1. Operating the machine
<ol>
	<li>Starting up the machine and software 
	NOTE: Supplemental Figure S1A-D describes the steps for starting up the machine and software.
	<ol>
		<li>Switch on the instrument at least 30 min before starting the measurements, and then start the PC.</li>
		<li>Double-click on the instrument software icon to start the program.</li>
		<li>Enter the username and password in the login window. Ensure that each user has their own account.</li>
		<li>Wait for all three black bars at the bottom right corner to light up green, indicating that the unit is ready for operation.</li>
		<li>In the case of long periods of inactivity, when the user is automatically logged out, under Security, click on Login, and re-enter the password.</li>
	</ol>
	</li>
	<li>Creating a measurement file 
	NOTE: A new measurement file is created at the beginning of each measurement day. All the measurements are listed and stored in the measurement file. For details of this procedure, see Supplemental Figure S2A-B.
	<ol>
		<li>Create a new measurement file by clicking on File | New | Measurement File. In the opened window, select the storage location, and name the measurement file. Confirm the details by clicking on Save.</li>
		<li>To open a file, click on File | Open | Measurement File. Select the measurement file in the opened window, confirm the details by clicking on Open, select the file name, and click on Save.</li>
	</ol>
	</li>
	<li>Printing the results
	<ol>
		<li>Print or save the results of the system suitability test (SST) (see step 1.5) and the mean value of the sample measurement according to Supplemental Figure S3.</li>
		<li>Mark the measurement(s) in the Records View of the Measurement File.</li>
		<li>Right-click on Batch Print, and wait for another small window to open.</li>
		<li>Select the PSD Intensity report from the choices, and confirm it by clicking on OK.</li>
	</ol>
	</li>
	<li>General procedure to start a measurement 
	NOTE: The procedure for starting a measurement is described in Supplemental Figure S4A-D. Follow the path outlined below for the required unit parameter file (referred to as SOP):
	<ol>
		<li>Select the required SOP from the dropdown list. Since the most recently used SOPs are displayed in the list, if an older SOP is needed, select Browse for SOP, and confirm by clicking on the green arrow. Once the storage location of the SOPs opens, proceed with step 1.4.2. 
		NOTE: For details of the important system parameters specific for iron sucrose (e.g., equilibration time of an attenuator), see Table 1.</li>
		<li>In the opened window, make the required entries under Sample Name and Notes. Confirm by clicking on OK, and wait for the measurement window to open automatically.</li>
		<li>Start the measurement by clicking on the green Start button.</li>
		<li>Once an acoustic signal sounds at the end of the measurement, close the measurement window.</li>
	</ol>
	</li>
	<li>System suitability test (SST) measurement 
	NOTE: Do not touch the lower part of the cuvette (measuring zone). At the beginning and at the end of the sequence, measure the 20 nm particle standard.
	<ol>
		<li>Fill ~1 mL of the undiluted particle standard into a polystyrene cuvette, and close with the lid. 
		NOTE: The diluted standard prepared in step 1.5.1 can be used for 1 month.</li>
		<li>After filling, close the cuvette, and check for air bubbles. Remove air bubbles by tapping the cuvette lightly.</li>
		<li>Place the cuvette in the cell holder of the instrument with the arrow mark facing forward, and close the measuring chamber cover.</li>
		<li>Load the unit parameter SOP, and enter the following data in the start window: 
		Sample Name: SST 20 nm Particle Standard 
		&#8203;Then, add a note: Identifier number and expiry date of the standard</li>
		<li>Start the measurement.</li>
		<li>After the end of the measurement when the acoustic signal sounds, close the measurement window.</li>
		<li>Print the report (see point 1.1.3). 
		NOTE: The SST is passed if the particle size Z-average corresponds to the value of the certificate of analysis &#177; 10%.</li>
	</ol>
	</li>
	<li>Measurement of the iron sucrose solution
	<ol>
		<li>Pipette 0.5 mL of an IS solution with an iron content of 2% m/V into a 25 mL volumetric flask, and fill up to the mark with low-particle water (e.g. freshly deionized and filtered [pore size 0.2 &#181;m]); this solution contains 0.4 mg Fe/mL. 
		NOTE: The sample preparation in step 1.6.1. with this specific dilution was established during method development, and this was determined as the optimal dilution for this purpose.</li>
		<li>For preliminary cleaning, fill the polystyrene cuvette approximately 3/4 full with the prepared measuring solution, swirl gently, and then empty as completely as possible. 
		NOTE: Do not touch the lower part of the cuvette (measuring zone), and avoid air bubbles by not shaking the cuvette.</li>
		<li>For the measurement, pipette 1 mL of the measuring solution into the cuvette, and put on a lid.</li>
		<li>Check the measuring solution in the cuvette for air bubbles. If there are air bubbles, remove them by lightly tapping the cuvette.</li>
	</ol>
	</li>
	<li>Performing the measurement
	<ol>
		<li>Place the plastic cuvette with the measuring solution in the device with the arrow mark facing forward, and close the lid.</li>
		<li>Load the parameter SOP (see step 1.4.1), and enter the following data in the start window: 
		&#8203;Sample Name: Batch number</li>
		<li>Start the measurement.</li>
		<li>After the end of the measurement, when the acoustic signal sounds, close the measurement window.</li>
		<li>Calculate the mean value of the six individual measurements according to Supplemental Figure S5. Mark the individual measurements in the Records View of the Measurement File, right-click on Create Average Result, add the name of the mean value under Sample Name, and confirm by clicking on OK.</li>
		<li>Wait for the software to create a new record at the end of the list, and look for the name entered and the averaged result in that record.</li>
		<li>Print the report (see step 1.1.3).</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Auerbach, M., Gafter-Gvili, A., Macdougall, I. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Intravenous+iron:+A+framework+for+changing+the+management+of+iron+deficiency.">Intravenous iron: A framework for changing the management of iron deficiency.</a> Lancet Haematology. 7 (4), e342-e350 (2020).</li><li>Generic drugs: FDA should make public its plans to issue and revise guidance on nonbiological complex drugs. US Government Accountability Office Available from: <a target="_blank" href="https://www.gao.gov/products/gao-18-80">https://www.gao.gov/products/gao-18-80</a> (2017)</li><li>Klein, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+EU+regulatory+landscape+of+non-biological+complex+drugs+(NBCDs)+follow-on+products:+Observations+and+recommendations.">The EU regulatory landscape of non-biological complex drugs (NBCDs) follow-on products: Observations and recommendations.</a> European Journal of Pharmaceutical Sciences. 133, 228-235 (2019).</li><li>Astier, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+to+select+a+nanosimilar.">How to select a nanosimilar.</a> Annals of the New York Academy of Sciences. 1407 (1), 50-62 (2017).</li><li>Rottembourg, J., Kadri, A., Leonard, E., Dansaert, A., Lafuma, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Do+two+intravenous+iron+sucrose+preparations+have+the+same+efficacy.">Do two intravenous iron sucrose preparations have the same efficacy.</a> Nephrology Dialysis Transplantation. 26 (10), 3262-3267 (2011).</li><li>Aguera, M. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficiency+of+original+versus+generic+intravenous+iron+formulations+in+patients+on+haemodialysis.">Efficiency of original versus generic intravenous iron formulations in patients on haemodialysis.</a> PLoS One. 10 (8), e0135967 (2015).</li><li>Alphandery, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Iron+oxide+nanoparticles+for+therapeutic+applications.">Iron oxide nanoparticles for therapeutic applications.</a> Drug Discovery Today. 25 (1), 141-149 (2020).</li><li>Arami, H., Khandhar, A., Liggitt, D., Krishnan, K. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vivo+delivery,+pharmacokinetics,+biodistribution+and+toxicity+of+iron+oxide+nanoparticles.">In vivo delivery, pharmacokinetics, biodistribution and toxicity of iron oxide nanoparticles.</a> Chemical Society Reviews. 44 (23), 8576-8607 (2015).</li><li>Nikravesh, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Factors+influencing+safety+and+efficacy+of+intravenous+iron-carbohydrate+nanomedicines:+From+production+to+clinical+practice.">Factors influencing safety and efficacy of intravenous iron-carbohydrate nanomedicines: From production to clinical practice.</a> Nanomedicine. 26, 102178 (2020).</li><li>Pai, A. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+and+in+vivo+DFO-chelatable+labile+iron+release+profiles+among+commercially+available+intravenous+iron+nanoparticle+formulations.">In vitro and in vivo DFO-chelatable labile iron release profiles among commercially available intravenous iron nanoparticle formulations.</a> Regulatory Toxicology and Pharmacology. 97, 17-23 (2018).</li><li>Brandis, J. E. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+the+physicochemical+properties+of+the+iron+nanoparticle+drug+products:+Brand+and+generic+sodium+ferric+gluconate.">Evaluation of the physicochemical properties of the iron nanoparticle drug products: Brand and generic sodium ferric gluconate.</a> Molecular Pharmaceutics. 18 (4), 1544-1557 (2021).</li><li>Di Francesco, T., Sublet, E., Borchard, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Nanomedicines+in+clinical+practice:+Are+colloidal+iron+sucrose+ready-to-use+intravenous+solutions+interchangeable.">Nanomedicines in clinical practice: Are colloidal iron sucrose ready-to-use intravenous solutions interchangeable.</a> European Journal of Pharmaceutical Sciences. 131, 69-74 (2019).</li><li>Di Francesco, T., Borchard, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+robust+and+easily+reproducible+protocol+for+the+determination+of+size+and+size+distribution+of+iron+sucrose+using+dynamic+light+scattering.">A robust and easily reproducible protocol for the determination of size and size distribution of iron sucrose using dynamic light scattering.</a> Journal of Pharmaceutical and Biomedical Analysis. 152, 89-93 (2018).</li><li>The Center for Research on Complex Generics. US Food and Drug Administration Available from: <a target="_blank" href="https://www.fda.gov/drugs/guidance-compliance-regulatory-information/center-research-complex-generics">https://www.fda.gov/drugs/guidance-compliance-regulatory-information/center-research-complex-generics</a> (2021)</li><li>Drug products, including biological products, that contain nanomaterials - Guidance for industry. Center for Drug Evaluation and Research. FDA-2017-D-0759. US Food and Drug Administration Available from: <a target="_blank" href="https://www.fda.gov/regulatory-information/search-fda-guidance-documents/drug-products-including-biological-products-contain-nanomaterials-guidance-industry">https://www.fda.gov/regulatory-information/search-fda-guidance-documents/drug-products-including-biological-products-contain-nanomaterials-guidance-industry</a> (2022)</li><li>US Food and Drug Administration. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Draft+guidance+on+ferric+oxyhydroxide.">Draft guidance on ferric oxyhydroxide.</a> US Food and Drug Administration. , (2021).</li><li>Zou, P., Tyner, K., Raw, A., Lee, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physicochemical+characterization+of+iron+carbohydrate+colloid+drug+products.">Physicochemical characterization of iron carbohydrate colloid drug products.</a> The AAPS Journal. 19 (5), 1359-1376 (2017).</li><li>D'Mello, S. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+evolving+landscape+of+drug+products+containing+nanomaterials+in+the+United+States.">The evolving landscape of drug products containing nanomaterials in the United States.</a> Nature Nanotechnology. 12 (6), 523-529 (2017).</li><li>Q2 (R1) Validation of analytical procedures: Text and methodology guidance for industry. FDA-2017-D-6821. US Food and Drug Administration Available from: <a target="_blank" href="https://www.fda.gov/regulatory-information/search-fda-guidance-documents/q2r1-validation-analytical-procedures-text-and-methodology-guidance-industry">https://www.fda.gov/regulatory-information/search-fda-guidance-documents/q2r1-validation-analytical-procedures-text-and-methodology-guidance-industry</a> (2005)</li><li>Reflection paper on the data requirements for intravenous iron-based nano-colloidal products developed with reference to an innovator medicinal product. European Medicines Agency Available from: <a target="_blank" href="https://www.ema.europe.eu/en/documents/scientific-guideline/reflection-paper-data-requirements-intravenous-iron-based-nano-colloidal-products-developed_en.pdf">https://www.ema.europe.eu/en/documents/scientific-guideline/reflection-paper-data-requirements-intravenous-iron-based-nano-colloidal-products-developed_en.pdf</a> (2015)</li><li>Fischer, K., Schmidt, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pitfalls+and+novel+applications+of+particle+sizing+by+dynamic+light+scattering.">Pitfalls and novel applications of particle sizing by dynamic light scattering.</a> Biomaterials. 98, 79-91 (2016).</li><li>Caputo, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Asymmetric-flow+field-flow+fractionation+for+measuring+particle+size,+drug+loading+and+(in)stability+of+nanopharmaceuticals.+The+joint+view+of+European+Union+Nanomedicine+Characterization+Laboratory+and+National+Cancer+Institute+-+Nanotechnology+Characterization+Laboratory.">Asymmetric-flow field-flow fractionation for measuring particle size, drug loading and (in)stability of nanopharmaceuticals. The joint view of European Union Nanomedicine Characterization Laboratory and National Cancer Institute - Nanotechnology Characterization Laboratory.</a> Journal of Chromatography A. 1635, 461767 (2021).</li><li>Yusa, S., Narain, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+6+-+Polymer+characterization.">Chapter 6 - Polymer characterization.</a> Polymer Science and Nanotechnology. , 105-124 (2020).</li></ol>

M.B., E.P., M.W., and A.B. are employees of Vifor Pharma. G.B. is a consultant for Vifor Pharma.

DLS has become a fundamental assay for the determination of the size and size distribution of nanoparticles for applications in drug development and regulatory evaluation. Despite advances in DLS techniques, methodologic challenges still exist regarding the diluent selection and sample preparation, which are especially relevant for iron-carbohydrate complexes in colloidal solutions. Importantly, DLS methods for iron-carbohydrate nanomedicines have not yet been studied extensively in the biological milieu (e.g., the plasma)22. Therefore, there still remains a critical need for the harmonization of best-practice protocols depending on the diluent selection. The selection of the diluent is important, as using purified water versus isotonic saline solutions may affect the colloidal suspension&#39;s stability16.
It should also be noted that iron-carbohydrate complexes should not be diluted below the prescribing information recommendations in an effort to mitigate the challenges of having a dark, opaque solution. Excessive dilutions are not biorelevant and can affect the colloidal suspension&#39;s stability via changes in ionic shielding, which can lead to potential precipitation and inaccurate result reporting. Various dilutions and diluents (unpublished data) were tested during the development of this method, and the sample preparation described in step 1.6.1 of the protocol was determined and validated as the optimal dilution for IS. Several modifications must be considered for the DLS analysis of iron-carbohydrate complexes. For example, the preparation of test solutions needs to be performed in the absence of any kind of high-speed agitation. The use of vortex mixers should be avoided, as this induces the creation of iron-sucrose aggregates. For the preparation of test solutions, IS solutions are gently mixed in water with an automatic pipette. Additionally, when running the samples for DLS analysis, the automatic calibration feature should be turned off.
There are several inherent limitations of DLS analysis for iron-carbohydrate nanoparticles. Due to the nature of the light scattering angles and the Z-average output, the hydrodynamic diameters reported are biased toward larger particles in the measuring solution. Thus, the particle size may be overestimated, and the true distribution of the particle size may be underestimated13. Reporting result techniques should be considered in the context of how large the iron-carbohydrate complex particles are and the potential for aggregation under the experimental conditions. It should also be taken into account that the results of the intensity-, volume-, and number-weighted size distributions may differ greatly between different DLS units from the same or different manufacturers, as different manufacturers use different algorithms for the calculation. Therefore, ISO22412 only recommends the use of the Z-average and polydispersity, as the algorithm for their calculation is standardized. Regulatory agencies have also recommended Z-average size reporting16. It should also be noted that minor modifications will be required (e.g., the handling of the software, measuring procedure, and data preparation) when this protocol is applied to other instruments.
Even in light of the challenges associated with DLS, this technique represents a significant advancement on previous analytic methodologies and adds compelling data to the characterization of iron-carbohydrate complexes. It has been endorsed by scientist collaboratives and regulatory agencies16,18,19,21. Future efforts in applying DLS analysis to iron-carbohydrate complexes should most importantly focus on the global harmonization of protocols for their application to drug development and regulatory evaluation, including ensuring bioequivalence. Overall, the analytical protocol here described aims to standardize the methodology for the measurement of the particle size and distribution of IS and can be a useful tool for the evaluation of the quality&#160;of IS.

Iron sucrose (IS) is a colloidal solution comprised of nanoparticles consisting of a complex of a polynuclear iron-oxyhydroxide core and sucrose. IS is widely employed to treat iron deficiency among patients with a wide variety of underlying disease states who do not tolerate oral iron supplementation or for whom oral iron is not effective1. IS belongs to the drug class of complex drugs as defined by the Food and Drug Administration (FDA), which is a class of drugs with complex chemistry commensurate with biologicals2. The regulatory evaluation of complex drug products may require additional orthogonal physicochemical methods and/or preclinical or clinical studies to accurately compare follow-on complex drugs3,4. This is important because several studies have reported that the use of IS versus a follow-on IS product does not produce the same clinical outcomes. This underscores the criticality of the use of novel and orthogonal characterization techniques that are suitable for detecting differences in the physicochemical properties between IS products5,6. 
The accurate elucidation of the size and size distribution of IS is of clinical importance, as particle size is a major influential factor in the rate and extent of opsonization-the first critical step in the biodistribution of these complex drugs7,8. Even slight variations in the particle size and particle size distribution have been related to changes in the pharmacokinetic profile of iron-oxide nanoparticle complexes9,10. A recent study by Brandis et al. showed that particle size measured by DLS was significantly different (14.9 nm &plusmn; 0.1 nm vs. 10.1 nm &plusmn; 0.1 nm, p &lt; 0.001) when comparing a reference listed drug and a generic sodium ferric gluconate product, respectively11. The consistent batch-to-batch quality, safety, and efficacy of iron-carbohydrate products are entirely dependent on the manufacturing process scale-up, and potential manufacturing drift must be carefully considered9. The manufacturing process may result in residual sucrose, and this will vary based on the manufacturer12. Any modifications in the manufacturing process variables can lead to significant changes in the final complex drug product with regard to the structure, complex stability, and in vivo disposition9. 
To assess drug consistency and predict the drug's in vivo behavior, contemporary orthogonal analytical methodologies are required to determine the physicochemical properties of complex nanomedicines. However, there is a lack of standardization of methodologies, which can result in a high degree of interlaboratory variation in result reporting13. Despite the recognition of these challenges by global regulatory authorities and the scientific community14, most of the physicochemical characteristics of IS remain poorly defined, and the full complement of critical quality attributes in the context of available regulatory guidance documents have not been defined15. The draft product-specific guidance documents issued by the FDA for iron-carbohydrate complexes suggest DLS as a procedure to evaluate the size and size distribution of follow-on products16,17.
Several publications have detailed established DLS protocols to determine IS nanoparticle dimensions13,18. However, because the sample preparation, procedure conditions, instrumentation, and instrumentation setting parameters are different among the published methods, the DLS results cannot be directly compared in the absence of a standardized method to interpret the results13,18. The diversity in methodologies and data-reporting approaches limit the appropriate evaluation of these characteristics for comparative purposes19. Importantly, many of the DLS protocols previously published to evaluate IS do not account for the effect of the diffusion of sucrose in the suspension due to the presence of free sucrose, which has been shown to spuriously elevate the Z-average-calculated hydrodynamic radii of the nanoparticles in colloidal solutions13,18. The present protocol aims to standardize the methodology for the measurement of the particle size and distribution of IS. The method has been developed and validated for this purpose.

<table><tbody><tr><td>&lt;strong&gt;Equipment&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Zetasizer Nano ZS</td><td>Malvern</td><td>NA</td><td>equipped with Zetasizer software 7.12, Helium Neon laser (633 nm, max. 4 mW) and 173&amp;deg; backscattering geometry</td></tr><tr><td>&lt;strong&gt;Materials&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Disposable plastic cuvettes&amp;nbsp;</td><td></td><td></td><td></td></tr><tr><td>LLG-Disposable plastic cells</td><td>LLG labware</td><td>LLG-K&amp;uuml;vetten, Makro, PS; Order number 9.406011</td><td></td></tr><tr><td>low-particle water</td><td></td><td></td><td>&amp;nbsp;(The use of freshly deionized and filtered (pore size 0.2 &amp;mu;m) water is recommended).</td></tr><tr><td>Microlitre pipette</td><td></td><td></td><td></td></tr><tr><td>Venofer 100 mg/5 mL</td><td>Vifor Pharma</td><td></td><td></td></tr><tr><td>Volumetric flask 25 mL</td><td></td><td></td><td></td></tr><tr><td>Nanosphere</td><td>Thermo</td><td>3020A</td><td>Particle Standard</td></tr><tr><td>&lt;strong&gt;Software&lt;/strong&gt;</td><td></td><td></td><td></td></tr><tr><td>Origin Pro v.8.5&amp;nbsp;</td><td>Origin Lab Corporation</td><td></td><td></td></tr></tbody></table>

dynamic light scattering analysis for the determination of the particle size of iron-carbohydrate complexes

Intravenously administered iron-carbohydrate nanoparticle complexes are widely used to treat iron deficiency. This class includes several structurally heterogeneous nanoparticle complexes, which exhibit varying sensitivity to the conditions required for the methodologies available to physicochemically characterize these agents. Currently, the critical quality attributes of iron-carbohydrate complexes have not been fully established. Dynamic light scattering (DLS) has emerged as a fundamental method to determine intact particle size and distribution. However, challenges still remain regarding the standardization of methodologies across laboratories, specific modifications required for individual iron-carbohydrate products, and how the size distribution can be best described. Importantly, the diluent and serial dilutions used must be standardized. The wide variance in approaches for sample preparation and data reporting limit the use of DLS for the comparison of iron-carbohydrate agents. Herein, we detail a robust and easily reproducible protocol to measure the size and size distribution of the iron-carbohydrate complex, iron sucrose, using the Z-average and polydispersity index.

The method described was validated according to ICH Q2(R1)20, which involved the measurement of test solutions under varying conditions. The precision was only 0.5% RSD for the Z-average size, while a maximum of 3.5% RSD was calculated for the PDI. The mean results from different analysts and days only differed by 0.4% for the Z-average size and 1.5% for the PDI. Statistics were calculated from 12 measurements performed by two analysts on varying days. Neither changes in the test concentration in the range of 50%-200% nor the storage of the test solutions for up to 5 days in refrigerated conditions had an impact on the final result.
Analyzed parameters 
Z-average size 
The hydrodynamic diameter is given as the Z-average particle size, and the method for determining this is defined in ISO 22412:201717. The Z-average size is a parameter also known as the cumulant mean. The Z-average is the preferred DLS size parameter, as the calculation of the Z-average is mathematically stable, and the Z-average result is insensitive to noise. According to the EMA and FDA, the Z-average size together with the PDI are the recommended values for the characterization of nanomedicines15,16,21. The Z-average particle size is only comparable with the size measured by other techniques if the sample is monomodal, spherical, or near-spherical in shape, is monodisperse, and is prepared in a suitable dispersant. This is because the Z-average mean particle size is sensitive to even small changes in the sample preparation. The Z-average particle size is a hydrodynamic parameter and is, therefore, only valid for particles in a dispersion or for molecules in solution.
Polydispersity index 
This index is a number calculated from a simple two-parameter fit to the correlation data (the cumulant analysis). The polydispersity Index is dimensionless and scaled such that values smaller than 0.05 are rarely seen, except for in highly monodisperse standards. Values greater than 0.7 indicate that the sample has a very broad particle size distribution and is likely not suitable for the DLS technique. Various size distribution algorithms can function with data that fall between these two extremes. The calculations for these parameters are defined in the ISO standard document 22412:201717.
Size distribution by intensity/volume/number 
Typical size distribution plots (intensity, volume, number) are depicted in Figure 1. The result plots show six independently prepared samples of IS batch 605211 at a concentration of 0.4 mg Fe/mL. For the visualization in Figure 1, the raw data taken from the DLS software were plotted with statistical software without further modification9. A size distribution by intensity impacted by a second peak is provided as an example of a bad result in Figure 1A. Figure 2 displays poor-quality data showing an additional signal at 5,000 nm.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63820/63820fig01.jpg" /> 
Figure 1: Size distribution. (A) intensity, (B) volume, and (C) number13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/63820/63820fig02.jpg" /> 
Figure 2: Representative poor-quality data. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
The test solution of IS batch 0371022A (0.4 mg Fe/mL), which was stored for 5 days at room temperature, showed an additional signal at ~5,000 nm, which is indicative of some additional particles (e.g., either dust or precipitation). Accordingly, the PDI originally determined at 0.130 was shifted to 0.184, while the Z-average was still close to the original value (i.e., 11.33) at 11.99 nm (unpublished data).
Precision was tested by two lab technicians on separate days. The mean value of 12 replicates was 11.32 nm with an RSD of 0.4% and 0.125 with an RSD of 1.5% for the Z-average and PDI, respectively, for the two technicians. The acceptance criteria were met (NMT 5% for the Z-average, NMT 20% for the PDI) (unpublished data).
Comparison of analyzable parameters 
In addition to calculating the basic parameters-the Z-average and polydispersity-the software of the DLS device also allows the calculation of size distributions that can be weighted according to the intensity of the detector signal or the volume (or number) of scattering particles. The relevance of comparing these parameters is obvious in the results outlined in Table 2. While the size distribution by number differed by up to a factor of 2 from the proposed intensity-based Z-average, only slightly lower values were calculated by the size distribution by volume. It should be noted, however, that intensity-based result reporting may be inaccurate if the iron-carbohydrate complex solutions contain larger particles or aggregates13.
Table 1: System parameters for the DLS. Abbreviations: RI = refractive index; DLS = dynamic light scattering13. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_Table 1 (3).xlsx" target="_blank">Please click here to download this Table.</a>
Table 2: Examples of how particle size determination by IS is affected by the data reporting approach. This table is adapted from Di Francesco and Borchard13. Abbreviations: SD = standard deviation; RSD = relative standard deviation; PDI = polydispersity index; IS = iron-sucrose. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_Table 2 (1).xlsx" target="_blank">Please click here to download this Table.</a>
Supplemental Figure S1: System operating steps. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_S1A_D.pdf" target="_blank">Please click here to download this File.</a>
Supplemental Figure S2: Creating a measurement file. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_S2A_B.pdf" target="_blank">Please click here to download this File.</a>
Supplemental Figure S3: System suitability test. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_S3.pdf" target="_blank">Please click here to download this File.</a>
Supplemental Figure S4: Starting a new measurement. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_S4A_D.pdf" target="_blank">Please click here to download this File.</a>
Supplemental Figure S5: Calculation of measurements. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/63820/63820_S5A_C.pdf" target="_blank">Please click here to download this File.</a>

Watch this Scientific Journal Video about Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes at JoVE.com

Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes

Dynamic light scattering (DLS) has emerged as a suitable assay for evaluating the particle size and distribution of intravenously administered iron-carbohydrate complexes. However, the protocols lack standardization and need to be modified for each iron-carbohydrate complex analyzed. The present protocol describes the application and special considerations for the analysis of iron sucrose.

Intravenously administered iron-carbohydrate nanoparticle complexes are widely used to treat iron deficiency. This class includes several structurally ...

dynamic-light-scattering-analysis-for-determination-particle-size

Nanyang Technological University

Research

JoVE Journal

Medicine

2.3K Views.  Vifor Pharma Management Ltd. Dynamische lichtverstrooiing, of DLS, is een fundamentele methode om de intacte deeltjesgrootte en -verdeling te evalueren. De analyse van nanodeeltjes uit ijzerkoolhydraten brengt echter enkele uitdagingen met zich mee. Een voordeel van DLS zijn breed beschikbare instrumentatie, eenvoudig uit te voeren analyse en het opstellen van protocollen voor de analyse van nanomaterialen.Een van de doelen van DLS is het evalueren van het polydispersieprofiel van de nanodeeltjes, wat uiteindelijk...

Video: Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes

Preparation and Characterization of SDF-1&#945;-Chitosan-Dextran Sulfate Nanoparticles

Chitosan (CS) and dextran sulfate (DS) are charged polysaccharides (glycans), which form polyelectrolyte complex-based nanoparticles when mixed under appropriate conditions. The glycan nanoparticles are useful carriers for protein factors, which facilitate the in vivo delivery of the proteins and sustain their retention in the targeted tissue. The glycan polyelectrolyte complexes are also ideal for protein delivery, as the incorporation is carried out in aqueous solution, which reduces the likelihood of inactivation of the proteins. Proteins with a heparin-binding site adhere to dextran sulfate readily, and are, in turn, stabilized by the binding. These particles are also less inflammatory and toxic when delivered in vivo. In the protocol described below, SDF-1&#945; (Stromal cell-derived factor-1&#945;), a stem cell homing factor, is first mixed and incubated with dextran sulfate. Chitosan is added to the mixture to form polyelectrolyte complexes, followed by zinc sulfate to stabilize the complexes with zinc bridges. The resultant SDF-1&#945;-DS-CS particles are measured for size (diameter) and surface charge (zeta potential). The amount of the incorporated SDF-1&#945; is determined, followed by measurements of its in vitro release rate and its chemotactic activity in a particle-bound form.

The objective of this protocol is to incorporate SDF-1&#945;, a stem cell homing factor, into dextran sulfate-chitosan nanoparticles. The resultant particles are measured for their size and zeta potential, as well as the content, activity, and in vitro release rate of SDF-1&#945; from the nanoparticles.

Chitosan (CS) and dextran sulfate (DS) are charged polysaccharides (glycans), which form polyelectrolyte complex-based nanoparticles when mixed under ...

Chemistry

Controlled Synthesis and Fluorescence Tracking of Highly Uniform Poly(N-isopropylacrylamide) Microgels

Stimuli-sensitive poly(N-isopropylacrylamide) (PNIPAM) microgels have various prospective practical applications and uses in fundamental research. In this work, we use single particle tracking of fluorescently labeled PNIPAM microgels as a showcase for tuning microgel size by a rapid non-stirred precipitation polymerization procedure. This approach is well suited for prototyping new reaction compositions and conditions or for applications that do not require large amounts of product. Microgel synthesis, particle size and structure determination by dynamic and static light scattering are detailed in the protocol. It is shown that the addition of functional comonomers can have a large influence on the particle nucleation and structure. Single particle tracking by wide-field fluorescence microscopy allows for an investigation of the diffusion of labeled tracer microgels in a concentrated matrix of non-labeled microgels, a system not easily investigated by other methods such as dynamic light scattering.

Controlled Synthesis and Fluorescence Tracking of Highly Uniform PolyN-isopropylacrylamide Microgels

Non-stirred precipitation polymerization provides a rapid, reproducible prototyping approach to the synthesis of stimuli-sensitive poly(N-isopropylacrylamide) microgels of narrow size distribution. In this protocol synthesis, light scattering characterization and single particle fluorescence tracking of these microgels in a wide-field microscopy setup are demonstrated.

Stimuli-sensitive poly(N-isopropylacrylamide) (PNIPAM) microgels have various prospective practical applications and uses in fundamental research. In this ...

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a technique used to measure the size distribution of polymer solutions or colloidal particles. Although this technique is widely used for the assessment of polymer solutions, it is difficult to measure the particle size in concentrated solutions due to the multiple scattering effect or strong light absorption. Therefore, the concentrated solutions should be diluted before measurement. Implementation of the confocal optical component in a dynamic light scattering microscope1 helps to overcome this barrier. Using such a microscopic system, both transparent and turbid systems can be analyzed under the same experimental setup without a dilution. As a representative example, a size distribution measurement of a temperature-responsive polymer solution was performed. The sizes of the polymer chains in an aqueous solution were several tens of nanometers at a temperature below the lower critical solution temperature (LCST). In contrast, the sizes increased to more than 1.0 &#181;m when above the LCST. This result is consistent with the observation that the solution turned turbid above the LCST.

A protocol for the direct measurement of particle size distribution in concentrated solutions using dynamic light scattering microscopy is presented.

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a ...

DNA-magnetic Particle Binding Analysis by Dynamic and Electrophoretic Light Scattering

Isolation of DNA using magnetic particles is a field of high importance in biotechnology and molecular biology research. This protocol describes the evaluation of DNA-magnetic particles binding via dynamic light scattering (DLS) and electrophoretic light scattering (ELS). Analysis by DLS provides valuable information on the physicochemical properties of particles including particle size, polydispersity, and zeta potential. The latter describes the surface charge of the particle which plays major role in electrostatic binding of materials such as DNA. Here, a comparative analysis exploits three chemical modifications of nanoparticles and microparticles and their effects on DNA binding and elution. Chemical modifications by branched polyethylenimine, tetraethyl orthosilicate and (3-aminopropyl)triethoxysilane are investigated. Since DNA exhibits a negative charge, it is expected that zeta potential of particle surface will decrease upon binding of DNA. Forming of clusters should also affect particle size. In order to investigate the efficiency of these particles in isolation and elution of DNA, the particles are mixed with DNA in low pH (~6), high ionic strength and dehydration environment. Particles are washed on magnet and then DNA is eluted by Tris-HCl buffer (pH = 8). DNA copy number is estimated using quantitative polymerase chain reaction (PCR). Zeta potential, particle size, polydispersity and quantitative PCR data are evaluated and compared. DLS is an insightful and supporting method of analysis that adds a new perspective to the process of screening of particles for DNA isolation.

This protocol describes the synthesis of magnetic particles and evaluation of their DNA-binding properties via dynamic and electrophoretic light scattering. This method focuses on monitoring changes in particle size, their polydispersity and zeta potential of particle surface which play major role in binding of materials such as DNA.

Isolation of DNA using magnetic particles is a field of high importance in biotechnology and molecular biology research. This protocol describes the ...

Characterization of Proteins by Size-Exclusion Chromatography Coupled to Multi-Angle Light Scattering (SEC-MALS)

Analytical size-exclusion chromatography (SEC), commonly used for the determination of the molecular weight of proteins and protein-protein complexes in solution, is a relative technique that relies on the elution volume of the analyte to estimate molecular weight. When the protein is not globular or undergoes non-ideal column interactions, the calibration curve based on protein standards is invalid, and the molecular weight determined from elution volume is incorrect. Multi-angle light scattering (MALS) is an absolute technique that determines the molecular weight of an analyte in solution from basic physical equations. The combination of SEC for separation with MALS for analysis constitutes a versatile, reliable means for characterizing solutions of one or more protein species including monomers, native oligomers or aggregates, and heterocomplexes. Since the measurement is performed at each elution volume, SEC-MALS can determine if an eluting peak is homogeneous or heterogeneous and distinguish between a fixed molecular weight distribution versus dynamic equilibrium. Analysis of modified proteins such as glycoproteins or lipoproteins, or conjugates such as detergent-solubilized membrane proteins, is also possible. Hence, SEC-MALS is a critical tool for the protein chemist who must confirm the biophysical properties and solution behavior of molecules produced for biological or biotechnological research. This protocol for SEC-MALS analyzes the molecular weight and size of pure protein monomers and aggregates. The data acquired serve as a foundation for further SEC-MALS analyses including those of complexes, glycoproteins and surfactant-bound membrane proteins.

Characterization of Proteins by Size-Exclusion Chromatography Coupled to Multi-Angle Light Scattering SEC-MALS

This protocol describes the combination of size exclusion chromatography with multi-angle light scattering (SEC-MALS) for absolute characterization of proteins and complexes in solution. SEC-MALS determines the molecular weight and size of pure proteins, native oligomers, heterocomplexes and modified proteins such as glycoproteins.

Analytical size-exclusion chromatography (SEC), commonly used for the determination of the molecular weight of proteins and protein-protein complexes in ...

Biochemistry

Ligand-Mediated Nucleation and Growth of Palladium Metal Nanoparticles

The size, size distribution and stability of colloidal nanoparticles are greatly affected by the presence of capping ligands. Despite the key contribution of capping ligands during the synthesis reaction, their role in regulating the nucleation and growth rates of colloidal nanoparticles is not well understood. In this work, we demonstrate a mechanistic investigation of the role of trioctylphosphine (TOP) in Pd nanoparticles in different solvents (toluene and pyridine) using in situ SAXS and ligand-based kinetic modeling. Our results under different synthetic conditions reveal the overlap of nucleation and growth of Pd nanoparticles during the reaction, which contradicts the LaMer-type nucleation and growth model. The model accounts for the kinetics of Pd-TOP binding for both, the precursor and the particle surface, which is essential to capture the size evolution as well as the concentration of particles in situ. In addition, we illustrate the predictive power of our ligand-based model through designing the synthetic conditions to obtain nanoparticles with desired sizes. The proposed methodology can be applied to other synthesis systems and therefore serves as an effective strategy for predictive synthesis of colloidal nanoparticles.

The main goal of this work is to elucidate the role of capping agents in regulating the size of palladium nanoparticles by combining in situ small angle x-ray scattering (SAXS) and ligand-based kinetic modeling.

The size, size distribution and stability of colloidal nanoparticles are greatly affected by the presence of capping ligands. Despite the key contribution ...

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. Modern instrumentation permits measurement of particle size as a function of time and/or temperature, but currently there is no simple method for performing DLS particle size distribution measurements in the presence of applied voltage. The ability to perform such measurements would be useful in the development of electroactive, stimuli-responsive polymers for applications such as sensing, soft robotics, and energy storage. Here, a technique using applied voltage coupled with DLS and a temperature ramp to observe changes in aggregation and particle size in thermoresponsive polymers with and without electroactive monomers is presented. The changes in aggregation behavior observed in these experiments were only possible through the combined application of voltage and temperature control. To obtain these results, a potentiostat was connected to a modified cuvette in order to apply voltage to a solution. Changes in polymer particle size were monitored using DLS in the presence of constant voltage. Simultaneously, current data were produced, which could be compared with particle size data, to understand the relationship between current and particle behavior. The polymer poly(N-isopropylacrylamide) (pNIPAM) served as a test polymer for this technique, as pNIPAM's response to temperature is well-studied. Changes in the lower-critical solution temperature (LCST) aggregation behavior of pNIPAM and poly(N-isopropylacrylamide)-block-poly(ferrocenylmethyl methacrylate), an electrochemically active block-copolymer, in the presence of applied voltage are observed. Understanding the mechanisms behind such changes will be important when trying to achieve reversible polymer structures in the presence of applied voltage.

Here, a protocol to apply voltage to solution during dynamic light scattering particle size measurements with the intent to explore the effect of voltage and temperature changes on polymer aggregation is presented.

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. ...

Assembly and Characterization of Polyelectrolyte Complex Micelles

Polyelectrolyte complex micelles (PCMs), core-shell nanoparticles formed by self-assembly of charged polymers in aqueous solution, provide a powerful platform for exploring the physics of polyelectrolyte interactions and also offer a promising solution to the pressing problem of delivering therapeutic oligonucleotides in vivo. Developing predictive structure-property relationships for PCMs has proven difficult, in part due to the presence of strong kinetic traps during nanoparticle self-assembly. This article discusses criteria for choosing polymers for PCM construction and provides protocols based on salt annealing that enable assembly of repeatable, low-polydispersity nanoparticles. We also discuss PCM characterization using light scattering, small-angle X-ray scattering, and electron microscopy.

We provide protocols and representative data for designing, assembling, and characterizing polyelectrolyte complex micelles, core-shell nanoparticles formed by polyelectrolytes and hydrophilic charged-uncharged block copolymers.

Polyelectrolyte complex micelles (PCMs), core-shell nanoparticles formed by self-assembly of charged polymers in aqueous solution, provide a powerful ...

Analyzing Large Protein Complexes by Structural Mass Spectrometry

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an array of dynamic, multi-protein complexes1. To gain a mechanistic understanding of the various cellular processes, it is crucial to determine the structure of such protein complexes, and reveal how their structural organization dictates their function. Many aspects of multi-protein complexes are, however, difficult to characterize, due to their heterogeneous nature, asymmetric structure, and dynamics. Therefore, new approaches are required for the study of the tertiary levels of protein organization.
One of the emerging structural biology tools for analyzing macromolecular complexes is mass spectrometry (MS)2-5. This method yields information on the complex protein composition, subunit stoichiometry, and structural topology. The power of MS derives from its high sensitivity and, as a consequence, low sample requirement, which enables examination of protein complexes expressed at endogenous levels. Another advantage is the speed of analysis, which allows monitoring of reactions in real time. Moreover, the technique can simultaneously measure the characteristics of separate populations co-existing in a mixture. 
Here, we describe a detailed protocol for the application of structural MS to the analysis of large protein assemblies. The procedure begins with the preparation of gold-coated capillaries for nanoflow electrospray ionization (nESI). It then continues with sample preparation, emphasizing the buffer conditions which should be compatible with nESI on the one hand, and enable to maintain complexes intact on the other. We then explain, step-by-step, how to optimize the experimental conditions for high mass measurements and acquire MS and tandem MS spectra. Finally, we chart the data processing and analyses that follow. Rather than attempting to characterize every aspect of protein assemblies, this protocol introduces basic MS procedures, enabling the performance of MS and MS/MS experiments on non-covalent complexes. Overall, our goal is to provide researchers unacquainted with the field of structural MS, with knowledge of the principal experimental tools.

Mass spectrometry has proven to be a valuable tool for analyzing large protein complexes. This method enables insights into the composition, stoichiometry and overall architecture of multi-subunit assemblies. Here, we describe, step-by-step, how to perform a structural mass spectrometry analysis, and characterize macromolecular structures.

Living cells control and regulate their biological processes through the coordinated action of a large number of proteins that assemble themselves into an ...

Biology

Routine Screening Method for Microparticles in Platelet Transfusions

Platelet inventory management based on screening microparticle content in platelet concentrates is a new quality improvement initiative for hospital blood banks. Cells fragment off microparticles (MP) when they are stressed. Blood and blood components may contain cellular fragments from a variety of cells, most notably from activated platelets. When performing their roles as innate immune cells and major players in coagulation and hemostasis, platelets change shape and generate microparticles. With dynamic light scattering (DLS)-based microparticle detection, it is possible to differentiate activated (high microparticle) from non-activated (low microparticle) platelets in transfusions, and optimize the use of this scarce blood product. Previous research suggests that providing non-activated platelets for prophylactic use in hematology-oncology patients could reduce their risk of becoming refractory and improve patient care. The goal of this screening method is to routinely differentiate activated from non-activated platelets. The method described here outlines the steps to be performed for routine platelet inventory management in a hospital blood bank: obtaining a sample from a platelet transfusion, loading the sample into the capillary for DLS measurement, performing the DLS test to identify microparticles, and using the reported microparticle content to identify activated platelets.

Platelet inventory management based on screening microparticle content in platelet concentrates is a new quality improvement initiative in hospital blood banks. The goal is to differentiate activated from non-activated platelets to optimize the use of platelets. Providing non-activated platelets to hematology-oncology patients might reduce their high risk to become refractory.

Platelet inventory management based on screening microparticle content in platelet concentrates is a new quality improvement initiative for hospital blood ...

Dynamic Light Scattering Analysis for the Determination of the Particle Size of Iron-Carbohydrate Complexes

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