3.2. Turbiscan Stability Index. Turbiscan Stability Index (TSI) was determined by comparing the amount of enzyme encapsulated in the determined by Static Multiple Light Scattering (S-MLS), using a nanovesicles after removal of free enzyme by diafiltration (Loaded Turbiscan Lab Expert (Formulaction, Toulouse, France), at 20 °C and prototype) with the amount of initial GLA present in the DELOS-susp 2 weeks after liposomes production. batch just after its production (Total prototype), see Eq. (1) (Entrapment efficiency calculation): 2.2.3.3. Morphology. The morphology of the systems was studied using mass GLALoaded Cryogenic Transmission Electron Microscopy (Cryo-TEM). Images were EE = ·100 mass GLATotal (1) obtained with a FEI Tecnai G2 12 microscope (FEI, The Netherlands) operating at 120 kV, as described in [15]. The analysis was performed 1 To detect and quantify the enzyme in each of these samples, SDS- week after samples production. PAGE was performed by using gels TGX Stain-Free™ FastCast™ acryla- mide 12% (Bio-Rad, ref. 161-0185). To visualize the fluorescent bands, 2.2.3.4. Uni-lamellarity. Quantitative information on the liposomes a ChemiDoc™ Touch Imaging System (Bio-Rad) was used. Samples and degree of lamellar structure and bilayer thickness was investigated standards to be quantitatively compared were run in the same gel and with small-angle X-ray scattering (SAXS) on an optimized NanoSTAR processed as a set. Densitometric analysis of the bands were performed SAXS instrument (Bruker AXS, Karlsruhe, Germany) equipped with a with the Image Lab™ software (version 5.2.1., Bio-Rad). Fig. 2. Process Flow Diagram to produce the nanoGLA. Raw materials and the materials leaving the process are also represented. In red, the intermediate nanoGLA formulation obtained by DELOS-susp that has been studied in the QbD implementation. Diafiltration and concentration processes are necessary to remove the remaining free GLA and organic solvents from the nanoformulation and to maximize the enzyme concentration in the final nanoformulation for preclinical studies, respectively. 4 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 2.2.3.6. Enzymatic activity. The α-galactosidase specific enzymatic concentration, which cannot be directly achieved in the DELOS-susp activity (EA) of liposomal formulations was assayed using step because of the limited solubility of the liposome membrane com- 4-Methylumbelliferyl α-D-galactopyranoside (4-MUG, Sigma Chemical) ponents in the organic phase, while keeping the nanoformulation as substrate, at a concentration of 2.46 mM in assay buffer (0.01 M acetic quality. acid, pH 4.5) as previously described [18]. The released product (4-methylumbelliferone) was determined by fluorescence measurement 3.1. Identification of the Critical Quality Attributes (CQAs) (λexc = 365, λem = 450 nm) and final specific enzymatic activities were shown as 4-methylumbelliferone μmol per time and protein During the development of liposomal drug products, the identifi- quantity. Measurements were performed 1 week after production of cation and pertinent characterization of CQAs of liposomal drug the samples. products is one of the main challenges from the quality point of view, together with the definition of proper control strategies. Liposomal 2.2.4. Experimental design and data processing products are complex formulations and small changes in their physi- An experimental design with 4 factors at 2 levels with 2 central cochemical attributes can have notable effects in their in vivo perfor- points (resulting in a total of 10 experimental runs) was constructed in mance. Thus, a suitable definition of CQAs and control strategies may order to study the influence of formulation parameters (independent allow a faster and more efficient drug product development [19]. variables or factors) on the properties (dependent variables or re- Table 1 shows the CQAs selected for QbD implementation related to the sponses) of nanoGLA dispersion. The selected experimental design was intermediate nanoGLA liposomal dispersion. The definition of the a Fractional Factorial design, and it was developed using Modde 12 Pro quality attributes has considered the ICH recommendations, as well as software (Umetrics, Sweden). Data fitting and calculation of statistical FDA and EMA guidelines [10]. parameters were performed by partial least squares (PLS) method. The As a parenteral dosage form, liposomal products must be sterile and experimental design used in this study allowed fitting the data with a pyrogen-free. These parameters are not considered as CQAs at this stage linear regression interaction model. The acceptance of the responses of formulation development since it is an intermediate product, but obtained was evaluated by means of the statistical parameters predicted they must be considered as CQAs in the final formulation. by the software R2, Q2 model validity, and model reproducibility. The design space for nanoGLA was determined using Design Space Explorer 3.2. Risk assessment and control strategies option from the Optimizer module of Modde 12 Pro software. Risk assessment is a valuable science-based process used in quality risk 3. Results and discussion management that can aid in identifying which material attributes and process parameters potentially influence product CQAs [11,22]. The The process flow diagram of the whole nanoGLA optimized manu- potential risk factors which might influence the quality of the product facturing process is presented in Fig. 2. Membrane components, sol- were identified through risk analysis, creating the Ishikawa diagram for vents, and gases, as well as the GLA protein, were processed using each CQA defined for nanoGLA (see Appendix C, where the detailed risk DELOS-susp (see Section 2) obtaining an intermediate nanoGLA dis- analysis assessment is presented). As a result, 4 formulation factors were persion, whose quality was studied by QbD. Then, the optimized in- considered relevant to be included in the subsequent DoE analysis: GLA termediate nanoGLA was diafiltrated and concentrated by TFF in order concentration, lipid concentration, peptide content in the liposomal to remove the organic solvents and to reach the target enzyme membrane, and ethanol concentration. The justification regarding the Table 1 CQAs defined for the intermediate nanoGLA liposomal dispersion obtained by DELOS-susp and their justification. Quality Attribute Justification [19–21] Macroscopic Appearance It must be a homogeneous opalescent dispersion without sedimentation. Sedimentation could indicate poor colloidal stability. Mean Particle Size Particle size and particle size distribution are major CQAs for nanoparticle-based systems, playing an important role in determining their in vivo absorption and distribution, drug loading, drug release, and targeting ability. Therefore, robust control of particle size is one of the crucial parameters for further in vivo application of liposomal drug products. Values below 300 nm are considered acceptable for nanoGLA. Polydispersity Index (PdI) PdI reflects the heterogeneity of the particle size, indicating how wide is the particle size distribution. The lower the PdI, the higher the homogeneity of the dispersion. To meet specification, PdI should be below 0.45. ζ-potential Important parameter in the evaluation of colloidal system’s stability. Particles with a high negative or positive ζ- potential value repel each other, indicating that the colloidal system is stable. On the contrary, decreasing the ζ- potential value to nearly neutral could lead to liposomal aggregation. The liposome surface charge can also influence drug loading, cellular uptake, tissue distribution, and clearance. ζ-potential values higher than + 30 mV are considered inside the specification range for nanoGLA. Particle morphology and lamellarity Vesicles must be spheroidal and, mostly, uni-lamellar. Lamellarity can affect drug loading and release, thus, impacting the enzyme delivery. GLA Entrapment Efficiency (EE) /Free drug substance Free drug substance may have side effects and impact into pharmacokinetic profile. Besides, a high and reproducible percentage of drug entrapment could reduce manufacturing costs and increase drug concentration in the final formulation allowing greater flexibility in dosing. Depending on the pharmacokinetics, higher drug concentration can result in increased dosing intervals and hence improved patient compliance. Specific Enzymatic Activity (EA) The bioactivity of the integrated enzyme must be preserved in the nanoformulation. EA ratio to control should be higher than 0.8, referred to the EA of a commercially available GLA (agalsidase alfa, Replagal®). Integration efficiency of Chol-PEG400-RGD in the The amount of targeting peptide moiety integrated in the nanoliposomal membrane must be in the proper ranges vesicular membrane to allow the nanoGLA to interact with cells and facilitate intracellular penetration. pH pH can affect dispersion stability, drug loading and release, and cell uptake among others. A suitable pH range is from 6.0 to 7.0. Dispersion stability The intermediate formulation must be stable at least until the diafiltration and concentration step. In terms of Turbiscan stability, the TSI should be less than 10.0 at 24 h. Lipid and GLA degradation products Chemical stability of the lipid components in the liposome as well as the chemical stability of the contained drug substance is important. These will be considered at further stages of development. 5 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 selection of these factors and their range of investigation is detailed in 3.4. Characterization of the intermediate nanoGLA obtained Table 2. Although the depressurization flow rate during the DELOS-susp A high variability on the stability of the samples was observed could be considered as a factor [30], it was not included in the present among the different experimental conditions tested. Thus, some char- work since an accurate flow rate range variation could not be carried acterizations were performed at the production day (t = 0) and fol- out in the used set-up. Due to limitations of the available in-house lowed until 14 days. synthesized starting materials (GLA and Chol-PEG400-RGD), an inter- Regarding the macroscopic appearance, all DELOS-susp batches mediate laboratory plant was selected for performing the DoE. Thus, for presented a homogenous, whitish, opalescent appearance without pre- this first QbD study the depressurization flow rate was kept constant at sence of sediment, except for DOE-001, DOE-006, and DOE-009. 6.3 ± 0.7 g/min because it can be controlled within narrow values A summary of the microscopy analysis of the nanoGLA samples by where the formulation requirements are ensured. So, despite not being cryo-TEM is presented in Fig. 3, indicating that for all experiments able to introduce the flow rate as a factor in the present study, this nanovesicles were obtained, being mostly uni-lamellar and spherical, parameter was defined as a controlled variable that was kept constant and ranging between 100 and 200 nm, with the presence of some larger for all experiments. QbD is based on the principle of continuous im- vesicles around 500 nm. provement, thus, by gathering knowledge during early development, it Table 4 shows a summary of the characterization results of the DoE is possible to avoid potential manufacturing problems as the drug samples, which were considered for the statistical analysis. The three out of product evolves through the development pipeline. Thus, the knowl- ten batches (DOE-001, DOE-006, and DOE-009) that presented small se- edge obtained in the present study will allow to concisely define further dimentation also showed a higher TSI indicating the dispersion instability. scale-up studies. The influence of DELOS-susp depressurization flow Besides, samples in which aggregation and sedimentation were ob- rate variation on the nanoGLA quality will be more accurately eval- served presented also higher size and PdI, and lower uni-lamellarity. uated in future studies at pilot plant scale, where it is possible to control Furthermore, the mean particle size and PdI of DOE-001, DOE-006, and and register this parameter. Taking the present results as the basis for DOE-009 significantly increased with time after production (Appendix D). refining the Design Space of the nanoGLA will ease this transition from On the other side, ζ-potential, EE, and EA values did not correlate with the lab to the pilot plant. macro and microscopical characteristics of the samples. All the formulations showed enzymatic activity, varying from 0.8 to 1.7 ratio to control referred to the enzymatic activity of a commercially 3.3. Experimental design and development available free GLA (Agalsidase alfa, Replagal® from Shire-Takeda) in- cluded in the analysis, as also shown in Table 4. These results indicate An experimental design was constructed to study the influence of an excellent enzymatic activity in all cases, compliant with preliminary the formulation (independent variables or factors) on the physico- specifications. chemical properties (dependent variables or responses) of intermediate nanoGLA obtained by DELOS-susp, as shown in Table 3. Low and high levels for each factor (Table 2) were selected based on previous ex- 3.5. Analysis of the influence of the factors on CQAs periments and studies [4,7]. All process parameters, including depressurization flowrate at The influence of the factors was studied for the rest of dependent 10 g/min, were kept constant for all experiments. The responses of the variables or CQAs. An analysis and discussion for each quantifiable experimental design were the CQAs of the intermediate nanoGLA dis- CQA is described below. From the characterized CQAs, mean particle persion: particle mean size, polydispersity index, ζ-potential, Turbiscan size, ζ-potential, and uni-lamellarity could be statistically fitted and stability index, ratio of monolayered liposomes, entrapment efficiency, were included in the prediction model (see Appendix E for modeling enzymatic activity, and pH. Furthermore, macro and microscopic ap- and data fitting) while for the rest of attributes a bad correlation was pearance (i.e. particle morphology) were analyzed, but these two CQAs obtained and thus a poor predictive ability of the model. were not included in the design because of their qualitative nature. The According to the data presented in Table 4, the mean particle size of matrix of the experimental design is presented in Table 3. the nanoGLA dispersions varied from 90 to 200 nm. These differences All experiments were produced following DELOS-susp method at the could be explained because of the aggregation and fusion of liposomal laboratory scale, as explained in Section 2. All 10 experiments were vesicles that could occur 1 week after preparation. The coefficients of produced in 2 consecutive days. the equation describing the influence of the factors on nanoGLA particle Table 2 Factors included in the DoE to optimize the intermediate nanoGLA formulation, their potential impact into CQAs and the ranges of investigation. Factor Potential impact into CQAs Factor Range studied in DoE GLA concentration Protein concentration plays a key role on dispersion stability. It From 7 to 27 µg/mL of enzyme. Defined according to the viability of has been reported that increasing the loading and charge of performing the subsequent diafiltration and concentration step up to protein will impact on size distribution and aggregation rate of the 200 µg/mL required for in vivo doses. the liposomal system [23]. Lipid concentration Besides the molar ratio between membrane components From 1.2 to 5.0 mg/mL, moving almost 2 mg/mL up and down of (cholesterol and phospholipid), the total lipid concentration in previously tested concentrations in similar nanoformulations liposomal systems will impact on its mean size, particle (3.0 mg/mL). distribution and stability, as well as on its loading capacity [24–27]. Chol-PEG400-RGD molar PEGylation of liposomes improves not only the stability and From 1% to 3% mol of molar ratio in relation to the total amount of ratio circulation time, but also the passive targeting ability on tumoral lipid components, according to previous studies. tissues, through a process known as the enhanced permeation retention effect, able to improve the therapeutic effects and reduce the toxicity of encapsulated drug [28]. EtOH concentration Solvent concentration could have a direct impact on shape, From 5% to 10% v/v, folding the standard 5% v/v since higher solubility and electrostatic interactions between the liposomal quantities are not recommended for intravenous administration [4]. bilayer and the loaded protein [29]. 6 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Table 3 Matrix of experimental design. The sample codes consider the randomized order of experiments. Experimental run GLA concentration (µg/mL) Lipid concentration (mg/mL) Chol-PEG400-RGD molar ratio to lipids EtOH concentration (% v/v) (% mol) DOE-001 27 1.2 1 10.0 DOE-002 7 1.2 3 10.0 DOE-003 17 3.1 2 7.5 DOE-004 27 5.0 1 5.0 DOE-005 7 5.0 3 5.0 DOE-006 27 1.2 3 5.0 DOE-007 17 3.1 2 7.5 DOE-008 7 1.2 1 5.0 DOE-009 27 5.0 3 10.0 DOE-010 7 5.0 1 10.0 Fig. 3. Representative cryo-TEM images of nanoGLA DoE samples at 1 week after production. Scale bar 200 nm. Table 4 Characterization of intermediate nanoGLA CQAs after 1 week of production. Uncertainties are calculated from the standard deviation of measurement for Size, PdI, ζ-potential, and EE; and from standard error of the mean for uni-lamellarity and EA. Sample ID Size (nm) PdI ζ-potential (mV) TSI Uni-lamellarity, fsingle EE (%) EA (ratio to control) DOE-001a 143 ± 6 0.45 ± 0.08 35 ± 2 11.5 0.88 ± 0.01 60 ± 1 1.7 ± 0.1 DOE-002 88 ± 2 0.17 ± 0.01 36 ± 2 0.6 0.99 ± 0.01 53 ± 1 1.2 ± 0.0 DOE-003 142 ± 3 0.12 ± 0.05 34 ± 0 1.2 0.95 ± 0.00 59 ± 1 1.4 ± 0.0 DOE-004 175 ± 1 0.32 ± 0.05 45 ± 0 8.2 0.93 ± 0.00 45 ± 1 1.6 ± 0.1 DOE-005 158 ± 4 0.24 ± 0.03 45 ± 6 1.9 0.93 ± 0.00 42 ± 1 0.8 ± 0.1 DOE-006a 202 ± 4 0.46 ± 0.05 32 ± 1 6.6 0.85 ± 0.02 68 ± 1 1.5 ± 0.0 DOE-007 146 ± 2 0.11 ± 0.05 35 ± 1 1.2 0.99 ± 0.01 53 ± 1 1.2 ± 0.2 DOE-008 100 ± 1 0.17 ± 0.02 38 ± 1 1.8 1.00 ± 0.01 84 ± 1 0.8 ± 0.0 DOE-009a 172 ± 5 0.22 ± 0.02 38 ± 1 12.0 0.94 ± 0.01 53 ± 1 1.1 ± 0.1 DOE-010 134 ± 2 0.13 ± 0.02 46 ± 2 0.6 0.93 ± 0.00 84 ± 1 1.4 ± 0.1 a DOE-001, DOE-006, and DoE-009 presented sedimentation. size are shown in Fig. 4a (left). According to this figure, the size of increases, MKC surfactant (used as excipient in the nanoformulation) nanoGLA liposomes is significantly influenced by GLA concentration concentration also increases, giving more positive charges to the lipo- (X1) and the lipid concentration (X2). Thus, a significant increase in somal system. The influence of lipid concentration is also illustrated by size is obtained when the concentration of GLA and lipid increase. The the contour plot for size in Fig. 4b (right). increase in size with the increase of GLA and lipid concentrations could Monolayered liposomes fractions varied from 0.88 to 1.00, as shown be explained by the occurrence of physical aggregation of the vesicles. in Table 4 by fsingle values. According to Fig. 4c (left), lipid con- The influence of GLA and lipid concentration is also illustrated by the centration was the only factor affecting this CQA significantly, showing contour plot for size in Fig. 4a (right). a larger difference in comparison to the rest of factors. As can be seen in As shown in Table 4, ζ-potential ranged from 32 to 46 mV for non- Fig. 4c (right), GLA concentration had an insignificant influence on the diafiltrated liposomes. The influence of studied factors on ζ-potential is monolayer ratio of liposomes, but it was strongly affected by the lipid shown as coefficients of the regression equation plot in Fig. 4b (left). concentration. The explanation can be the same as the effect of lipid According to this plot, lipid concentration (X2) was the only factor that concentration on vesicle size: aggregation and fusion of the vesicles had a significant positive effect on the ζ-potential of the dispersions when lipid concentration increases could be responsible of this obtained. This could be explained because when lipid concentration behavior. 7 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Fig. 4. Left side: scaled and centered coefficients of the regression equations describing the influence of formulation parameters X1-GLA concentration, X2-lipid concentration, X3-Chol-PEG400-RGD molar ratio, X4-EtOH concentration, on the liposomes size, ζ-potential, and uni-lamellarity of nanoGLA intermediate dispersion. Right side: contour plots for the same CQAs of the nanoGLA intermediate dispersion. Molar ratio of chol-PEG400-RGD to lipid and EtOH concentration were kept constant at 2% mol and 7.5% v/v, respectively. 3.6. Evaluation of the design space charge provided by this cationic surfactant. Nevertheless, this ζ-potential increase was not correlated with a higher colloidal stability of the nano- Among all the factors studied, GLA concentration and lipid con- formulation as also confirmed by an uni-lamellarity decrease. It seems that centration were found to have a significant influence on some of the this MKC amount is not enough to stabilize such highly concentrated responses. Thus, the Design Space for intermediate nanoGLA was con- samples. However, higher MKC concentrations, although could improve structed using these factors which significantly influenced the quality of the stability of these concentrated samples, it also could entail a the nanoformulation. On the one hand, increase of GLA and lipid toxicological concern as well as the abolishment of the enzymatic activity concentration had a negative influence on liposomal mean particle size of the GLA, as reported by Tomsen-Melero et al. [7]. because of the size increase promoted by aggregation. On the other hand, The other CQAs such as polydispersity index, TSI, GLA entrapment as the lipid concentration increased, and, consequently, the amount of efficiency, and enzymatic activity could not be fitted in any reliable model MKC surfactant was higher, ζ-potential (which is related to the electrical because of the sedimentation of some batches and the high characterization charge at the liposomes surface) also increased due to the formal positive variability, due to the use of SDS-PAGE plus TGX as a reference method for 8 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Fig. 5. The Design Space for intermediate nanoGLA liposomal dispersion that meets the specifications in terms of CQAs, expressed as the probability of failure (%). Molar ratio of chol-PEG400-RGD to lipid and EtOH concentration have been optimized in the run at 1.16% mol and 6.2% v/v, respectively. Table 5 if both factor concentrations are high is due to aggregation effect of The desired CQAs of nanoGLA introduced in the Design Space explorer and liposomes caused by a change of interaction between them, provoked their values. by the high load of components in the membrane [24,31]. Response Criterion Min. Target Max. 3.7. Optimization of the nanoGLA formulation Size (nm) Target 50 150 250 ζ-potential Excluded – – – Uni-lamellarity (fsingle) Maximize 0.95 1.00 – The challenge was to obtain a stable nanoGLA concentrated for- mulation containing 200 μg/mL of GLA, suitable doses for in vivo testing. To do so, a batch of nanoGLA was prepared by DELOS-susp and GLA quantification. Results could be improved in the future using a HPLC diafiltrated and concentrated following the trend of the preliminary method for the quantification of GLA. Hence, the Design Space was de- Design Space: the lipid concentration was reduced to 1.2 mg/mL so that termined using particle size, ζ-potential, and uni-lamellarity. the GLA concentration could be increased up to 35 µg/mL, obtaining an The Design Space obtained is shown as the green region in Fig. 5, intermediate nanoGLA by DELOS-susp meeting all the CQAs. and shows the combination of factors for which the nanoGLA inter- Physicochemical properties are shown in Table 6 and Fig. 6. Particle mediate obtained by DELOS-susp will meet the specifications in terms mean size, polydispersity index, ζ-potential, and GLA concentration – of CQAs, specified in Table 5, with a probability of failure less than 1%. all meet the requirements to go to future in vivo preclinical trials The combination inside the design space which is pointed out by the (<300 nm, ≤0.45, >30 mV, and >200 μg GLA/mL, respectively). A black arrows indicates the robust setpoint (17.7 µg/mL GLA con- good colloidal stability was observed for the concentrated final na- centration, 2.97 mg/mL lipid concentration, 1.3% mol Chol-PEG400- noGLA, composed mainly by single lamellar liposomes (Fig. 6). Some RGD, and 6.2% v/v EtOH) corresponding to the formulation for which structural effects were noticeable by cryo-TEM after over-concentrating the prediction errors are the lowest. the GLA-loaded liposomes. Images revealed the formation of some To our knowledge, there are no similar results reporting the multilamellar complexes, where the GLA can be identified between li- relationship between lipid and protein concentration affecting size, posomal layers as well as inside the vesicles (Fig. 6, arrows), forming ζ-potential, and uni-lamellarity in this way. We could expect that at low structures resembling lipoplexes [32]. Interestingly, the high con- concentration of lipid and GLA, we would also obtain a nanoGLA within centration of GLA (330 µg/mL) after the concentration process where the established acceptance limits, so it could be possible that the red these structures were identified was quite above the minimum required zone showed in Fig. 5 around the lowest concentrations belongs to a value for in vivo trials (200 µg/mL). range that remained unexplored. In addition, the finding of a model In addition, the final prototype dispersion was stable for more than which indicates that formulation will escape from the acceptance limits 2 weeks. Table 6 Critical Quality Attributes for optimized intermediate nanoGLA, diafiltrated and concentrated around 10-fold. Attributes After DELOS-susp (Intermediate nanoGLA) After concentration (Preclinical nanoGLA) Stability NA >2 weeks Particle mean size (nm) 138 ± 7 165 ± 3 Polydispersity Index 0.38 ± 0.03 0.41 ± 0.02 ζ-potential (mV) 40 ± 1 35 ± 1 Enzymatic activity (ratio to control) 1.11 ± 0.08 0.93 ± 0.04 GLA (µg/mL) 34 ± 2 330 ± 20 9 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Fig. 6. Cryo-TEM images of optimized nanoGLA prototype after concentration. The images were acquired 2 weeks after production. 3.8. Safe-by-Design implementation prototype of nanoGLA suitable for in vivo testing could be optimized. The influence of some formulation parameters was determined by using a The implementation of the SbD approach followed the strategy DoE. Thus, among the formulation factors, GLA concentration and lipid reported by [33] and was specifically tailored to complement the QbD concentration were the most important parameters for the quality of work, to prevent hazards from the developed components and processes, nanoGLA obtained by compressed fluid processing. and to support the redesign of technical workflows where the need is This study also enabled the obtaining of a preliminary design space identified. Each individual process step was evaluated to identify possible to produce nanoGLA intermediate dispersion, in which the established exposure scenarios and safety issues. quality requirements of the product are met. For the used DELOS-susp methodology (see Fig. 2), four specific Through the design space analysis, it could be predicted that for issues that pose a potential risk were identified: achieving a higher (10-fold), concentration of enzyme in the final for- mulation the concentration of lipid in the DELOS-susp step could be 1. DMSO/EtOH in the nanoformulation reduced in order to obtain a good quality product in terms of particle 2. Aerosol exposition due to organic compounds, vapors, streams from size and uni-lamellarity, and to avoid aggregation and sedimentation. the organic phase 3. Carbon dioxide poisoning Declaration of Competing Interest 4. Cold burn during lyophilization The authors declare the following financial interests/personal re- All the identified possible risks during the DELOS-susp methodology lationships which may be considered as potential competing interests: are rated on low respectively medium risk level and are controlled J.L-C., D.P., S.Sch., M.R., I.A., J.V., S.Sa. and N.V. are inventors of patent (see Appendix F), thus the DELOS-susp process can be considered as WO/2014/001509 licensed to Biopraxis Resarch AIE. J.V., S.Sa. and safe. To fully cover the entire innovation process towards its final N.V. are inventors of patent WO/2006/079889 owned by Nanomol product application, immunogenicity, endotoxicity, and impurities of Technologies SL, and stock-owners in Nanomol Technologies SL. J.M-M., the nano-formulation will be evaluated at later stage. J.T-M., A.F., E.G-M., J-L.C, E.C-L., D.P., M.R., S.Sch., I.A., A.S., S.Sa., J.V., N.V. and A.C. are inventors of patent application EP21382062.4. 4. Conclusions Acknowledgments The current work brings a new contribution in the preparation of GLA The authors acknowledge the financial support from European loaded liposomes through the successful application of the QbD approach Commission through H2020 program of the Smart-4-Fabry project to DELOS-susp production method. Thanks to this methodology a (ID 720942). 10 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 We acknowledge financial support to our research from Instituto UAB SepBioES scientific-technical service (www.nanbiosis.es/unit/u1- de Salud Carlos III, through “Acciones CIBER”. The Networking proteinproduction-platform-ppp/), the Soft Materials Service linked to Research Center on Bioengineering, Biomaterials, and Nanomedicine Biomaterial Processing and Nanostructuring Unit at ICMAB-CSIC (CIBER-BBN) is 2008–2011, financed by the Instituto de Salud Carlos (www.nanbiosis.es/portfolio/u6-biomaterial-processing-and- III with assistance from the European Regional Development Fund. nanostructuring-unit/) and the Peptide Synthesis unit at the IQAC-CSIC Authors acknowledge financial support from the Agencia Estatal de (www.nanbiosis.es/portfolio/u3-synthesis-of-peptides-unit/). Investigación-Ministerio de Ciencia e Innovación through the N. A-G. is supported by a PERIS grant from the Catalan Government “Severo Ochoa” Programme for Centres of Excellence in R & D (SLT006/17/270). (CEX2019-000917-S). This work was also financed by 1084 the J. T-M. is supported by a FI-AGAUR grant from the Catalan Government Ministerio de Ciencia e Innovación (PID2019-105622RB-1085 I00). and the European Social Fund (ESF-Investing in your future) of the We also thank the denomination of the 1101 consolidated group European Union. This work has been done in the framework of the JT-M. from Generalitat de Catalunya: 2017-1102 SGR-1439 (M.R.) and doctorate in Materials Science of the Universitat Autònoma de Barcelona. 2017-SGR-918 (J.V.). The technical assistance of Inbal Ionita, Ella Kesselman and We also acknowledge the ICTS “NANBIOSIS”, more specifically the Mingming Zhang from Technion - Israel Institute of Technology; and support from the Protein Production Platform of CIBER-BBN/IBB, at the Ramon González from ICMAB-CSIC is acknowledged. Appendix A. Synthesis of GLAcmycHis Plasmids and E. coli strains The GLA gene was obtained from the commercial vector pReceiver-M10 (OmicsLink ORF Expression Clone, ref. EX-Q0172-M10), that encodes a cDNA version of the GLA gene (primary gene accession number: NM_000169), in which both c-myc and 6xHis tags are fused (for further detection and purification purposes) to the C-terminus. For further steps, the pOptiVEC™-TOPO® TA Cloning Kit (Catalog Number 12744-017, Invitrogen, by Life Technologies) was used following the vendor protocol. The PCR product was cloned into the pOptiVEC™-TOPO® plasmid, and the resulting plasmid (pOptiVec-GLA) was transformed into TOP10 E. coli cells. Positive clones were selected by ampicillin and confirmed by restriction analysis. The pOptiVec-GLA plasmid was purified by “gigaprep” method, and finally linearized before transfection, as recommended by the vendor, with restriction enzyme PvuI. All plasmids were purified from their corresponding overnight bacterial cultures, using the EndoFree Plasmid Giga Kit (Qiagen, ref. 12391). For their quantification, absorbances at 260 nm (A260) and 280 nm (A280) were measured. Mammalian cell line, transfection and selection of positive clones For the transfection and further selection of CHO cells overexpressing the human GLA enzyme, the OptiCHO™ Express Kit (Catalog number 12745-014, Invitrogen, by Life Technologies) was used. This kit provides CHO DG44 cells, media and transfection reagent needed. DG44 dhfr- CHO cells were grown in CD DG44 medium with 8 mM L-glutamine, at 37 °C in 8% CO2 using standard techniques. Transfection of CHO DG44 cells and selection of positive GLA-DHFR cells were performed following the vendor protocol. At 28 days post-transfection, stepwise selection for dhfr amplification was started, using two-fold increments of methotrexate hydrate (MTX, Sigma, catalog number A6770) starting at 50 nM up to 4 μM. Finally, and in order to obtain a single clone, the pool of stably transfected and 4 μM MTX-amplified cells were serially diluted and seeded at 1–2 cells per well in a 96-well plate. As suggested by vendor, to grow CHO DG44 cells under adherent conditions, the specific medium Gibco® CD-CHO-A was used. After this process, a single clone (namely CHO-DG44-GLA clone #3) was isolated and cryopreserved. Cryopreservation of CHO-DG44-GLA clone #3 CHO-DG44-GLA clone #3 was cultured in complete CD OptiCHO medium (supplemented with L-Glutamine 8 mM) to 2 × 106 cells per milliliter and then centrifuged at 100 g for 5 min. Cell pellets were then resuspended in fresh medium containing 10% DMSO to a final cell concentration of 10 × 106 cells/mL. Cells were aliquoted into 1 mL cryovials (Nalgene) and stored in the vapor phase of liquid nitrogen. Production and purification of extracellular GLAcmycHis protein Cryovials of CHO-DG44-GLA clone #3 were thawed under standard procedures. Briefly, cryovial was rapidly thawed at 37 °C and resuspended in 15 mL of prewarmed complete CD OptiCHO medium. Cells were expanded by subculturing them up to the desired volume. In each passage, cells were diluted into pre-warmed complete CD DG44 Medium to give a final cell density of 2 × 105 –3 × 105 viable cells/mL. Finally, supernatant containing extracellular GLAcmycHis was harvested by centrifuging the cell culture at 14,000 rpm for 15 min. This su- pernatant was purified in an ÄKTA Pure system (GE Healthcare) by using an affinity chromatography column (HisTrap Excel 5 mL, Ref 17-3712-06, GE Healthcare) following the vendor protocol. Finally, the eluted protein was dialyzed in acetic buffer 0.01 M pH 5.5 and stored at −20 °C until used. 11 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Appendix B. DELOS-susp methodology for the preparation of nanoGLA Table B.1 summarizes the process parameters that were kept constant for all DELOS-susp experiments; and also includes the control strategies since some of them could have an impact on some CQAs. The 10 experiments carried out in this study were produced in 2 consecutive days. Table B.1 DELOS process parameters kept constant in all DoE experimental runs. Process Parameter Value Control Working temperature, Tw 35 °C Heating jacket High pressure stirring 500 rpm Magnetic stirrer controller Working pressure, Pw 9 MPa Syringe pump for CO2 Depressurization pressure in the autoclave 10 MPa Manometer and N2 pressure regulator Collector Stirring 300 rpm Plate with magnetic stirrer CO2 molar fraction, XCO2 0.55 Solvent volume in the reactor Depressurization flowrate 10 g/min Manually controlled due to scale, averaged Collector temperature 23 °C Monitored, room temperature Appendix C. Risk analysis assessment Fig C.1 represents a summary of Critical Material Attributes (CMAs) and Critical Process Parameters (CPPs) that may impact the CQAs of the intermediate nanoGLA using Ishikawa methodology. Components purity Plant factors CO2 Condions Chol-PEG400-RGD Depressurizaon GLA Mixing Intermediate Suspension of nanoGLA Dispersant media Column specs Fig. C.1. Ishikawa diagram illustrating the summary of CPPs and CMAs that may impact on each selected CQA of intermediate nanoGLA dispersion. 12 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 A control strategy is designed to ensure that a product of required quality will be produced consistently. These controls are based on product, formulation and process understanding and should include, at a minimum, control of the critical process parameters and material attributes. The risk assessment and the definition of control strategies serve to evaluate which CMAs and CPPs must be studied in a DoE. In Table C.1 the risk analysis assessment of the potential CMAs and CPPs on the DELOS-susp process is presented. Table C.1 Risk analysis assessment and control strategies of CMAs and CPPs for intermediate nanoGLA production by DELOS-susp. CMA or CPP Impact on Risk Control strategy CQA Components purity Low Change in composition CoA from supplier Raw GLA High Change in morphology, nanoGLA CoA from supplier and check analysis by TGX, BCA or HPLC. stability an activity Chol-PEG400-RGD AA% Low Affect biological activity CoA from supplier and check analysis Chol-PEG400-RGD moisture Low Uni-lamellarity and morphology could CoA from supplier and check analysis be affected. EtOH concentration High To be evaluated in DoE. To be included in DoE. DMSO concentration Medium Stability, enzymatic activity Previously defined. Buffer concentration Medium To be studied in further steps. To be defined in further steps of the project. Membrane components molar High Morphology, stability Previously defined. ratio Lipid concentration High Entrapment efficiency, stability of the To be included in DoE. solution. Chol-PEG400-RGD concentration High Morphology, stability, intracellular To be included in DoE. penetration MKC concentration High Higher concentration, higher stability Previously defined. and Entrapment. GLA concentration High Stability, enzymatic activity To be included in DoE. Mixing configuration High Morphology, stability Previously defined. Operator Low Low control of the flowrate Lab scale: Follow the standard protocol and practice on depressurization. Pilot scale: automatic control of depressurization valve. Stirring of vessel Low Enough to obtain a single phase inside Previously defined, servocontrolled by high pressure stirrer. the high pressure vessel. Pressure of vessel Low Enough to obtain a liquid phase inside Previously defined, servocontrolled by pump and PIC. the high pressure vessel. Temperature of vessel Low Enough to obtain a liquid phase inside Previously defined, controlled by heating jacket and TIC. the high pressure vessel. CO2 molar fraction Low Inside the range of cosolvency. Previously Defined and controlled by volume, P and T of the pump. N2 pressure Low 10 bar higher than pressure of the vessel, Defined and controlled by a pressure regulator and PIC could affect the flowrate. Flowrate High Morphology and uni-lamellarity. To be To be included in DoE. evaluated in DoE. Collector volume Medium Change in flow and mixing between Previously defined. phases. Collector temperature High GLA degradation depends on Previously defined. Controlled by TIC. temperature and exposition time Stirring of the collector Medium Change in flow and mixing between Previously defined. phases. Appendix D. Samples time evolution of mean particle size, PdI, and ζ-potential Fig D.1 shows the analysis in time by DLS of the samples. As the Fig D.1. Evolution shows, the mean size of some samples increased during time, mainly explained by the aggregation of the nanovesicles, showing clearly that DOE-006 and DOE-009 were going to sediment. PdI values, remained constant except for the two samples previously mentioned. ζ-potential maintained mostly constant with time, although the decrease observed in some cases could be explained because of the change in pH during time caused by the release of dissolved CO2. 13 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Fig. D.1. Evolution of a) mean particle size, b) PdI, and c) ζ-potential over time during 14 days after the production of the samples. Appendix E. Modeling and data fitting The acceptance of the responses obtained was evaluated by means of the statistical parameters predicted by the software R2, Q2 model validity, and model reproducibility: (i) R2: it represents the percent of the variation of the response explained by the model, that is, how well the model fits the data; (ii) Q2: it is the percent of the variation of the response predicted by the model according to cross validation. It gives information about how well the model predicts new data. In Table E.1, the values of these statistical parameters are summarized, indicating if the data collected from the experimental results is fitting into a model. Only those CQAs that could be fitted (mean particle size, ζ -potential and uni-lamellarity) were included in the model. Table E.1 Statistical parameters and fitting for the investigated intermediate nanoGLA CQAs. CQA R2 Q2 Fitting and model (if applies) Mean particle size 0.937 0.661 Yes, Size = 2.0 X1 + 10.6 X2 + 11.7 X3 - 2.2 X4 + 86 Polydispersity 0.437 0.200 No, a bad correlation and a poor predictive ability of the model were obtained. ζ-potential 0.791 0.550 Yes, ζ-pot = −19 X1 + 2.1 X2 - 10.9 X3 - 24.5 X4 + 41 TSI 0.636 0.200 No, a bad correlation and a poor predictive ability of the model were obtained. Uni-lamellarity 0.858 0.498 Yes, fsingle = 3.3·10−4 X1 - 1.8·10−2 X2 - 1.1·10−7 X3 - 5.7·10−9 X4 + 1.0 Entrapment efficiency 0.420 0.200 No, a bad correlation and a poor predictive ability of the model were obtained. Enzymatic activity 0.625 0.040 No, it could be explained by the high measurement related variability Appendix F. Identified safety issues Occupational exposure scenarios as well as environmental exposure scenarios were registered, considering different operational conditions. Table F.1 shows the obtained risk rating key for the specific activity and/or process in the DELOS-susp methodology for the preparation of the nanoGLA intermediate, and lists relevant methods to manage the possible risk and decrease its possibility to take place. 14 J. Merlo-Mas, J. Tomsen-Melero, J.-L. Corchero et al. The Journal of Supercritical Fluids 173 (2021) 105204 Table F.1 Identified safety issues in relation to their severity and likelihood leads to risk rating key. Activity/Process Associated Risk(s): Severity: Likelihood: Method(s) to Manage the Risk: Safety issue(s) associated Level of The chances of A list of methods you will use to minimize the chances of with the activity impact that risk the risk happening happening Preparation of the organic solution EtOH/DMSO in the Acceptable Low Related to the environment: Solvents to the non- nanoformulation Acceptable Low chlorinated solvents waste container. Cholesterol, Chol- Weighing solids and preparation of a Dermal/occu pational safety PEGn-RGD, MKC, and DPPC to the solid chemical waste solution issues during cleaning container. Cleaning the laboratory material Related to workers: Fume hood. Mask, gloves, glasses and lab coat. Loading of the vessel, closing and Dermal/occupational safety Acceptable Low Related to workers: Fume hood. Mask, gloves, glasses, and pressurization by adding CO2 issues during loading the lab coat. Vent and safety valves present in the equipment vessel in case of overpressure Preparation of aqueous solution Dermal safety issues during Acceptable Low Related to workers: Fume hood. Mask, gloves, glasses, and cleaning of the material lab coat. Depressurization and mixing of the Carbon dioxide poisoning Tolerable Low Related to workers: Fume hood. Mask, gloves, glasses and organic and aqueous phases during valve opening lab coat. Vent and safety valves. Filters for carbon dioxide exhaust expelled to the environment have to be considered in larger scales. Collecting the final product and storage Cold Burn during Acceptable Low Fume hood. Mask, gloves, glasses and lab coat. lyophilization References [17] R. Hosemann, S.N. Bagchi, The interference theory of ideal paracrystals, Acta Cryst. 5 (1952) 612–614. [18] M.I. Giannotti, I. Abasolo, M. Oliva, F. Andrade, N. García-Aranda, M. Melgarejo, [1] N. Ventosa, J. Veciana, S. Sala, M. Cano, Patent Application EP 1843836, 2012. D. Pulido, J.L. Corchero, Y. Fernández, A. Villaverde, M. Royo, M.F. García-Parajo, [2] I. Cabrera, E. Elizondo, O. Esteban, J.L. Corchero, M. Melgarejo, D. Pulido, F. Sanz, S. Schwartz, Highly versatile polyelectrolyte complexes for improving the A. Córdoba, E. Moreno, U. Unzueta, E. Vazquez, I. Abasolo, S. Schwartz, enzyme replacement therapy of lysosomal storage disorders, ACS Appl. Mater. A. Villaverde, F. Albericio, M. Royo, M.F. García-Parajo, N. Ventosa, J. Veciana, Interfaces 8 (2016) 25741–25752, https://doi.org/10.1021/acsami.6b08356 Multifunctional nanovesicle-bioactive conjugates prepared by a one-step scalable [19] M. Kapoor, S.L. Lee, K.M. Tyner, Liposomal drug product development and quality: method using CO2-expanded solvents, Nano Lett. 13 (2013) 3766–3774, https:// current US experience and perspective, AAPS J. 19 (2017) 632–641, https://doi. doi.org/10.1021/nl4017072 org/10.1208/s12248-017-0049-9 [3] N. Grimaldi, F. Andrade, N. Segovia, L. Ferrer-Tasies, S. Sala, J. Veciana, [20] FDA, Liposome Drug Products Chemistry, Manufacturing, and Controls; Human N. Ventosa, Lipid-based nanovesicles for nanomedicine, Chem. Soc. Rev. 45 (2016) Pharmacokinetics and Bioavailability; and Labeling Documentation, 2018. 6520–6545, https://doi.org/10.1039/c6cs00409a [21] European Medicine Agency, Reflection Paper on the Data Requirements for [4] I. Cabrera, I. Abasolo, J.L. Corchero, E. Elizondo, P.R. Gil, E. Moreno, J. Faraudo, Intravenous Liposomal Products Developed with Reference to an Innovator S. Sala, D. Bueno, E. González-Mira, M. Rivas, M. Melgarejo, D. Pulido, F. Albericio, Liposomal Product, EMA/Committee Hum. Med. Prod., 2013, pp. 1–13 806058/ M. Royo, A. Villaverde, M.F. García-Parajo, S. Schwartz, N. Ventosa, J. Veciana, α- 2009/Rev. 02. 44. Galactosidase-A loaded-nanoliposomes with enhanced enzymatic activity and in- [22] X. Xu, M.A. Khan, D.J. Burgess, A quality by design (QbD) case study on liposomes tracellular penetration, Adv. Healthc. Mater. 5 (2016) 829–840, https://doi.org/10. containing hydrophilic API: II. Screening of critical variables, and establishment of 1002/adhm.201500746 design space at laboratory scale, Int. J. Pharm. 423 (2012) 543–553, https://doi. [5] S. Alipourfetrati, A. Saeed, J.M. Norris, A review of current and future treatment org/10.1016/j.ijpharm.2011.11.036 strategies for fabry disease: a model for treating lysosomal storage diseases, J. [23] I.C. Pintre, S.J. Webb, Binding and Reactivity at Bilayer Membranes, 1st ed., Pharmacol. Clin. Toxicol. 3 (2015). Elsevier Ltd, 2013, https://doi.org/10.1016/B978-0-12-407754-6.00003-X [6] M. Solomon, S. Muro, Lysosomal enzyme replacement therapies: historical devel- [24] S. Shaker, A. Gardouh, M. Ghorab, Factors affecting liposomes particle size pre- opment, clinical outcomes, and future perspectives, Adv. Drug Deliv. Rev. 118 pared by ethanol injection method, Res. Pharm. Sci. 12 (2017) 346–352, https:// (2017) 109–134, https://doi.org/10.1016/j.addr.2017.05.004 doi.org/10.4103/1735-5362.213979 [7] J. Tomsen-Melero, S. Passemard, N. García-Aranda, Z.V. Díaz-Riascos, R. González- [25] G. Pamunuwa, V. Karunaratne, D.N. Karunaratne, Effect of lipid composition on in Rioja, J.N. Pedersen, J. Lyngsø, J. Merlo-Mas, E. Cristóbal-Lecina, J.L. Corchero, vitro release and skin deposition of curcumin encapsulated liposomes, J. D. Pulido, I. Portnaya, E. Crist, L. Corchero, D. Pulido, P. Cámara-Sánchez, Nanomater. 2016 (2016) 1–9, https://doi.org/10.1155/2016/4535790 I. Portnaya, I. Ionita, S. Schwartz, J. Veciana, S. Sala, M. Royo, A. Córdoba, [26] N.S. Awad, V. Paul, M.S. Mahmoud, N.M. Al Sawaftah, P.S. Kawak, M.H. Al Sayah, D. Danino, J.S. Pedersen, E. González-Mira, I. Abasolo, N. Ventosa, Impact of G.A. Husseini, Effect of pegylation and targeting moieties on the ultrasound- chemical composition on the nanostructure and biological activity of α-galactosi- mediated drug release from liposomes, ACS Biomater. Sci. Eng. 6 (2019) 48–57, dase-loaded nanovesicles for fabry disease treatment!impact of chemical composi- https://doi.org/10.1021/acsbiomaterials.8b01301 tion on the nanostructure and biological activity of galactosidaseloaded nanove- [27] M.L. Briuglia, C. Rotella, A. McFarlane, D.A. Lamprou, Influence of cholesterol on sicles for fabry disease treatment, ACS Appl. Mater. Interfaces 13 (7) (2021) liposome stability and on in vitro drug release, Drug Deliv. Transl. Res. 5 (2015) 7825–7838, https://doi.org/10.1021/acsami.0c16871 231–242, https://doi.org/10.1007/s13346-015-0220-8 [8] International Council of Harmonisation, Q8 - Pharmaceutical Development, 2009. [28] P. Milla, F. Dosio, L. Cattel, PEGylation of proteins and liposomes: a powerful and [9] International Council of Harmonisation, Q9 - Quality Risk Management, 2005. flexible strategy to improve the drug delivery, Curr. Drug Metab. 13 (2011) [10] International Council of Harmonisation, Q10 - Pharmaceutical Quality System, 2008. 105–119, https://doi.org/10.2174/138920012798356934 [11] A. Porfire, D.M. Muntean, L. Rus, B. Sylvester, I. Tomuţă, A quality by design ap- [29] S. Guner, M.H. Oztop, Food grade liposome systems: effect of solvent, homo- proach for the development of lyophilized liposomes with simvastatin, Saudi genization types and storage conditions on oxidative and physical stability, Colloids Pharm. J. 25 (2017) 981–992, https://doi.org/10.1016/j.jsps.2017.01.007 Surf. A Physicochem. Eng. Asp. 513 (2017) 468–478, https://doi.org/10.1016/j. [12] I. van de Poel, Z. Robaey, Safe-by-design: from safety to responsibility, Nanoethics colsurfa.2016.11.022 11 (2017) 297–306, https://doi.org/10.1007/s11569-017-0301-x [30] D. Carugo, E. Bottaro, J. Owen, E. Stride, C. Nastruzzi, Liposome production by [13] R. Purohit, A. Mittal, S. Dalela, V. Warudkar, K. Purohit, S. Purohit, Social, en- microfluidics: potential and limiting factors, Sci. Rep. 6 (2016) 1–15, https://doi. vironmental and ethical impacts of nanotechnology, Mater. Today Proc. 4 (2017) org/10.1038/srep25876 5461–5467, https://doi.org/10.1016/j.matpr.2017.05.058 [31] X. Xu, A. Costa, D.J. Burgess, Protein encapsulation in unilamellar liposomes: High [14] E. Cristóbal-Lecina, D. Pulido, P. Martin-Malpartida, M.J. Macias, F. Albericio, encapsulation efficiency and a novel technique to assess lipid-protein interaction, M. Royo, Synthesis of stable cholesteryl-polyethylene glycol-peptide conjugates Pharm. Res. 29 (2012) 1919–1931, https://doi.org/10.1007/s11095-012-0720-x with non-disperse polyethylene glycol lengths, ACS Omega 5 (2020) 5508–5519, [32] N. Dan, D. Danino, Structure and kinetics of lipid-nucleic acid complexes, Adv. https://doi.org/10.1021/acsomega.0c00130 Colloid Interface Sci. 205 (2014) 230–239, https://doi.org/10.1016/j.cis.2014.01. [15] D. Danino, Cryo-TEM of soft molecular assemblies, Curr. Opin. Colloid Interface Sci. 013 17 (2012) 316–329, https://doi.org/10.1016/j.cocis.2012.10.003 [33] C. Schimpel, S. Resch, G. Flament, D. Carlander, C. Vaquero, I. Bustero, A. Falk, A [16] G. Pabst, M. Rappolt, H. Amenitsch, P. Laggner, Structural information from mul- methodology on how to create a real-life relevant risk profile for a given nano- tilamellar liposomes at full hydration: full q-range fitting with high quality X-ray material, J. Chem. Heal. Saf. 25 (2018) 12–23, https://doi.org/10.1016/j.jchas. data, Phys. Rev. E - Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 62 (2000) 2017.06.002 4000–4009, https://doi.org/10.1103/PhysRevE.62.4000 15