WHO/BS/2015.2270

ENGLISH ONLY

EXPERT COMMITTEE ON BIOLOGICAL STANDARDIZATION

Geneva, 12 to 16 October 2015

Collaborative Study to establish the 1st WHO International Standard for

BKV DNA for nucleic acid amplification technique (NAT)-based assays

Sheila Govind, Jason Hockley, Clare Morris and the *Collaborative Study Group

Division of Virology and Biostatistics. National Institute of Biological Standards and

Control, Blanche Lane, South Mimms, Potters Bar, Hertfordshire. EN6 3QG. United

Kingdom.

*See Appendix I

NOTE:

This document has been prepared for the purpose of inviting comments and suggestions on

the proposals contained therein, which will then be considered by the Expert Committee on

Biological Standardization (ECBS). Comments MUST be received by 14 September 2015

and should be addressed to the World Health Organization, 1211 Geneva 27, Switzerland,

attention: Technologies, Standards and Norms (TSN). Comments may also be submitted

electronically to the Responsible Officer: Dr M Nübling at email: nueblingc@who.int

© World Health Organization 2015

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WHO/BS/2015.2270

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Summary

An international collaborative study was conducted to establish the 1st WHO International

Standard for use in the standardisation of Polyoma virus BKV nucleic acid amplification

(NAT) technology assays. Two candidate samples of freeze-dried whole BKV virus

preparations (subtype 1b-1 and 1b-2), formulated in 10mM Tris-HCl pH 7.4, 0.5% Human

serum albumin (HSA), 0.1% D-(+)-Trehalose dehydrate, were analysed by 33 laboratories

from 15 countries, each using their routine NAT-based assays for BKV detection. Of the two

candidate samples 14/202 and 14/212 the latter was found to be most suitable for use as an

international standard.

The results from the accelerated thermal degradation stability studies performed at 3 months

have demonstrated that the candidate material is stable at temperatures used for storage (-

20°C) and laboratory manipulation (4°C to 20°C), as well 37°C to 45°C reflecting ambient

temperature fluctuations encountered during global shipment. Further real-time stability

studies will ensue to assess the long-term stability of the candidate.

Based upon the conclusion from the dataset received, it is proposed that the candidate sample

(14/212; 4092 vials) be established as the 1st WHO International Standard for BKV DNA for

nucleic acid amplification technique (NAT)-based assays with an assigned potency of 7.0

log10 IU/ mL per ampoule.

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Introduction

BK Virus is a member of the polyomaviridae family of double stranded DNA viruses.

Primary infection is acquired in early childhood and in the majority of cases is asymptomatic.

Consequently seropositivity across the adult population is as high as approximately 90% [1].

Following primary infection the virus establishes latency in the kidneys and urinary tract with

intermittent reactivation throughout life, where virus is detectable in <5% of healthy

individuals [2, 3].

There are 4 main BKV subtypes I, II, III and IV based on nucleotide variation of the VP1

gene that encodes for the viral capsid protein 1. Subtype I is prevalent in most geographical

regions with a prevalence of 46-82% throughout the world, whilst subtype IV, the next most

prevalent subtype is more commonly associated with East Asian populations, and subtypes II

and III are rare [4]. Subtype I can be further divided into sub-groups 1a, 1b-1,1b-2, and 1c on

the basis of DNA sequence variation [5]. Each have been reported to be traceable to a unique

geographical location where 1a is most prevalent in Africa, 1b-1 in South-east Asia, 1b-2 in

Europe and 1c in North-east Asia [6].

The clinical sequelae of BKV reactivation is confined to the immunocompromised state, such

as in renal transplantation and haematopoietic stem cell transplantation (HSCT) patients.

Under immunosuppression, latent viral reactivation can result in BKV-associated nephropathy

(BKVAN) characterized by interstitial nephritis and/or urinary tract stenosis, affecting up to

10% of patients. This can cause allograft loss in up to 60% of affected kidney transplant

recipients [7]. In HSCT patients BKV reactivation can present with haemorrhagic cystitis that

can be associated with significant morbidity and mortality [8].

Guidelines for the management of BKVAN in renal transplant patients recommend rigorous

viral monitoring for BKV reactivation using quantitative PCR of urine and plasma post-

transplantation for specified time points. Viral reactivation is detectable in the urine several

weeks before viremia is detectable. A BKV viral load (BKVL) of ≥4 log10/mL (in

plasma/serum) for >3 weeks is presumed predictive for BKVAN, upon which a reduction in

immunosuppression is recommended. This threshold value has been recommended by the UK

Renal Association and by the American Society of Transplantation (AST).

An international group convened in 2006 and 2008 to discuss the requirement for the

international standardisation of JCV NAT assays, alongside which BKV NAT assay

standardisation was also discussed. This included participants from academia (Professor

Hans Hirsch, Dr Manfred Weidman), pharmaceutical industry (Biogen Idec, GSK,

Millennium Pharmaceuticals), the External Quality Assessment provider QCMD (Quality

Control for Molecular Diagnostics) and governmental institutions (NIBSC). Evaluations from

QCMD proficiency panels in 2007 and 2008 for both BKV and JCV highlighted large

variability in NAT-assay quantitative data, underscoring the need for greater standardisation

and the availability of international standards that could be used to calibrate the different

working standards used by individual laboratories. The merits of four source materials were

considered for use as candidate materials for the preparation of IS candidates. It was

concluded that purified virions from BKV infected cell cultures should be used for the

preparation of a BKV candidate international standard (Manuscript in preparation Paola

Cinque, Proceedings of the Second meeting on JCV PCR standardisation: Towards the

establishment of International standards). A publication by Hoffman et al further reiterated the

need for standardisation. “The absence of standardized BKV assays constitutes a major

obstacle to the comparison of BK titers measured at different institutions and may severely

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limit the usefulness of generalized quantitative viral-load cutoffs in screening and diagnostic

protocols.” [9].

The current study describes the preparation and evaluation of two BKV candidate materials,

intended for use as primary international standards for NAT-detection assays. They are

referred to in the text by the assigned NIBSC codes 14/202 and 14/212, as well as by the

alphabetic code given as part of the collaborative study test panel, Sample B and D

respectively.

Aim of the study

The purpose of this study is to establish the 1st WHO International Standard for BK virus

DNA for use in NAT detection assays primarily for use in clinical diagnostics. Two

candidates were evaluated in a multicentre collaborative study, and the results obtained has

enabled a potency estimation to be assigned to the proposed candidate based on the range of

NAT assays that are currently in use, represented by the collaborative study datasets. The

collated data has also been used to determine the suitability of the candidate material for use

as a primary reference material in the calibration of secondary reference materials.

Furthermore the evaluation conducted provides a preliminary assessment of the

commutability of the candidate formulation when used as a reference standard for a range of

matrices following reconstitution in nuclease-free water.

Bulk Material and Processing

Candidate Standards

Two materials were evaluated for consideration as proposed candidates for BKV IS

production. The first candidate 14/202 was sourced from Dr JL Murk MD, Medical

Microbiology Department of Virology, University Medical Centre Utrecht, The Netherlands.

The second candidate 14/212 was sourced from NIBSC, which comprised a virus stock

archived in 1998. Both proposed BKV standard formulations were cell-free, live virus

preparations from productively infected cell culture. The candidate standards 14/202 and

14/212 have both been formulated in universal buffer comprising 10mM Tris-HCl pH 7.4,

0.5% Human serum albumin (HSA), 0.1% D-(+)-Trehalose dehydrate, to permit dilution into

a sample matrix pertinent to the end user. Both preparations have been freeze-dried to ensure

long term stability of the product.

The donated cultured viral stock was obtained from a viral isolate from the urine of a bone

marrow transplant (BMT) recipient diagnosed with BK-cystitis. As the donated BKV stock

had not been genotyped the whole viral genome was sequenced at NIBSC using Sanger

sequencing to confirm the genotype of the isolate as well as assure the sequence integrity of

the viral genome post propagation. Primer pairs were designed to amplify ~1000bp regions of

the entire viral genome. PCR was performed on viral DNA extracted using the QIAamp Viral

RNA mini kit (QIAGEN, Germany) from the donated cell culture supernatant. This extraction

kit is recommended for the extraction of all viral nucleic acids. PCR was performed on the

Veriti 96 well thermal cycler (Applied Biosystems) using Platinum® Taq DNA Polymerase

(Life Technologies). Sequencing reactions were performed on purified PCR templates on the

3130 XL Genetic Analyzer (Applied Biosystems). The sequence was identified to be BKV1b-

1 subtype, based on base pair comparison within the VP1 region and showed a 98.9%

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sequence identity with the BKV 1b-1 sequence (NCBI GenBank Accession AB301095). The

NIBSC BKV stock material was also subject to full sequence analysis as described above and

identified to be BKV1b-2 which showed 98.4% sequence identity to (NCBI GenBank

Accession AB301093). Further sequencing is in progress to verify the subgroup allocation.

Culture of bulk material

A total volume of 100ml (2 x50ml) of viral supernatant was provided by the donating lab,

shipped on dry-ice, and stored at -80⁰C until required. Briefly the propagation of BK virus

was achieved as summarised by the donating laboratory. BKV culture was performed at 39⁰C

without CO2 using the human foetal lung fibroblast cell line MRC-5 cultured in MEM-Eagle

with Hanks salts, 0,084% Na-bicarbonate, 200 mM L-Glutamine and 3% FBS. Culture

supernatant was harvested when maximal cytopathic effect (CPE) was visible (after 4 weeks)

and cleared from cellular debris by centrifugation for 5 minutes at 380 g (1316 rpm).

Subsequently FBS was added to the BKV viral stock to obtain a final concentration of 10%

and then stored at -80⁰C. The in-house BKV culture was also performed using MRC-5 cell

cultures grown at 37⁰C with 5% CO2 using MEM (Sigma Cat# G8644), 10% FCS, 2%

200mM L-Glutamine (Sigma Cat# G7513), 1.5% 1M HEPES (Sigma Cat# H0887). Culture

supernatant was harvested when maximal CPE was visible, approximately after ~4 weeks and

cleared from cellular debris by centrifugation for 15 minutes at 150 g. 70ml of culture

supernatant was harvested and FCS was added to the cleared BKV viral stock to obtain a final

concentration of 10% FCS which was then stored at -80⁰C until required for bulk preparation.

Pre-fill testing

The concentration of the BK viral stocks were determined at NIBSC using a CE marked IVD

kit, BKV ELITE MGB kit (ELITech, Torino, Italy). Briefly nucleic acid extractions were

performed using 140 µL of BKV sample using the QIAamp Viral RNA mini Kit (QIAGEN,

Germany). Extractions were performed using the QIAcube, an automated extraction platform

(QIAGEN, Germany). Extractions were performed with the inclusion of an internal control

(CPE) which was included as positive control for DNA extraction from non-cellular

biological samples (ELITech, Torino, Italy). 20µl of the 80µl purified nucleic acid sample

was amplified by qPCR using the probe-based quantification BKV ELITE MGB kit

(ELITech, Torino, Italy) on the ABI 7900HT Real-time PCR instrument (Applied

Biosystems, California USA). Viral quantification was achieved with the inclusion of 4

plasmid based quantification standards in the amplification reaction, to generate a standard

curve with a dynamic range of 105-10

2 quantifiable gEq/mL (ELITech, Torino, Italy). The

donating laboratory provided an estimation of ~3x108 copies/mL for the viral load of the

sample. Using the method described above the donated viral stock was determined to contain

a copy number of 3.24 x 108 gEq/mL (Range 2.89 x 10

8 – 3.57 x 10

8 gEq/mL). The NIBSC

cultured BKV was estimated to have a viral copy number of 2.55 x10e8 gEq /mL (Range 2.38

x 108 – 2.72 x 10

8 gEq/mL). (1 genome equivalent/ mL (gEq/mL) is equivalent to 1 copy/mL

according to ELItech kit instructions).

Preparation of bulk material and evaluation of materials

The production dates of each of the BKV candidates were 20/10/14 and 10/11/14. However

both candidate bulks were prepared in an identical fashion. The universal buffer 10mM Tris-

Cl pH 7.4, 0.5% Human serum albumin (HSA), 0.1% D-(+)-Trehalose dehydrate was

prepared at NIBSC. The HSA used in the production of the candidate standards was derived

WHO/BS/2015.2270

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from licensed products that was further screened at NIBSC to be negative for anti-HIV-1,

HIV-2, HBsAg, and HCV. Frozen aliquots of the viral supernatants were thawed using a 30⁰C

water bath prior to dilution into universal buffer. A 100 fold dilution was made in order that

the bulk preparation should contain approximately 3.24 x 106

copies/mL in the case of the first

candidate and 2.55 x106 copies /mL in the case of the second candidate, in a final volume of

4.5L of universal buffer. 100-150mL of each of the liquid bulks was divided into aliquots of

0.25ml, 0.55ml, 0.75ml and 1.1ml in 2ml screw cap Sarstedt tubes and stored at -80⁰C for

viral copy determination as well as for inclusion in the collaborative study panel to be tested

alongside the equivalent lyophilised preparation. The remaining bulk volume in each case was

processed for lyophilisation which was designated NIBSC product code 14/202 for the first

candidate and 14/212 for the second candidate.

Filling and lyophilisation of candidate standard Lyophilisation

The filling and lyophilisation of both bulk materials was performed at NIBSC, and the

production summary is detailed in Table 1 for 14/202 and Table 2 for 14/212. The filling was

performed in a Metall and Plastic GmbH (Radolfzell, Germany) negative pressure isolator

that contains the entire filling line and is interfaced with the freeze dryer (CS150 12m2, Serail,

Argenteuil, France) through a ‘pizza door’ arrangement to maintain integrity of the operation.

The bulk material was kept at 18°C throughout the filling process, and stirred constantly using

a magnetic stirrer. The bulk was dispensed into 5 mL screw cap glass vials in 1 ml aliquots,

using a Bausch & Strobel (Ilfshofen, Germany) filling machine FVF5060. The homogeneity

of the fill was determined by on-line check-weighing of the wet weight, and vials outside the

defined specification were discarded. Filled vials were partially stoppered with halobutyl

14mm diameter cruciform closures and lyophilized in a CS150 freeze dryer. Vials were

loaded onto the shelves at +4°C, then cooled to -50⁰C and held at this temperature for 2 hours.

A vacuum was applied to 270 µb over 1 hour, followed by ramping to 100 µb over 1 hour.

The temperature was then raised to -15°C, and the vacuum maintained at this temperature for

31 hours. The vacuum was lowered to 30 µb and the shelves were ramped to 25°C over 10

hours before releasing the vacuum and back-filling the vials with nitrogen, produced by

evaporation of liquid nitrogen with an analysis of 99.999% purity. The vials were then

stoppered in the dryer, removed and capped in the isolator, and the isolator decontaminated

with formaldehyde before removal of the product. The sealed vials are stored at -20°C at

NIBSC under continuous temperature monitoring for the lifetime of the product.

Post-fill testing

Validation of study samples

The freeze-dried candidates (14/202 and 14/212) were tested to determine the homogeneity of

the viral contents of the lyophilised material post-production. Briefly lyophilised samples

were reconstituted in 1 mL of nuclease-free water (QIAGEN, Germany), mixed gently on a

vortex and left for 20 minutes. 140 µL of reconstituted sample was used for extraction and the

extracted DNA used for amplification as described for Pre-fill testing.

The assessments of residual moisture and oxygen content are critical parameters when

considering the stability and shelf life of lyophilized products. Non-invasive moisture and

oxygen determinations were made as follows. Vials of excipient only formulations for the

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proposed BKV standards were prepared to be used to compare between destructive and non-

invasive moisture analysis by near Infra-Red reflectance (NIR, Process Sensors MT 600P,

Corby, UK). Results obtained from the non-infectious samples by NIR would then be

correlated to coulometric Karl Fischer (KF, Mitsubishi CA-100, A1 Envirosciences,

Cramlington, UK) to give % w/w moisture readings. Moisture determinations were compared

against values from a standard curve, which was made using 10 vial replicates of non-

infectious excipient only samples, which were subjected to varying exposure times (0, 5, 10,

15, 30, 45, 60 and 90 minutes) to atmospheric air, by removing screw caps and raising the

stopper to the filling position for the designated period of time before the stoppers were fully

re-inserted and the caps re-sealed. Subsequently, several vials of each time point were tested

by coulometric Karl Fischer and the standard curve generated. Then 12 vials of the definitive

batch containing lyophilised BKV in excipient formulation were tested by NIR and their

moistures assigned based on the calibration curve generated from the data from the non-

infectious excipient vials.

Oxygen headspace content is an indicator of the success of the nitrogen back-filling process in

the dryer and subsequent integrity of the seal on the vials. Oxygen headspace was measured

using non-invasive headspace gas analysis (FMS-760 Lighthouse, Charlottesville, VA). This

correlates the NIR absorbance at 760nm (for oxygen) based on a NIR laser source and is

calibrated against equivalent vials, sealed with traceable oxygen gas standards. Calibration of

the unit was achieved using 5ml screw capped vials containing oxygen standards 0% and

20%.

Stability assessment of candidate product

To predict the stability of the freeze-dried materials, vials of the proposed BKV IS candidates

14/202 and 14/212 are subject to accelerated degradation studies. This entails the storage of

multiple vials of each candidate post production at -70⁰C, -20⁰C, +4⁰C, +20⁰C, +37⁰C and

+45⁰C for up to 10 years. Periodically 3 vials are removed from each temperature and tested

for viral potency using the real-time PCR method described above, to provide an indication of

stability at the storage temperature of -20⁰C. 3 tests are performed in the first year and

annually thereafter.

Study samples

A total of 7 study samples coded A-G, were prepared for evaluation in this study (Table 1).

Participating laboratories were sent a questionnaire (Appendix II) prior to sample dispatch, to

ascertain the types of clinical samples routinely assayed in their laboratory and to determine

the quantity of sample required for their extraction methodology. Sample sets were thereby

customised to each participant based on the responses received. All participants received the

candidate BKV materials in both the lyophilised and liquid state (Candidate 14/202; B and C,

Candidate 14/212; D and E). In addition to the proposed IS candidates 3 other samples were

also included for testing alongside the candidate materials. These were a plasmid construct

encoding the BKV genome excluding a section of the non-coding regulatory region (Sample

A); kindly donated by the National Institute of Standards and Technology, Gaithersburg,

USA. The donating laboratory provided an estimation of 1.5-1.8 x 106 genome copies/ µL.

Two patient samples were kindly donated by the Rigshospitalet, Department Clinical

Microbiology, Copenhagen, Denmark. 3ml aliquots of urine and plasma obtained from a bone

marrow transplant patient were received on dry-ice. The viral copy numbers of the neat

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samples were estimated by the donating laboratory to be 2.3 x 107

copies/mL (urine) and 6.5 x

105

copies/mL (plasma). Each 3 ml aliquot was diluted into 107 mL of BKV negative urine

and plasma respectively and aliquoted into smaller volumes (0.25ml, 0.55ml, 0.75ml and

1.1ml in 2ml screw cap Sarstedt tubes) commensurate to the volumes required by participants

to perform duplicate nucleic acid extractions in 3 separate runs as part of the collaborative

study.

Plasma was obtained from the National Blood Service and urine was obtained from an in

house donor. Samples were tested prior to dispatch to study participants to confirm the viral

load and homogeneity of the aliquots. All liquid samples were stored at -80⁰C until required

for shipment.

Design of the study

Participants were shipped 6 vials of each sample on dry-ice and asked to perform duplicate

analysis of each sample using a fresh vial of each sample for each data point in 3 independent

runs. This was with the exception of sample A, where participants received 3 vials, and

participants were recommended to use 1 vial per run. (In some instances where insufficient

volumes of samples remained, participants received fewer vials, but quantities sufficient for 6

extractions).

Study protocol

Upon receipt participants were directed to store samples either at -70⁰C (C, E, F, G) or -20⁰C

(A, B, D). Participants were directed to reconstitute the lyophilised sample (B and D) in 1ml

of nuclease-free molecular grade water for a minimum of 20 minutes with occasional

agitation before use. For liquid preparations participants were directed to thaw samples just

prior to extraction.

Participants performing quantitative analysis, were directed to test samples B and D for the

first run, undiluted and in addition at a minimum of 3-4 serial ten-fold dilutions in a single

sample matrix commonly used in their laboratory (e.g. urine, plasma etc.). For example,

dilutions of 1/10, 1/100 etc. were suggested such that at least 1 of these dilutions should fall

into the linear range of quantitation in their assay. For subsequent assays participants were

requested to test a minimum of two serial dilutions of sample B and D that fall within the

linear range of their assay.

Those participants performing qualitative analysis were requested for the first assay to test

samples undiluted and then an additional minimum of 7 serial 1:10 fold serial dilutions of

Sample B and D in a single sample matrix commonly used in their laboratory (e.g. urine,

plasma etc.) in order to determine the end point of detectable viral DNA. Participants were

asked to select a single matrix for the dilution of both samples B and D such that the data

would be comparable between the two lyophilised BKV candidates. Participants were

requested to ensure their data included at least 2 dilution points at which a product was no

longer detectable. For the 2 remaining qualitative assays, participants were requested to re-test

the dilutions around the assay end point as determined in the first assay, and to include a

minimum of two half-log serial dilutions either side of the determined end point dilution.

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Sample A was estimated to be 109 genome copies/ mL therefore participants were advised to

perform serial dilutions that fell within the linear range of their quantification assay.

Participants were asked to only use nuclease-free water for the dilution of this sample. For

clinical samples F and G, participants were asked to test these samples neat.

A results report form was provided to each participant. This included a sheet to provide

details of extraction and amplification processes in the assays performed. Separate sheets

were provided to submit data values of each assay performed. An example study protocol is

shown in Appendix III.

Participants

36 participants were recruited, however 3 of these were unable to proceed with the study due

to import constrains. Study samples were sent to 33 participants representing 15 different

countries (Appendix 1). Participants were selected from research and clinical laboratories

based on recent peer reviewed publications on BKV NAT detection assays. Manufacturers of

BKV NAT in-vitro diagnostic (IVD) kits were also included as well as reference and EQA

laboratories. All participating laboratories were assigned randomly a laboratory code by

which to reference their data thereby assuring laboratory anonymity. Where laboratories

submitted more than one dataset they are referred to as, for example 27a, 27b etc.

Statistical Methods

Qualitative and quantitative assay results were evaluated separately. In the case of qualitative

assays, for each laboratory and assay method, data from all assays were pooled to give a

number positive out of number tested at each dilution step. A single ‘end-point’ for each

dilution series was calculated, to give an estimate of NAT detectable units/mL. It should be

noted that these estimates are not necessarily directly equivalent to copies/ mL.

In the case of quantitative assays, results were reported as copies/mL and were used directly

in the analysis. For each assay run, a single estimate of log10 copies/mL was obtained for each

sample, by taking the mean of the log10 estimates of copies/mL across replicates, after

correcting for any dilution factor. A single estimate for the laboratory and assay method was

then calculated as the mean of the log10 estimates of copies/mL across assay runs.

The overall mean estimates were calculated as the means of all individual laboratories.

Variation between assays (intra-laboratory) and between laboratories (inter-laboratory) was

expressed as standard deviations (SD) of the log10 estimates and % geometric coefficient of

variation (%GCV) of the actual estimates. The potencies of each sample (A, C, E, F and G)

relative to sample B or D, the candidate International Standards, were calculated per

laboratory as the difference in estimated log10 units per mL (test sample – candidate standard).

Potencies were also estimated for samples F and G relative to sample A.

A comparison of log10 copies/mL results (after correction for dilution) was carried out in

Minitab 17 [Minitab. Inc, State College, PA, USA] by fitting a general linear model with

laboratory and diluent (“undiluted”, “plasma”, “urine”, “Blood” etc.) as factors, with post-hoc

Dunnett’s test being used to compare results obtained using different diluents with those

obtained for undiluted samples.

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Results and analysis

Validation of study samples

Stability studies

Production data for the candidate standards sample B and D validated the CV of the fill mass

and the mean residual moisture and oxygen content, which were both determined to be within

limits acceptable s for a WHO International Standard (Table 2 and 3).

The mean BKV viral nucleic acid load from 12 randomly selected vials containing the

candidate IS preparations were tested in duplicate for homogeneity. Each vial was

reconstituted using nuclease-free water for 20 minutes with gentle agitation. 140 µL of a 1:10

dilution from each vial was extracted as described above and the extracted DNA used for

amplification. An average of each duplicate was then used to determine the average viral copy

number (Table 4).

A 3 month thermal accelerated degradation assessment was performed on the candidate

standards by assessing the change in potency if any, of detectable BKV viral nucleic acid

across the various storage temperatures. 1 vial was tested at each of the storage temperatures

in 3 independent assays. Each vial was tested at a 10 fold dilution and a further 100 fold

dilution. The values obtained at 3 months show no observable drop in potency at temperatures

up to +45⁰C (Table 5). The stability analysis using Degtest-R (CombiStats, EDQM) was

unable to show any predicted loss of potency. For candidate 14/212 the model showed an

apparent upwards trend in activity (+0.006% per year when stored at -20⁰C). The reason for

this is not clear. Further analysis are scheduled to be performed which will provide an

additional evaluation on the stability and suitability of the candidates for long term use.

Data Received

Data were received from 33 laboratories from 15 different countries. They were allocated a

participant number at random. From the 33 laboratories 35 quantitative datasets, and 3

qualitative datasets were analysed. For quantitative data, participants returned values as

copies/mL or log10 copies/ mL. 2 laboratories provided data in gEq/mL which were assumed

to be equivalent to copies/mL according to the manufacturer’s protocol. Qualitative data was

expressed as positive or negative detection. In general, participants performed their

experimental runs using 1 assay method with the use of one matrix type for the dilution of

Sample B and D.

Exceptions were as follows:

Participant 10 performed their analysis using two different versions of a commercial assay on

a different amplification platform for each. They were given the designation10a and 10b.

Participant 13 performed one quantitative assay and one qualitative assay which were given

the designation 13a and 13b respectively.

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Participant 21 performed two sets of analysis, using 2 types of extraction kits and

corresponding automated extraction platforms. Each was then performed on a different

amplification platform and given the designation 21a and 21b respectively.

Participant 27 performed amplification reactions using 4 different amplification instruments

each of these methods were designated a-d. In addition dilutions of Sample B and D were

made in 3 different matrices (Urine, Whole Blood, and Plasma) and assayed on each of the 4

amplification platforms. Therefore mean estimates of sample B or D from this laboratory is

represented by the total dataset based on all 3 diluents, and represented as 27a, 27b, 27c or

27d to distinguish each method variation.

Participant 35 did not receive sample C. A sufficient number of vials were not available for a

comprehensive analysis comparable to other laboratories.

Summary of assay methodologies Most participants used commercially available nucleic acid extraction kits, which included:

BioMerieux: NucliSENS® easyMag

®. MACHEREY-NAGEL: NucleoSpin

® Blood.

Lifetechnologies: ChargeSwitch® gDNA Serum Kit. Anatolia Geneworks: Magrev®

Viral

DNA/RNA Extraction Kit. ELITechGroup S.p.A: ELITe GALAXY 300 Extraction Kit.

Norgen Biotek Corp: Plasma/Serum DNA Purification Kit. Roche: MagNA Pure 96 DNA and

Viral NA Small/Large Volume Kit, MagNA Pure LC Total Nucleic Acid Isolation Kit,

MagnaPure LC Universal Pathogen kit. QIAGEN: (QIAsymphony DSP Virus/Pathogen Kit,

QIAsymphony VIRUS-BACTERIA midi kit, EZ1 DSP Virus Kit, QIAamp 96 DNA

QIAcube HT kit, MagAttract Virus Mini M48 kit, QIAamp DNA mini kit, QIAamp Viral

RNA kit, QIAamp Viral RNA Mini QIAcube Kit, QIAamp DSP Virus RNA mini Kit, QIA

amp DNA Blood Mini Kit. Only1 manual method was performed using Proteinase

K/Chloroform-Phenol extraction. 15 of the 33 laboratories used QIAGEN kits, 7 laboratories

using BioMerieux kits and 5 using Roche extraction kits. No two methodologies were alike.

Of the 33 laboratories 10 performed manual extractions, whilst the remainder performed

automated extractions on platforms including: BioMérieux (Nuclisens EasyMAG), QIAGEN

(QIAcube, QIAcube HT, QIAsymphony SP, M48 BioRobot MDX, EZ1 Advanced XL),

Roche (MagNA Pure LC, MagNA Pure 96), and ELITech Group (ELITe GALAXY).

For PCR amplification 35 datasets were quantitative compared with 3 qualitative datasets. 15

laboratories generated data using in-house amplification methods, compared with 18

laboratories generating datasets using commercially available amplification assays. 8 BKV

NAT commercial assays were represented in the study; Eurospital (Euro-RT BKV Kit),

ELITEch (BKV ELITe MGB kit), Altona Diagnostics (Realstar BKV PCR Kit 1.0), Anatolia

Geneworks (Bosphore® BKV Quantification Kit v1), and Epoch Biosciences (MGB Alert BK

Virus Primer mix ASR), Biomérieux (R-Gene BK virus quantification kit), Luminex

(Multicode BK primers (ASR) and MultiCode associated ancillary reagents), and QIAGEN

(Artus BK Virus RG PCR assay). In addition the Abbott Molecular Inc, IRIDICA Viral IC

Assay Reagent Kit which combines PCR and electrospray ionisation mass spectrometry.

Differences in the targeted PCR amplification region were as follows; the T-antigen (small

and large) target gene region was used by 11 of the 33 participating laboratories, 9

laboratories used the VP1 region. 6 datasets were derived by amplification of VP2 and VP3

genes, and 1 using the NCCR non-coding region. 6 data sets did not disclose the region of

amplification. A range of amplification platforms were also represented by returned datasets,

WHO/BS/2015.2270

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which include Applied Biosystems instruments (7500 Fast, 7900HT Real-time PCR Systems),

Bio-rad (DX-Real-time, I cycler, CFX connect), Corbett Research QIAGEN (Rotor-Gene

6000, Rotor- Gene Q), Roche (LightCycler® 480 II, LightCycler

® 2), Eppendorf

Mastercycler® pro S, Anatolia Geneworks (Montania® 4896 Real-Time PCR Instrument),

Life Technologies (Stratagene MX3000P QPCR system), Cepheid (Smartcycler) and Focus

Diagnostics (Integrated Cycler).

Estimated potencies of study samples

The laboratory mean estimates from 35 quantitative and 3 qualitative datasets are presented in

Tables 6 and 7 respectively. Table 6 shows the mean estimates as log10 copies/ mL from

quantitative assays performed for each of the samples received by each of the corresponding

laboratories. Samples A to E were assayed by all laboratories (with the exception of

laboratory 35 that did not receive sample C, which is denoted by **). Where an * appears

under sample F and G in Table 6, these samples were not received by these laboratories based

on their response to the questionnaire regarding the types of samples processed routinely in

their laboratory. The mean estimates are based on the collective dataset, including data points

from undiluted and diluted samples. For table 7 qualitative datasets are presented only for

sample B and D the two proposed BKV candidate standards.

There is an overall broad range in the estimated viral load estimates across all the assay

formats and for most of the samples assayed. The log10 copies/ml range for sample A (BKV

plasmid construct) is 7.01-11.24, a spread of 4.23 log10. The log10 copies/mL range for the

first proposed BKV candidate IS (sample B) is 4.12-7.53 combining both the qualitative and

quantitative datasets. For the quantitative data alone the range is 4.38-7.53 log10 copies/mL.

The log10 spread increases from 3.15 to 3.41 when the quantitative data is combined with the

qualitative data, a fractional increase as the difference within the qualitative data alone is only

0.78 log10 copies. The corresponding liquid bulk sample (C), shows the highest log10 spread

of 4.43 (range 3.62-8.05), of all the samples assayed by quantitative analysis alone. The

difference in the quantitative mean estimate between the lyophilized and liquid equivalent for

candidate 14/202 is 0.06 log10 copies. The second proposed BKV candidate sample D shows a

log10 spread of 4.73 (3.60-8.33) when combining quantitative and qualitative estimates. The

quantitative mean estimates alone range between 5.69 and 8.33 with a log10 spread of 2.64.

The 3 qualitative datasets alone show a log10 spread of 2.59 NAT-detectable units/ mL. The

liquid equivalent of the second BKV candidate shows a mean estimate range of 4.92-8.35, a

log10 spread of 3.43. Here the difference in the quantitative mean estimate between the

lyophilized and liquid equivalent for candidate 14/212 is 0.02 log10 copies. The two clinical

samples F and G show mean estimate log10 ranges of 1.00 -4.82 and 1.24 - 4.60, equating to a

spread of 3.82 and 3.36 log10 copies respectively.

Inter-laboratory variation

The overall mean estimates and the inter-laboratory variation for both quantitative and

qualitative assays are presented in Table 8. Column “n” defines the number of datasets used to

derive each row of data. Quantitative log10 copies/mL estimates are provided for all samples,

and qualitative estimates for Sample B and D are provided in NAT detectable units/ mL. The

overall mean estimate for sample B reported by qualitative assays is 2.06 log10 lower

compared with the overall mean estimate reported by the quantitative assays for sample B

(6.62 – 4.56). For sample D this difference is 2.50 log10 copies/ mL between quantitative and

qualitative mean estimates (7.17 – 4.67). The highest standard deviation is seen with the

WHO/BS/2015.2270

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qualitative data for sample D which also has the highest geometric coefficient of variation.

This contrasts with the GCV% obtained for the qualitative estimates of sample B which is

152%, some 13 fold less. However between the quantitative mean estimates of the two

proposed BKV standards the GCV% are 344% and 306% for B and D respectively. These

represent the lowest variation of the whole dataset with the exception of the GCV% obtained

for the qualitative assessment of B. The overall mean estimates of the liquid bulk samples C

and E are within range of the lyophilized bulk mean estimates showing good agreement. For

the remaining samples, sample A shows a mean estimates of 8.97 log10 copies/ mL, sample F

2.67 log10 copies copies/ mL and sample G 2.99 log10 copies copies/ mL. However the

standard deviations of the mean estimates are high and the degree of variation between

laboratories is also reflected by the high GCV% values obtained.

Intra-laboratory variation The intra-laboratory standard deviations of the quantitative log10 copies/ mL estimates for all

of the samples for each laboratory are provided in Table 9. Within most laboratories the SD

values are low across the assayed samples. Sample F (clinical urine sample) gives the greatest

proportion of the highest SD values across all the laboratories, with 18 of the 29 laboratories

giving an SD > 0.2, which represents 62% of the dataset. For the other samples the proportion

of laboratories with SD values greater than 0.2 were considerably lower (A: 7/35, B: 10/36, C:

5/35, D: 9/36, E: 8/36 and G: 8/29). The highest standard deviation of 2.25 log10 copies/ mL is

seen with sample E for laboratory 13a. They also have the highest SD value for sample F but

the SD values across this laboratory for the remaining samples are far lower.

Comparison of laboratory reported estimates

Figures 1, 3, 5-7 show histogram representations of the quantitative laboratory mean estimates

for sample A, C, E, F and G respectively in log10 copies/ mL. For samples B and D, figures 2

and 4 show the histogram representations of the laboratory mean estimates represented in

NAT detectable units/ mL and log10 copies/ mL for qualitative and quantitative assays

respectively. Each laboratory dataset is shown by the assigned laboratory number inside each

box. Where laboratories have provided more than one dataset a further designation of “a” or

“b” alongside the laboratory number has been given. The mean estimates of each sample are

plotted as log10 copies/ mL against the frequency of the estimated mean values. In Figure 2

and 4 that represent each of the BKV candidates quantitative assay estimates are shown in the

unshaded boxes and the qualitative datasets in shaded (red) boxes. Each histogram provides a

representation of where each laboratory lies in the distribution of the total dataset for each

sample, highlighting positioning in relation to the consensus mean estimate.

For sample A whilst there is a spread of 4.23log10 in the mean estimates across the

laboratories, 15 datasets lie at the overall mean estimate, representing 43% of the total

datasets showing very good agreement (Figure 1). (Laboratory 32 is not represented in Figure

1 as their amplification targeted the NCCR gene target region which was omitted from the

plasmid construct). For sample B, 47% of datasets lie at the overall quantitative mean

estimate again showing very good agreement in almost half of the datasets (Figure 2).

Datasets at the lower end of log10 scale include data obtained from qualitative assays. Figure 3

shows the log10 mean estimates for sample C the liquid bulk equivalent of sample B. 23

datasets out of 35 sit within the two highest peaks that are around the overall quantitative

mean estimate of 6.71 log10 copies/ mL for sample C. For the second BKV candidate sample

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D a broader distribution of mean estimates is evident, compared with sample B. 23 datasets

out of 38 represented by the two peaks in the distribution, report mean estimates that are

within ~0.50 log10 copies/ mL of the overall quantitative mean estimate. The two lowest

estimations are represented by datasets obtained by qualitative assays (Figure 4). For the

liquid equivalent of the second BKV candidate (sample E) a similar two peak distribution is

evident, with 13 datasets out of 35 in agreement, reporting to within 0.50 log10 copies/ mL of

the overall quantitative mean estimate. For the clinical samples, the mean estimates exhibit a

much broader bell-shaped distribution of mean estimations, particularly for sample F (urine),

compared with samples A-E (Figure 6). For sample G (plasma) 32% of datasets are in

agreement, reporting mean estimates to within 0.2 log10 copies/ mL of the overall mean

estimate of 2.99 log10 copies/ mL (Figure 7).

Relative potency estimations

Figures 8 and 9 show the laboratory mean estimates of potency relative to the proposed

candidate standards sample B or D from quantitative assays, for each of the liquid bulk

samples (C and E). These values were obtained by taking the difference between the

laboratory derived mean estimates for sample B or D from each of the laboratory derived

estimates for sample C and E. Figure 8 shows the mean estimate difference for sample C

measured by each laboratory when expressed relative to their mean estimate for the proposed

candidate standard B. There is very good harmonization of the dataset with 66% of

laboratories in agreement after the relative potency assessment (23 of 35 datasets). 29% of the

remaining laboratories fall to within 1 log10 of the consensus after the potency assessment.

Similarly for sample D, 66% of the datasets are in agreement, and 31% of the remaining

datasets fall to within 1 log10 of the candidate standard D, showing harmonisation after the

relative potency assessment.

Figures 10 and 11 shows the mean estimate differences for sample F (clinical urine sample)

when expressed relative to the laboratory mean estimates of either candidate standard B or D

respectively. There is a reduction the log10 spread of the data from 3.82 (Figure 6) to 2.42, a

difference of 1.40 log10 when a relative potency estimation is made with the BKV candidate B.

When a relative potency assessment is made using the second BKV candidate sample D there

is a fractional change in the log10 spread of the data from 3.82 (1.40- 4.82) to 3.16 (-6.08 to -

2.92). Overall there is some harmonisation of the datasets obtained for sample F where the

harmonisation is fractionally better relative to sample D.

In Figure 12 when a relative potency assessment of sample G (clinical plasma sample) is

made with sample B there is a change from a 3.36 log10 spread (1.24 to 4.60) (Figure 7) to

1.64 log10 spread (-4.52 to -2.88). Good harmonization of the dataset is also seen when the

mean estimates are expressed relative to sample D (Figure 13). A tighter harmonisation of the

data is seen with the relative potency assessment with sample B compared with the relative

potency assessment with sample D.

As a comparison we also performed a similar analysis to see if agreement of the laboratory

mean estimates for sample F and G would improve when expressed relative to sample A, the

BKV plasmid construct. For both sample F and G, the potency assessment relative to sample

A gave minimal harmonisation of the dataset when compared with sample B and sample D

(Figure 14 and 15).

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Assessment of diluent effects

Figure 16 shows the laboratory mean estimates for sample B in log10 copies/ mL using data

obtained following the dilution of the reconstituted lyophilised candidate. Both clinical

samples and non-clinical samples were used to perform dilutions. Each diluent used is

represented by a colour/shade of grey. At the consensus plasma is represented in 9 out of 20

values. Sample D also was subject to dilution into multiple diluents and the mean estimates

from the diluted values are shown in Figure 17. At the consensus plasma is represented 12 out

of 16 values.

Since the proposed IS preparation is intended for use using multiple diluents, Figure 18 and

19 show a post-hoc Dunnett’s analysis to establish the effect, if any, on the mean estimate of

Sample B and D depending on the diluent used. The results obtained using different diluents

are compared with those obtained for the undiluted sample (reconstituted in water). All

diluents used for sample B or D are listed on the y-axis. For both candidates only PBS shows

a significant difference from the mean of the undiluted sample. Plasma is represented by the

greatest number of datasets showing the least difference from the mean of the undiluted

sample for both B and D.

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Discussion

The proposed candidate standards B (14/202) and D (14/212) comprise whole virus

preparations of BKV type 1b-1 and 1b-2 respectively. Both preparations were derived from

viral propagation in a permissive cell line. For both practical and ethical reasons, it would be

impossible to acquire sufficient volumes of each clinical matrix relevant for BKV NAT

detection, for the production of multiple formulations at the scale required for the production

of an international standard. Furthermore there would be little or no consistency between

batches of the standard. Therefore BKV viral preparations were grown from cell culture and

formulated in universal buffer for further dilution by the end user, using a diluent pertinent to

the clinical analyte under investigation. In addition the use of a whole virus preparation allows

the candidate standard to be extracted alongside clinical samples. The inclusion of the

candidate standard into the workflow of the detection assay thus allows for the standardisation

of the entire process. The BKV preparations were not subject to viral inactivation methods, in

order that viral particles remain as close to the native state as possible and potentially more

comparable to viral particles observed in a clinical specimen. This was also implemented

considering the possible changes introduced through lyophilisation of the candidate.

The production data analysis of the residual oxygen and moisture content of the lyophilised

formulations are both within the acceptable limits for long term stability. The results obtained

from the accelerated thermal degradation studies at 3 months indicate that both candidate

preparations are stable. Further analysis at future time points will provide an indication of

continued suitability for long-term use.

The viral copy values obtained for both candidates post-production, show good homogeneity

across the vial contents. The mean copies/ mL obtained for 14/202 from the in house analysis

(6.53 log10 copies/ mL) is in agreement with the both the quantitative and combined mean

estimate of this candidate (6.62 and 6.46 log10 copies/ mL) obtained by the collaborative

study data. The mean copies/ mL obtained for 14/212 from the in house analysis (6.50 log10)

is also in reasonable agreement with the combined mean estimate of this candidate (6.97

log10) obtained from the collaborative study. The overall quantitative mean estimate of the

freeze-dried material 14/202 sample B is 6.62 log10 copies/ mL (SD 0.65 and GCV 344%),

this compares well with the quantitative mean of the equivalent liquid bulk (Sample C)

6.71log10 copies/ mL SD 0.77 and GCV 494%), indicating there was no significant loss in

potency upon freeze drying of the candidate. For 14/212 (sample D) the overall quantitative

mean estimate for the freeze-dried material is 7.17 log10 copies (SD 0.61 and GCV 306%),

this compares well with the quantitative mean of the equivalent liquid bulk (Sample E)

7.21log10 copies/ mL SD 0.71 and GCV 415%), again indicating there was no significant loss

in potency upon freeze drying of the candidate.

Overall there was a good agreement between the quantitative laboratory mean estimates of the

candidate materials, with the lyophilised samples showing better agreement in estimation

compared with the liquid equivalents. Furthermore good agreement across laboratories was

also observed with the plasmid construct. The viral loads of these samples were high and

participants were advised to perform serial dilutions to identify the dilutions that fell within

the linear range of their quantitative assays. Therefore the mean estimates for the lyophilised

and the plasmid sample were obtained from multiple data points.

For the liquid equivalents of the candidate standards most data points were obtained from

undiluted samples, or where dilutions were performed they were not as comprehensive as

WHO/BS/2015.2270

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those performed particularly for the lyophilised candidates. These samples in some instances

were reported outside of the detectable limit, and only assays with a broad dynamic range

would be able to report an accurate estimation of a high titre sample without dilution. This

may explain the reduced agreement seen in the mean estimates of C and E compared with B

and D, and A.

In this study qualitative assays represent fewer than 8% of the total dataset. The mean

estimates of samples B and D were consistently lower when qualitative assays were used. For

candidate B there was a 2.09 log10 underestimation compared with the quantitative mean

estimate. For sample D this was higher with a difference of 2.52 log10 for the mean estimate

between qualitative and quantitative estimates. For a fair comparison however equal number

of datasets should be compared. Nevertheless accuracy with qualitative assays is limited by

the number of dilutions that are performed around the end point and are inherently less

definitive. For the analysis included in this study the qualitative assays are sufficient for

positive or negative determinations of viral presence at reasonable titres, but show limited

sensitivity below 3.60 log10 NAT detectable units/ mL.

As BKV NAT detection assays are relied upon for the monitoring of BKV reactivation in

urine and plasma samples of transplantation patients under immunosuppressive treatment, we

included patient samples in our study panel for analysis alongside the candidate materials. We

obtained 3ml aliquots each of urine and plasma which was diluted further in order to obtain a

volume sufficient for the total number of study participants and the volumes required for each

individual extraction method. The overall mean estimate of the urine sample was 2.67 log10

copies/ mL and 2.99 log10 copies/ mL for the plasma sample. The mean estimate agreement

across laboratories for these samples showed considerable variability with a very broad

distribution of estimates. This may be due in part to the reduced sensitivity of assays at the

lower detection range compared with higher viral loads present in the other samples. The

urine sample showed greater variability across assays with a higher SD and GCV% compared

with the plasma sample. Only negligible harmonisation of potency estimates of this sample

was seen with either of the two candidate standards. A clearer difference in harmonisation

was observable with the plasma sample which may be related to the difference in detection

efficacy across matrices. It is noteworthy that the clinical samples F and G were not

genotyped and the variability in the reported data between laboratories may also be

attributable, to mismatches in primer annealing if the genotype in the analyte is not

comparable to the sequence used for assay development as highlighted by Randhawa et al

[11]. It has been reported that since assays are designed predominantly using Subtype 1 the

viral loads for BKV subtypes IV and III are notably underestimated due to reduced sensitivity

on account of primer pair and probe mismatching in regions of subtype polymorphisms [4, 9,

11].

The agreement between laboratories for samples C and E was markedly improved when the

potencies for these samples were expressed relative to the candidate standard (Sample B or D),

demonstrating the suitability of the candidates to improve assay standardisation. However a

comparable improvement in agreement was not observed with the clinical urine sample F.

This could be attributable to the lower limits of quantification for some of the assays with the

lower titre sample. This could also be in part due the sample matrix. However better

harmonisation of estimates was seen with sample G relative to the proposed candidates.

The plasmid (sample A) was unable to enhance agreement across laboratories for sample F or

for sample G unlike the candidate materials. As the plasmid is added directly to the

WHO/BS/2015.2270

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amplification reaction without extraction, the extraction step is not controlled for which may

account for the limited harmonisation of the dataset. As clinical materials undergo extraction,

this step must be controlled for especially considering the number of various extractions

methods included in this study. A similar observation was also made in the WHO ECBS

report for HCMV [10].

This collaborative study has been able to provide some preliminary information on the

potential commutability of the proposed candidate materials. This information came from

participant dilutions of the candidate materials into the various matrices tested. The majority

of laboratories used plasma for the dilution of each candidate (n=24) followed by urine (n=

14) and 5 datasets were obtained using whole blood. Therefore any analysis is skewed in

favour of plasma. In figure 16 the consensus mean estimate is represented mainly by plasma

diluted estimates as expected, however in addition, it also includes whole blood and urine as

well as non-clinical diluents. Laboratory 27 performed analysis of the two candidates in urine

whole blood and plasma. For sample B the log10 copies/ml mean estimates in urine is lower

compared with whole blood and plasma, such that (urine < whole blood < plasma) (Figure

16). This trend is also evident for sample D (Figure 17). Laboratory 16 also used multiple

diluents, urine, plasma, whole blood and CSF. Their data shows closer agreement between the

various matrices tested, where the log10 copies/mL mean estimates for sample B exhibited

good agreement, suggesting that there is good commutability of this standard in different

matrices in their assay (Figure 16). For candidate D there was good agreement between the

log10 copies/mL estimations using urine, CSF and whole blood. However plasma exhibited a

lower estimation in log10 copies/mL for sample D.

The comparison of diluent effects using Dunnett Test analysis (Figure 18 and 19), show that

the mean estimates derived from the candidate dilutions made using plasma do not differ from

the estimations obtained using the means estimates obtained from the undiluted estimates,

suggesting there is no diluent effect on the obtained mean estimates. The mean estimates

obtained from dilutions using urine also did not differ significantly from undiluted estimates.

For the remaining samples fewer datasets were used and interpretation should be reserved for

a more robust analysis. For PBS, the data from this model suggests that the mean value

obtained using PBS as a diluent was significantly different from the control (undiluted) mean.

However this was based on only1datasets where the undiluted sample was underestimated

since it was out of the range of the laboratories assay. Further controlled commutability

assessments should be performed to test this empirically for all clinically relevant diluents. In

order to address this issue fully a larger study with multiple low, medium and high clinical

samples in equal numbers with an equal number of participants should be conducted in order

to draw robust conclusions on the commutability of the proposed standard preparations.

This multicentre collaborative study included a good number of laboratories with a wide

geographical representation. The study group provided a good representation of the variety of

end-users of BKV NAT assays. It also represents a wide range of assays methodologies in use.

The details supplied by participants on the assay methodologies highlight the heterogeneity of

the method combinations for both extraction and amplification of BKV NAT-detection assays,

where no two methods of the 38 datasets were actually alike. The standard deviations

obtained from the intra-laboratory analysis show good consistency within each laboratory,

indicative of good single assay validation. It has been noted that the mean laboratory

estimates returned for the candidate materials are surprisingly uniform despite the absence of

a primary reference standard (personal communications at SoGAT meeting 2015). This may

WHO/BS/2015.2270

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in part be due to the proportion of commercial assays available and represented in the BKV

collaborative study which outnumbered the laboratory developed methods by 18 to 15.

Nevertheless the inter-laboratory mean estimates of all the study samples do still show broad

variation illustrating limited comparability between all laboratories which justifies the need

for standardisation.

The results of the study demonstrate that either of the two proposed candidate standards

NIBSC code 14/202 and 14/212, would be suitable for use as a standards for the

quantification of BKV DNA detection assays. Using Sanger sequencing analysis candidate

14/202 has been identified as subgroup Ib-1, which is most common in South-east Asia,

whereas 14/212 has been matched to subgroup Ib-2 which is the most prevalent sub-group in

Europe. Considering the genotyping data we have obtained for both candidates we would

recommend 14/212 as the most suitable for use as the 1st International Standard based on

relevance to current IVD kits and overall geographical coverage. In light of the findings of

this collaborative study we would recommend a value of 6.99 log10 rounded up to 7.0 log10

International Units/ mL to be assigned. This potency assignment would represent the range of

NAT assays in use for BKV determination. Alternatively the potency assigned could be based

on the quantitative data alone, and a value of 7.2 log10 IU/mL would be recommended.

Sample Assay n Mean SD GCV D Qualitative 3 4.67 1.33 2034%

Quantitative 35 7.19 0.63 325%

Combined 38 6.99 0.96 819%

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Recommendation

It is proposed that the candidate standard (NIBSC code 14/212) is established as the 1st WHO

International standard for BKV DNA for nucleic acid amplification technique (NAT)-based

assays with an assigned potency of 7.0 log10 International Units when reconstituted in 1 mL of

nuclease-free water. The proposed standard is intended for use by IVD manufactures for kit

calibration and for use by clinical, reference and research laboratories for the calibration of

secondary reference reagents used in routine NAT-assays for BKV detection. A draft

instruction for use (IFU) for the product is included in Appendix V.

Collaborative study participant comments

There were no disagreements with the suitability of the candidate standard (NIBSC code

14/212) to serve as the 1st WHO International Standard for BKV nucleic acid amplification

technique (NAT)-based assays. The majority of comments suggested typographical errors and

corrections which have been implemented into the revised document. Specific comments

from participants are as follows:

Participant 7

Discuss the impact of genomic variability in the real world as both standards are genotype 1b.

The establishment of an IS with genotype 1 would of course would only improve the

standardisation of assays targeted to this subtype. Subtype I is predominant in most

geographical regions with a prevalence of 46-82% throughout the world, against which most

NAT assays have been developed. However the impact of genetic variability is of notable

concern considering the underestimation of viral loads when making clinical decisions for

patients with genotypes Ic, II, III and IV, as highlighted by Randhawa et al [11].

They and others have suggested that assay design could be improved to detect relatively

uncommon genotypes by targeting alternate more conserved regions or indeed the

employment of degenerate primers, or a multiplex approach. Alternatively perhaps like HIV-1

a subtype panel maybe warranted.

Participant 9

Participant 9 noted the absence of figure legends, which have now been added (page 30).

Participant 9 comments that the nomenclature for the IS candidates in the introduction is not

clear. “The two proposed candidates are named in different ways, i.e. the first and the second,

or the donated viral stock and the NIBSC BKV stock. Two clear codes or two clear names for

both the candidates should be given since the beginning and then each candidate always

called with the same name.”

The following has been added to the end of the introduction on page 4 for clarification.

The current study describes the preparation and evaluation of two BKV candidate materials,

intended for use as primary international standards for NAT-detection assays. They are

referred to in the text by the assigned NIBSC codes 14/202 and 14/212, as well as by the

alphabetic code given as part of the collaborative study test panel, Sample B and D

respectively.

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Care has also been taken to keep this nomenclature consistent throughout the remaining

document.

Participants 11 and 25

Corrections have been made to the data provided by participants 11 and 25.

These participants both queried the derivation of the values presented in the statistical

analyses. Therefore the following description has been provided to clarify the statistical

methodology used to calculate the results presented in the tables.

First each result was corrected up for any dilution factor. Then a mean was calculated across

the replicates for each vial. Then means of the vial means were calculated to give a result for

each assay. Finally, means and standard deviations (as well as differences) are calculated on

the assay results to give the values listed in the tables.

Additional data corresponding to the histogram plots (Figure 8-17) has also been added into

Appendix IV.

Participant 14

The assay used for the study by participant 14 was launched as a CE-IVD assay during the

time the collaborative study experiments were performed. They have requested the following

details be added to the section “summary of assay methodologies”; IRIDICA Viral IC Assay

Reagent Kit (List No. 08N24-010) manufactured by Abbott Molecular Inc. (page 11).

Participant 34

Participant 34 was also interested in BKV genotyping and asked if all samples were

genotyped and asked if any differences in quantitative assessment was observed based on the

genotype tested. Only the candidate materials 14/202 and 14/212 were genotyped.

They also asked if any grouping of participating laboratories relating to assay types used was

performed, for example commercial vs. in-house developed. This analysis has not been

performed. The collaborative study was primarily conducted to evaluate and assign a potency

unit to the proposed candidate material.

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Acknowledgements

We gratefully acknowledge the significant contributions of all the collaborative study

participants. We would also like to extend our gratitude to Dr JL Murk, University Medical

Centre, Utrecht, The Netherlands for the provision of materials used for the preparation of the

candidate standard. We would also like to sincerely thank Dr P Vallone & Dr JL Harenza of

the National Institute of Standards and Technology, USA for the donation of the BKV

plasmid construct. We also thank Dr CB Christiansen of Rigshospitalet Department Clinical

Microbiology, Denmark for the kind donation of clinical samples.

WHO/BS/2015.2270

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sequences: Implications for molecular diagnostic laboratories. J Med Virol. 2008

Oct;80(10):1850-7.

5] Zheng HY, Nishimoto Y, Chen Q, Hasegawa M, Zhong S, Ikegaya H, Ohno N,

Sugimoto C, Takasaka T, Kitamura T, Yogo Y. Relationships between BK virus

lineages and human populations. Microbes Infect. 2007 Feb;9(2):204-13.

6] Zhong S, Randhawa PS, Ikegaya H, Chen Q, Zheng HY, Suzuki M, Takeuchi T, Shibuya A,

Kitamura T, Yogo Y. Distribution patterns of BK polyomavirus (BKV) subtypes and

subgroups in American, European and Asian populations suggest co-migration of BKV and

the human race. J Gen Virol. 2009 Jan; 90 (Pt 1):144-52.

7] Babel N, Volk HD, Reinke P. BK polyomavirus infection and nephropathy: the

virus-immune system interplay. Nat Rev Nephrol. 2011 May 24;7(7):399-406.

8] Dropulic LK, Jones RJ. Polyomavirus BK infection in blood and marrow transplant

recipients. Bone Marrow Transplant. 2008 Jan; 41(1):11-8.

[9] Hoffman NG, Cook L, Atienza EE, Limaye AP, Jerome KR. Marked variability of BK

virus load measurement using quantitative real-time PCR among commonly used assays. J

Clin Microbiol. 2008 Aug; 46(8):2671-80.

[10] Fryer JF, Heath AB, Anderson R, Minor PD: Collaborative Study Group: Collaborative

Study to Evaluate the Proposed 1st WHO International Standard for Human Cytomegalovirus

(HCMV) for Nucleic Acid Amplification (NAT)-based Assays. In WHO ECBS Report 2010,

WHO/BS/10.2138. Geneva: WHO Press; 2010.

[11] Randhawa P, Kant J, Shapiro R, Tan H, Basu A, Luo C. Impact of genomic sequence

variability on quantitative PCR assays for diagnosis of polyomavirus BK infection. J Clin

Microbiol. 2011 Dec;49(12):4072-6.

WHO/BS/2015.2270

Page 24

Tables and Figures:

Table 1: Study sample details

Sample BKV Sample ID

Estimated viral log10

copies/mL

A BKV plasmid construct 9.18 -9.26

B

Proposed BKV candidate IS

14/202

6.73

C 14/202 Liquid bulk 6.69

D

Proposed BKV candidate IS

14/212

6.75

E 14/212 Liquid bulk 6.75

F Urine sample (BMT patient) 3.91

G Plasma sample (BMT patient) 3.47

Table 2: Production summary for the candidate standard (Sample B)

NIBSC code 14/202

Product name BK Virus

Dates of processing Filling: 20/10/14

Lyophilisation: 20/10/14- 23/10/14

Sealing: 23/10/14

Presentation

Freeze-dried preparation in 5ml screw-cap glass

vial

Appearance Well-formed robust cake

No of vials filled 4229

Mean fill weight (g) 1.0074

CV of fill weight (%) 0.23 (n=140)

Mean residual moisture (%) 0.66 (n=12)

CV of residual moisture (%) 12.3

Mean of Oxygen content (%) 0.82 (n=12)

CV of Oxygen content (%) 8.65

No. of vials available to WHO 4108

WHO/BS/2015.2270

Page 25

Table 3: Production summary for the candidate standard (Sample D)

NIBSC code 14/212

Product name BK Virus

Dates of processing Filling: 10/11/14

Lyophilisation: 10/11/14-13/11/14

Sealing: 13/11/14

Presentation

Freeze-dried preparation in 5ml screw-cap glass

vial

Appearance Well-formed robust cake

No of vials filled 4219

Mean fill weight (g) 1.0075

CV of fill weight (%) 0.27 (n=142)

Mean residual moisture (%) 0.91 (n=12)

CV of residual moisture (%) 8.6

Mean of Oxygen content (%) 0.75 (n=12)

CV of Oxygen content (%) 14.33

No. of vials available to WHO 4092

Table 4: Viral potency analysis of lyophilised candidate

Lyophilised Candidate Average Log10 copies/ mL

14/202 14/212

Vial 1 6.82 6.49

Vial 2 6.48 6.53

Vial 3 6.52 6.54

Vial 4 6.46 6.54

Vial 5 6.46 6.49

Vial 6 6.44 6.50

Vial 7 6.47 6.51

Vial 8 6.43 6.51

Vial 9 6.51 6.54

Vial 10 6.46 6.54

Vial 11 6.49 6.56

Vial 12 6.44 6.55

Overall Av Log10 copies/

mL

6.53 6.50

SD 0.029 0.105

CV (%) 4.4 1.6

WHO/BS/2015.2270

Page 26

Table 5: Stability of BKV candidate materials

Temperature

(°C)

Candidate 14/202 Difference in log10

Mean log10 copies/mL copies/mL from -20°C

at 3 months baseline sample

-70 6.56

-20 6.57

+4 6.64 0.07

+20 6.59 0.02

+37 6.64 0.07

+45 6.63 0.06

Temperature

(°C)

Candidate 14/212 Difference in log10

Mean log10 copies/mL copies/mL from -20°C

at 3 months baseline sample

-70 6.63

-20 6.67

+4 6.67 0

+20 6.65 -0.02

+37 6.80 0.13

+45 6.81 0.14

WHO/BS/2015.2270

Page 27

Table 6: Laboratory Mean Estimates from Quantitative Assays (log10

copies/ml)

Lab Sample A Sample B Sample C Sample D Sample E Sample F Sample G

1 7.54 6.51 6.56 7.10 7.07 * 3.18

2 8.62 6.78 6.67 7.25 7.48 * *

3 8.68 6.72 6.91 6.86 7.53 2.42 *

4 9.78 7.29 7.40 8.13 8.05 * 3.66

5 8.88 6.69 6.80 7.16 7.36 2.39 3.16

7 10.56 7.48 7.40 8.02 7.96 4.30 4.60

9 11.24 7.32 8.05 7.52 8.17 3.65 *

10a 8.82 6.59 6.77 7.24 7.28 2.84 3.24

10b 8.79 6.35 6.46 6.86 6.93 2.74 3.12

11 9.69 7.22 5.70 7.47 5.62 * *

12 9.05 6.61 6.64 7.53 6.77 * 2.50

13a 8.80 6.44 3.06 7.31 5.29 4.03 3.19

16 7.49 5.03 5.21 5.84 5.99 1.00 *

17 7.01 4.38 3.62 5.69 4.92 1.45 1.24

18 9.17 6.43 6.46 6.76 6.64 1.87 2.64

19 9.20 6.70 6.96 7.56 7.70 3.01 3.28

20 8.58 6.61 6.61 7.39 7.29 1.86 2.85

21a 8.90 6.90 6.88 7.48 7.51 3.19 3.37

21b 9.26 6.78 6.68 7.30 7.36 3.04 3.28

22 8.66 6.39 6.58 7.17 7.28 * 2.84

23 8.55 6.34 6.41 7.01 6.97 3.13 3.15

24 9.24 6.01 6.31 6.13 6.13 1.72 *

25 9.21 7.32 7.41 7.68 7.62 3.36 3.28

26 9.04 6.91 6.92 7.39 7.44 2.35 *

27a 8.85 6.51 6.95 6.73 7.23 2.08 2.42

27b 8.86 6.36 6.97 6.63 7.19 1.88 2.41

27c 8.87 6.41 6.95 6.65 7.22 2.11 2.56

27d 8.89 6.35 6.98 6.64 7.23 1.98 2.31

28 9.36 6.79 6.90 7.57 7.53 2.56 2.59

30 9.42 7.26 7.34 7.89 7.93 3.70 3.88

31 10.41 7.53 7.42 8.19 8.19 4.82 3.87

32 ND 5.57 5.85 6.76 7.29 * 1.36

33 7.36 6.97 6.98 7.29 7.18 2.19 2.45

34 9.71 7.40 7.76 8.33 8.35 2.26 3.86

35 8.59 6.75 ** 6.87 7.17 2.92 3.04

36 8.60 6.61 6.71 6.79 6.74 3.88 3.52 ND not detected. * Refers to samples “not tested” as they were not part of the test panel for that

laboratory. ** Refers to “not received” as insufficient vials were remaining of this sample.

WHO/BS/2015.2270

Page 28

Table 7: Laboratory Mean Estimates from Qualitative Assays (NAT-detectable

units/ml)

Lab Sample B Sample D

13b 4.68 6.19

14 4.90 4.26

15 4.12 3.60

Table 8: Overall Mean Estimates and Inter-Laboratory Variation (log10 copies/ml for

quantitative or NAT-detectable units/ml for qualitative assays)

Sample Assay n Mean SD GCV Min Max

A Quantitative 34 8.97 0.85 607% 7.01 11.24

B Qualitative 3 4.56 0.40 152% 4.12 4.90

Quantitative 35 6.62 0.65 344% 4.38 7.53

Combined 38 6.46 0.84 596% 4.12 7.53

C Quantitative 34 6.71 0.77 494% 3.62 8.05

D Qualitative 3 4.67 1.33 2034% 3.60 6.19

Quantitative 35 7.17 0.61 306% 5.69 8.33

Combined 38 6.97 0.95 787% 3.60 8.33

E Quantitative 35 7.21 0.71 415% 4.92 8.35

F Quantitative 28 2.67 0.88 660% 1.00 4.82

G Quantitative 28 2.99 0.72 427% 1.24 4.60

Excluding laboratory 13a

WHO/BS/2015.2270

Page 29

Table 9: Intra-Laboratory standard deviation of log10 copies/ml quantitative assays

Lab Sample A Sample B Sample C Sample D Sample E Sample F Sample G

1 0.63 0.11 0.10 0.18 0.30 * 0.02

2 0.32 0.08 0.18 0.26 0.02 * *

3 0.38 0.21 0.10 0.69 0.12 0.11 *

4 0.01 0.03 0.06 0.10 0.06 * 0.06

5 0.49 0.13 0.16 0.23 0.04 0.17 0.32

7 0.09 0.46 0.19 0.47 0.30 0.74 0.44

9 0.06 0.14 0.07 0.12 0.16 0.60

10a 0.03 0.02 0.05 0.01 0.05 0.81 0.06

10b 0.03 0.03 0.03 0.00 0.09 0.76 0.05

11 0.05 0.25 0.39 0.20 0.56 * *

12 0.28 0.17 0.29 0.40 0.05 * 0.23

13a 0.18 0.31 0.18 0.42 2.25 1.60 0.02

16 0.16 0.02 0.04 0.01 0.02 0.30 *

17 0.01 0.35 0.27 0.91 0.08 0.45 0.11

18 0.03 0.09 0.04 0.04 0.10 0.39 0.07

19 0.03 0.21 0.07 0.05 0.10 0.27 0.17

20 0.67 0.05 0.12 0.08 0.29 0.07 0.35

21a 0.11 0.01 0.11 0.05 0.16 0.02 0.02

21b 0.04 0.16 0.01 0.03 0.05 0.55 0.23

22 0.14 0.21 0.14 0.21 0.14 * 0.15

23 0.04 0.08 0.12 0.12 0.20 0.09 0.04

24 0.05 0.38 0.19 0.17 0.70 0.00 *

25 0.02 0.07 0.02 0.02 0.11 0.13 0.04

26 0.14 0.10 0.06 0.18 0.26 0.22 *

27a 0.08 0.02 0.15 0.09 0.16 0.08 0.11

27b 0.04 0.02 0.02 0.03 0.05 0.22 0.13

27c 0.02 0.06 0.05 0.04 0.06 0.31 0.19

27d 0.04 0.06 0.05 0.07 0.08 0.44 0.23

28 0.14 0.08 0.19 0.08 0.05 0.26 0.20

30 0.31 0.08 0.05 0.01 0.05 0.09 0.12

31 0.15 0.20 0.13 0.32 0.05 0.21 0.08

32 ND 0.39 0.21 0.16 0.17 * 0.03

33 0.02 0.01 0.01 0.01 0.17 0.35 0.09

34 0.09 0.32 0.17 0.08 0.13 0.43 0.32

35 0.16 0.06 ** 0.03 0.01 0.06 0.09

36 0.18 0.14 0.25 0.15 0.21 0.13 0.34 ND not detected. * Refers to samples “not tested” as they were not part of the test panel for that

laboratory. ** Refers to “not received” as insufficient vials were remaining of this sample.

WHO/BS/2015.2270

Page 30

Figure legends

Figure 1-7:

Individual laboratory mean estimates represented by log10 copies/ mL samples A-G obtained

using quantitative analysis. For Figure 2 and 4 results are presented for the qualitative datasets

as NAT detectable units/ mL. The qualitative assays are shaded. Each box represents the

mean estimate obtained from each laboratory based on all the returned values within each

dataset (mean estimation from neat and diluted samples). Each box is labelled with the

laboratory code number.

Figures 8-15:

The individual laboratory mean estimates of sample C or E, F and G expressed as the

difference in log10 copies/mL relative to the candidate standard Sample B (Figures 8, 10, 12),

or to candidate standard D (Figures 9, 11, 13), or to the BKV plasmid construct, sample A

(Figures 14 and 16). Each box is labelled with the laboratory code number. Only quantitative

data is shown. (Relative potency estimate values for each figure are included in Appendix IV)

Figure 16 and 17: Laboratory Mean Estimates for Sample B and D respectively in log10

copies/ml and NAT detectable units/ mL using diluted data only.

Individual laboratory mean estimates for sample B (Figure 16) and D (Figure 17), both

quantitative and qualitative datasets are shown. The boxes are shaded to represent the matrix

used for dilution of each sample. Each box represents the mean estimate obtained from each

laboratory based on all the returned values within each dataset (mean estimation from diluted

samples only). Each box is labelled with the laboratory code number.

Figure 18 and 19: Comparison of diluent effects using Dunnett Test

The Dunnett's Test is used in ANOVA to create confidence intervals for differences between

the mean of sample B (Figure 18) or D (Figure 19) diluted into the various diluents and the

mean of the undiluted sample. If an interval contains zero, then there is no significant

difference between the two means under comparison. Each evaluation was derived from the

following number of datasets: Urine= 14, Plasma = 24, Blood = 5, Water = 4, CSF = 1, PBS =

2, FCS=1. CSF (Cerebrospinal Fluid), PBS (Phosphate buffered saline), FCS (Foetal Calf

serum)

WHO/BS/2015.2270

Page 31

Figure 1: Laboratory Mean Estimates for Sample A in log10 copies/ml

N

um

ber

of Labora

tories

0

2

4

6

8

10

12

14

16

Log10 copies/ml

5 6 7 8 9 10 11 12 13

17 1

16

33

2

3

20

22

23

35

36

5

10a

10b

12

13a

18

19

21a

24

25

26

27a

27b

27c

27d

11

21b

28

30

34

4 7

31

9

Figure 2: Laboratory Mean Estimates for Sample B in log10 copies/ml

Num

ber

of Labora

tories

0

2

4

6

8

10

12

14

16

18

NAT detectable units/ml (Qualitative assays) or Log10 copies/ml (Quantitative assays)

2 3 4 5 6 7 8 9 10

15 13b

17

14

16

32 24 1

3

5

10a

10b

12

13a

18

19

20

22

23

27a

27b

27c

27d

35

36

2

11

21a

21b

26

28

33

4

7

9

25

30

31

34

Quantitative Assays Qualitative Assays

WHO/BS/2015.2270

Page 32

Figure 3: Laboratory Mean Estimates for Sample C in log10 copies/ml

Num

ber

of Labora

tories

0

2

4

6

8

10

12

14

Log10 copies/ml

2 3 4 5 6 7 8 9 10

13a 17 16 11 32 1

2

10b

12

18

20

21b

22

23

24

36

3

5

10a

19

21a

26

27a

27b

27c

27d

28

33

4

7

25

30

31

9

34

Figure 4: Laboratory Mean Estimates for Sample D in log10 copies/ml

Num

ber

of Labora

tories

0

2

4

6

8

10

12

14

NAT detectable units/ml (Qualitative assays) or Log10 copies/ml (Quantitative assays)

2 3 4 5 6 7 8 9 10

15 14 17 13b

16

24

27a

27b

27c

27d

1

3

5

10a

10b

18

22

23

32

35

36

2

9

11

12

13a

19

20

21a

21b

25

26

28

33

4

7

30

31

34

Quantitative Assays Qualitative Assays

WHO/BS/2015.2270

Page 33

Figure 5: Laboratory Mean Estimates for Sample E in log10 copies/ml

N

um

ber

of Labora

tories

0

2

4

6

8

10

12

14

Log10 copies/ml

2 3 4 5 6 7 8 9 10

17 11

13a

16

24

18

36

1

10b

12

23

27a

27b

27c

27d

33

35

2

3

5

10a

19

20

21a

21b

22

25

26

28

32

4

7

9

30

31

34

Figure 6: Laboratory Mean Estimates for Sample F in log10 copies/ml

Num

ber

of Labora

tories

0

2

4

6

8

10

Log10 copies/ml

0 1 2 3 4 5 6 7 8

16 17

24

18

20

27a

27b

27c

27d

33

3

5

10b

26

28

34

10a

19

21a

21b

23

35

9

25

30

13a

36

7 31

WHO/BS/2015.2270

Page 34

Figure 7: Laboratory Mean Estimates for Sample G in log10 copies/ml

Num

ber

of Labora

tories

0

2

4

6

8

10

Log10 copies/ml

0 1 2 3 4 5 6 7 8

17 32 12

18

27a

27b

27c

27d

28

33

1

5

10a

10b

13a

20

22

23

35

4

19

21a

21b

25

36

30

31

34

7

WHO/BS/2015.2270

Page 35

Figure 8: Laboratory Mean Estimates difference for Sample C relative to Sample B (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

Difference in Log10 copies/ml

-4 -3 -2 -1 0 1 2 3 4

13a 11 17 1 2 3 4 5 710a10b 12 16 18 2021a21b 22 23 25 26 28 30 31 33 36

9 19 2427a27b27c27d 32 34

Figure 9: Laboratory Mean Estimates difference for Sample E relative to Sample D (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

Difference in Log10 copies/ml

-4 -3 -2 -1 0 1 2 3 4

1113a

12 17

1 4 5 710a10b 16 18 19 2021a21b 22 23 24 25 26 28 30 31 33 34 36

2 3 927a27b27c27d 32 35

WHO/BS/2015.2270

Page 36

Figure 10: Laboratory Mean Estimates difference for Sample F relative to Sample B (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

Difference in Log10 copies/ml

-8 -7 -6 -5 -4 -3 -2 -1 0

20

33

34

3

5

18

24

26

27a

27b

27c

27d

16

25

28

35

9

10a

10b

19

21a

21b

30

7

17

23

13a

31

36

Figure 11: Laboratory Mean Estimates difference for Sample F relative to Sample D (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

Difference in Log10 copies/ml

-8 -7 -6 -5 -4 -3 -2 -1 0

34 20 5

16

18

26

27b

28

33

3

10a

19

21a

21b

24

25

27a

27c

27d

9

10b

17

23

30

35

7

13a

31

36

WHO/BS/2015.2270

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Figure 12: Laboratory Mean Estimates difference for Sample G relative to Sample B (in

log10 copies/ml) N

um

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Difference in Log10 copies/ml

-8 -7 -6 -5 -4 -3 -2 -1 0

33 12

18

20

25

27a

27b

27c

27d

28

32

1

4

5

10a

13a

19

21a

21b

22

30

31

34

35

7

10b

17

23

36

Figure 13: Laboratory Mean Estimates difference for Sample G relative to Sample D (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Difference in Log10 copies/ml

-8 -7 -6 -5 -4 -3 -2 -1 0

32 12

28

33

4

17

19

20

22

25

27a

27d

31

34

1

5

10a

13a

18

21a

21b

23

27b

27c

30

35

7

10b

36

WHO/BS/2015.2270

Page 38

Figure 14: Laboratory Mean Estimates difference for Sample F relative to Sample A (in

log10 copies/ml)

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

Difference in Log10 copies/ml

-10 -9 -8 -7 -6 -5 -4 -3 -2

9

18

24

34

27a

27b

27c

27d

28

3

5

7

16

20

26

10a

10b

19

21b

25

13a

17

21a

23

30

31

35

33 36

Figure 15: Laboratory Mean Estimates difference for Sample G relative to Sample A (in

log10 copies/ml

Num

ber

of Labora

tories

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

Difference in Log10 copies/ml

-10 -9 -8 -7 -6 -5 -4 -3 -2

28 12

18

27a

27b

27c

27d

31

4

7

17

19

21b

22

25

34

5

10a

10b

13a

20

21a

23

30

35

33

36

1

WHO/BS/2015.2270

Page 39

Figure 16: Laboratory Mean Estimates for Sample B in log10 copies/ml,

using diluted data only.

Num

ber

of Labora

tories

0

2

4

6

8

10

12

14

16

18

Log10 copies/ml

2 3 4 5 6 7 8 9 10

15 13b

17

14

16

16

16

16

32 24

27a

27b

27c

27d

27d

1

3

5

10a

10b

12

13a

18

18

19

20

22

23

27a

27b

27c

35

36

2

9

21a

21b

26

27a

27b

27c

27d

28

33

4

7

11

25

30

31

34

Urine Plasma Blood Water CSF PBS FCS

WHO/BS/2015.2270

Page 40

Figure 17: Laboratory Mean Estimates for Sample D in log10 copies/ml,

using diluted data only.

Num

ber

of Labora

tories

0

2

4

6

8

10

12

14

Log10 copies/ml

2 3 4 5 6 7 8 9 10

15 14 16 13b

16

16

16

17

24

27b

27c

18

27a

27a

27b

27c

27d

27d

32

1

3

5

10a

10b

18

22

23

27a

27b

27c

27d

35

36

2

9

11

12

13a

19

20

21a

21b

25

26

28

33

4

7

30

31

34

Urine Plasma Blood Water CSF PBS FCS

WHO/BS/2015.2270

Page 41

Figure 18: Comparison of diluent effects using Dunnett Test for Sample B

Figure 19: Comparison of diluent effects using Dunnett Test for Sample D

WHO/BS/2015.2270

Page 42

Appendix 1: List of Study Participants

Australia Dr Seweryn Bialasiewicz Sir Albert Sakzewski Virus Research Centre

Queensland

Belgium Dr. Marijke Reynders AZ Sint-Jan Brugge-Oostende AV Campus Sint-Jan

Laboratory Medicine (6th Floor) Molecular Microbiology

BRUGGE

Canada Dr Jaclyn Ugulini Norgen Biotek Corp

Ontario

Czech Republic Dr Martina Salakova Department of Experimental Virology

Institute of Hematology and Blood Transfusion

128 00 Prague 1

Czech Republic Dr Jana Zdychova PLM-OKI/IKEM

140 21 Prague 4

Denmark Dr Claus Bohn Christiansen Dept. Clinical Microbiology

Rigshospitalet

Copenhagen

France Dr David Boutolleau Virology Department

University Hospital Pitie-Salpetriere

Paris

France Dr Céline Bressollette/ Dr Marina Illiaquer Nantes University Hospital

Laboratoire de Virologie

Nantes

France Prof. Samira Fafi-Kremer Hôpitaux Universitaires de Strasbourg

Laboratoire de Virologie

Strasbourg

France Dr Catherine Mengelle/ Dr Jean-Michel Mansuy Department of Virology

Federative Institute of Biology

Toulouse

France Dr Matthieu Vignoles BioMerieux

Verniolle Site, Molecular Biology Unit

Verniolle

Germany Dr Karin Rottengatter/ Dr Waldemar Fischer Altona Diagnostics GmbH

Hamburg

Germany Dr Steffi Silling Nationales Referenzzentrum für Papillom- und Polyomaviren

Institut für Virologie

Köln

India Dr Rajesh Kannangai Department Of Clinical Virology

Christian Medical College

Tamil Nadu

Italy Dr Mauro G. Tognon University of Ferrara

Cell Biology and Molecular Genetics

Ferrara

Italy Dr Christiana Olivo ELITetechGroup SpA

Torino

Netherlands Prof. H.G.M Niesters/ Lilli Rurenga-Gard University Medical Center Groningen (UMCG)

Department of Medical Microbiology. Division Of Clinical Virology

Groningen

Netherlands Dr Rob Schuurman University Medical Center Utrecht

Department of Virology

Utrecht

Spain Dr Juan E. Echevarría National Center of Microbiology

Institute of Health Carlos III

Madrid

Tunisia Dr Mounir Trimeche Department of Pathology

CHU Farhat Hached of Sousse

Instituion Participant Country

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Turkey Prof. Dr. Dilek Colak/ Dr Derya Mutlu Akdeniz University Hospital Central Microbiology Laboratory

Medical Microbiology Department

Antalya

Turkey Dr Elif Akyuz Anatolia Tani ve Biyoteknoloji Urunleri Ar-Ge San.Tic. A.S.

Istanbul

UK Dr Elaine McCulloch QCMD

West of Scotland Science Park

Glasgow

UK Dr Anna Blacha QIAGEN Manchester Ltd

Manchester

UK Dr Sheila Govind Division of Virology

National Institute for Biological Standards and Control

South Mimms

USA Dr Kathleen Stellrecht/ Mr Shafiq Butt Albany Medical Center

Albany, New York

USA Dr Kristin S Lowery AthoGen/Ibis Biosciences

Carlsbad, California

USA Dr Midori Mitui/ Dr Damon Lacey Children's Medical Center

Medical District Drive

Dallas, Texas

USA Dr Mayur S Ramesh Henry Ford Health Systems, Clinical Microbiology Laboratory

Henry Ford Hospital

Detroit, Michigan

USA Dr Jianli Dong Sealy Center for Cancer Biology

University of Texas Medical Branch

Galveston, Texas

USA Dr Kelly Homb Luminex Corporation

Madison, Wisconsin

USA Dr Parmjeet Randhawa Division of Transplantation Pathology

UPMC-Montefiore Hospital

Pittsburgh, Pennsylvania

USA Dr Angela Caliendo/ Dr Soya Sam The Miriam Hospital

Caliendo Molecular Lab

Rhode Island

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Appendix II: Collaborative study Questionnaire

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Appendix III: Collaborative Study Protocol

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Appendix IV

Laboratory Estimates of Relative Potency from Quantitative Assays

(Difference in log10 copies/ml)

Lab C - B E - D F - B F - D G - B G - D F - A G - A

1 0.03 -0.09 * * -3.38 -3.95 * -3.92

2 -0.16 0.30 * * * * * *

3 0.18 0.67 -4.31 -4.44 * * -6.27 *

4 0.11 -0.08 * * -3.63 -4.47 * -6.12

5 0.11 0.20 -4.31 -4.77 -3.53 -3.99 -6.49 -5.71

7 -0.08 -0.06 -3.18 -3.72 -2.88 -3.43 -6.26 -5.96

9 0.73 0.64 -3.66 -3.87 * * -7.59 *

10a 0.19 0.05 -3.75 -4.40 -3.34 -3.99 -5.99 -5.58

10b 0.11 0.07 -3.61 -4.13 -3.23 -3.75 -6.06 -5.67

11 -1.52 -1.85 * * * * * *

12 0.10 -0.98 * * -4.11 -5.03 * -6.68

13a -3.38 -2.02 -2.42 -3.28 -3.26 -4.12 -5.70 -5.63

16 0.18 0.15 -4.03 -4.84 * * -6.49 *

17 -0.75 -0.77 -2.92 -4.23 -3.14 -4.45 -5.56 -5.78

18 0.03 -0.13 -4.55 -4.89 -3.79 -4.13 -7.29 -6.53

19 0.26 0.14 -3.69 -4.55 -3.42 -4.28 -6.19 -5.92

20 0.00 -0.10 -4.77 -5.49 -3.76 -4.54 -6.38 -5.73

21a -0.02 0.03 -3.71 -4.29 -3.53 -4.11 -5.71 -5.53

21b -0.10 0.06 -3.74 -4.27 -3.50 -4.02 -6.22 -5.98

22 0.19 0.11 * * -3.54 -4.33 * -5.82

23 0.08 -0.04 -3.21 -3.87 -3.19 -3.86 -5.42 -5.41

24 0.30 0.01 -4.30 -4.41 * * -7.53 *

25 0.09 -0.06 -3.96 -4.32 -4.03 -4.40 -5.85 -5.92

26 0.01 0.06 -4.56 -5.04 * * -6.70 *

27a 0.44 0.50 -4.43 -4.65 -4.09 -4.31 -6.78 -6.43

27b 0.62 0.56 -4.48 -4.75 -3.95 -4.22 -6.99 -6.45

27c 0.53 0.56 -4.30 -4.54 -3.86 -4.10 -6.76 -6.32

27d 0.64 0.59 -4.36 -4.65 -4.03 -4.32 -6.91 -6.58

28 0.11 -0.04 -4.24 -5.01 -4.21 -4.98 -6.80 -6.77

30 0.08 0.04 -3.56 -4.19 -3.39 -4.01 -5.72 -5.54

31 -0.12 0.01 -2.72 -3.37 -3.67 -4.32 -5.59 -6.54

32 0.28 0.53 * * -4.21 -5.40 * *

33 0.01 -0.11 -4.78 -5.10 -4.52 -4.84 -5.17 -4.91

34 0.36 0.02 -5.14 -6.08 -3.54 -4.47 -7.45 -5.85

35 ** 0.30 -3.80 -3.94 -3.71 -3.83 -5.72 -5.55

36 0.10 -0.06 -2.73 -2.92 -3.09 -3.27 -4.72 -5.08 * Refers to samples “not tested” as they were not part of the test panel for that laboratory. ** Refers to

“not received” as insufficient vials were remaining of this sample.

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Appendix V

Collaborative study draft IFU

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