who/bs/2015.2270 english only expert committee on biological standardization geneva, 12 to 16...
TRANSCRIPT
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: [email protected]
© World Health Organization 2015
All rights reserved. Publications of the World Health Organization are available on the WHO web site (www.who.int) or can
be purchased from WHO Press, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland (tel.: +41 22
791 3264; fax: +41 22 791 4857; e-mail: [email protected]).
Requests for permission to reproduce or translate WHO publications – whether for sale or for noncommercial distribution –
should be addressed to WHO Press through the WHO web site:
(http://www.who.int/about/licensing/copyright_form/en/index.html).
The designations employed and the presentation of the material in this publication do not imply the expression of any opinion
whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or
of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate
border lines for which there may not yet be full agreement.
The mention of specific companies or of certain manufacturers’ products does not imply that they are endorsed or
recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and
omissions excepted, the names of proprietary products are distinguished by initial capital letters.
All reasonable precautions have been taken by the World Health Organization to verify the information contained in this
publication. However, the published material is being distributed without warranty of any kind, either expressed or implied.
The responsibility for the interpretation and use of the material lies with the reader. In no event shall the World Health
Organization be liable for damages arising from its use. The named authors alone are responsible for the views expressed in
this publication.
WHO/BS/2015.2270
Page 2
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.
WHO/BS/2015.2270
Page 3
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
WHO/BS/2015.2270
Page 4
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%
WHO/BS/2015.2270
Page 5
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
Page 6
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
WHO/BS/2015.2270
Page 7
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
WHO/BS/2015.2270
Page 8
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.
WHO/BS/2015.2270
Page 9
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.
WHO/BS/2015.2270
Page 10
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.
WHO/BS/2015.2270
Page 11
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
Page 12
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
Page 13
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
WHO/BS/2015.2270
Page 14
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).
WHO/BS/2015.2270
Page 15
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.
WHO/BS/2015.2270
Page 16
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
Page 17
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
Page 18
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
Page 19
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%
WHO/BS/2015.2270
Page 20
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.
WHO/BS/2015.2270
Page 21
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.
WHO/BS/2015.2270
Page 22
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
Page 23
References
1] Egli A, Infanti L, Dumoulin A, Buser A, Samaridis J, Stebler C, Gosert R, Hirsch HH.
Prevalence of polyomavirus BK and JC infection and replication in 400 healthy blood donors.
J Infect Dis. 2009 Mar 15;199 (6):837-46.
2] Knowles WA, Pipkin P, Andrews N, Vyse A, Minor P, Brown DW, Miller E.
Population-based study of antibody to the human polyomaviruses BKV and JCV and the
simian polyomavirus SV40. J Med Virol. 2003 Sep;71(1):115-23.
3] Hirsch HH. BK virus: opportunity makes a pathogen. Clin Infect Dis. 2005 Aug
1;41(3):354-60. Epub 2005 Jun 14.
4] Luo C, Bueno M, Kant J, Randhawa P. Biologic diversity of polyomavirus BK genomic
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
Page 37
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
WHO/BS/2015.2270
Page 43
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
WHO/BS/2015.2270
Page 53
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.