Eurachem Scientific Workshop - Data - Quality, Analysis and Integrity
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Eurachem
Scientific Workshop
Data - Quality, Analysis and Integrity
14th & 15th May 2018
Dublin Castle, Ireland
DELEGATE NAME
Supported by
Gold Sponsors
Silver Sponsors
2 www.eurachem2018.com
[ Contents
]
Conference Information 4
Welcome Message 6
Conference Committee 7
Workshop Programme 8
Invited Speakers 10
Conference Sponsors 18
Floor Plan 20
Abstracts 21
Get Social on Twitter FREE Wi-Fi
Follow the event on twitter There is free Wi-Fi
using @eurachem2018. throughout the venue.
During the event join the Username DC_Conference
discussions using the and password May-2018
hashtag #Eurachem2018
@eurachem2018 3
[ Conference
Information ]
Ship Street
Gate
12
15
7
1 Dublin Castle Ticket Office
6 2 State Apartments
1 3 Viking & Medieval Excavation
8 4 Chapel Royal
9
5 2 5 Medieval Tower
6 Dubhlinn Gardens
10 7 Coach House Gallery
4
14 8 Terrace Café
13
9 Hibernia Conference Centre
3 10 Bedford Hall
11 Printworks Conference Centre
12 Chester Beatty Library
Cork Hill 13 Revenue Museum
11 Gate 14 Revenue Commissioner
16 15 Assay Office
16 Garda Museum
Palace Street
Gate
Conference Venue By Tram (Luas)
The conference will take place in the The closest Luas stops are Westmoreland
Hibernia Conference Centre located within and Trinity. The next stops are St Stephen’s
Dublin Castle. There are three entrances to Green on the Green Line and Jervis on the
Dublin Castle. The Ship Street Gate entrance Red Line.
or the Cork Hill Gate entrance are the closest
to the conference centre (please see the By Car
map above). Once inside the courtyard Please note there is no visitor parking
of Dublin Castle the Hibernia Conference available on site. The nearest public car parks
Centre is located in the Upper Yard of the are Q-Park Christchurch and Park Rite Drury
Castle (No 9 on the map). Street.
Address: Dame Street, Dublin 2, Ireland
At the Conference
Find Dublin Castle Registration
By Bus The Registration desk will be located on the
Buses stopping on nearby George’s Street: ground floor level and will be open during
9, 14, 15, 15A, 15B, 16, 65, 68, 83, 122, 140 the conference from 8.30am on Monday
Buses stopping on nearby Dame Street: 13, 14th May. When you arrive at Dublin Castle
27, 40, 49, 54A, 56A, 77A, 123, 150, 151, 747 Conference Centre, please ensure that you
go to the registration desk to check in and
collect your name badge.
4 www.eurachem2018.com
[ Conference
Information ]
Poster Set-Up Conference Dinner
All posters need to be displayed by 10.00 The conference dinner will be held in the
on Monday 14th May in the designated area renowned Guinness Storehouse, located in
near the registration desk. Poster presenters the heart of the legendary St. James’s Gate
will be required to be at their posters for the Brewery in Dublin on Monday 14th May.
reception and poster session on Monday 14th Please arrive between 19.15 and 19.45 to
May from 17.00 - 18.00. allow time to follow the story of Guinness.
This self-guided tour can take up to 20
Poster Pack-Down minutes.
All posters need to be removed from the
poster boards by 17.00 on Tuesday 15th May. Visitors are asked to enter the building from
All posters must be removed by this time the cobbled entrance situated on Market
otherwise they will be disposed of. Street (in through the large black Guinness
Gates). Once you have been through the
Poster Session tour you will then be guided to the Arrol
Delegates are encouraged to attend the Suite on the 2nd floor where you can
poster session on Monday 14th May at 17.00 - learn to pull the perfect pint of Guinness.
18.00. Refreshments will be provided. Dinner will commence at 20.00. (This
event is included in the Eurachem Scientific
Exhibition Workshop registration fee).
The exhibition will be open during the
morning and afternoon coffee breaks and All delegates who have booked to attend the
lunchtimes. We ask that you take the time to conference dinner are required to arrange
visit the stands. their own way to and from the dinner venue.
Please see options below.
Refreshments
Coffee breaks will be served each day on Options on how to get to the Guinness
the lower ground floor outside the main Storehouse:
conference hall. Lunch will be provided each
day and will be served in Castle Hall. Walk with the group, departing from Palace
Street Gate (marked on the map) at 19.00
Mobile Phones sharp, walking time 25 minutes.
We kindly ask all delegates to keep their
mobile devices turned off or on ‘silent’ mode or Make your own way there (a map & trail
during all presentations. will be provided at the workshop).
Twitter: or Take the bus. From Dame Street (outside
You can join the Twitter conversation: Dublin Castle) the following buses will take
@eurachem2018 you to the venue, 13, 40 & 123.
Wi-Fi: or Take a taxi which can be flagged in the
There is complimentary Wi-Fi available to street, collected at a rank or ordered using
delegates throughout the conference centre. the MyTaxi app. The fare from Dublin Castle
Username DC_Conference and password to the Guinness Storehouse should be less
May-2018 than 10euro.
@eurachem2018 5
[ Welcome
Message ]
Dear Colleagues,
Welcome to Dublin Castle!
Eurachem Ireland, in conjunction with the know the great community of people you
Eurachem Education and Training Working are working alongside across Europe. Please
Group (ETWG), are delighted to be hosting make use of the times during lunch, coffees,
the 2018 Eurachem Workshop, exploring the poster session and the conference dinner
topics around Data – Quality, Analysis and which are dedicated to networking and
Integrity, here in Dublin. This workshop scientific discussion.
takes place in conjunction with the General
Assembly, the flagship annual meeting of We would like to thank both the local
Eurachem. Our Cypriot colleagues hosted a organising and the scientific committees
successful and insightful workshop in 2017, who have been particularly supportive. We
and we are delighted to build on this success would also like to acknowledge the help
in Dublin 2018. It is a great honour for us to and support of Happenings, our conference
welcome Eurachem back to Dublin, 21 years organisers, who have pulled together the
since we last hosted the General Assembly, wonderful event you are participating in this
back in 1997. week, and Fáilte Ireland, who supported our
bid to bring Eurachem 2018 to Dublin.
The programme for Eurachem 2018 is
packed full with oral, flash and poster Finally, we’ll leave you with some relevant
presentations around a diverse range of trivia - A Guinness brewer developed the
topics. Given the short time we have for famous statistical analysis tool, the students
this meeting, we have tried to maximise t-test. Who was this? Enjoy the tour on the
the number of presentation slots, making a way to the conference dinner to find out!
fairly intense and hopefully rich programme. Enjoy the meeting and many thanks for your
However, as importantly, we hope that this support,
meeting will afford you the time to get to
Assoc. Prof. Blánaid White, Vicki Barwick,
Scientific Workshop Chair Education & Training Working Group Chair
Dr. Hugh Fay, Barbara O’Leary,
Eurachem Ireland Vice-Chair Eurachem Ireland Chair
6 www.eurachem2018.com
[ Conference
Committee ]
Scientific Local Organising
Committee Committee
Vicki Barwick UK Vicki Barwick UK
Patrice Behan Ireland Patrice Behan Ireland
Oktay Cankur Turkey Helen Cantwell Ireland
Helen Cantwell Ireland Hugh Fay Ireland
Eugenia Eftimie Totu Romania Rosemary Hayden Ireland
Hugh Fay Ireland Sean Hyland Ireland
Rosemary Hayden Ireland Sean McGowan Ireland
Michael Koch Germany Ted McGowan Ireland
Ted McGowan Ireland Colmán Ó’Ríordáin Ireland
David Milde Czech Republic Barbara O'Leary Ireland
Brian Murphy Ireland Blánaid White, Chair Ireland
Michele O'Connor Ireland
Barbara O'Leary Ireland
Elizabeth Prichard UK
Alessandra Rachetti Austria
Lorens Sibbesen Denmark
Kyriacos Tsimillis Cyprus
Wolfhard Wegsheider Austria
Blánaid White, Chair Ireland
Alex Williams UK
Perihan Yolci Ömeroğlu Turkey
@eurachem2018 7
[ Workshop
Programme ]
Day 1 - Monday May 14th
Theme “Current best practice/Where are we now?”
Aoife Morrin, Insight Centre, DCU, Ireland and Vicki Barwick, LGC, UK:
9:00 - 10:00
‘(Re)introduction to statistics: dusting off the cobwebs’
8:30 - 10:00 Registration, Coffee & Exhibition
Welcome and Opening Address
10:00 - 10:15
Ita Kinahan, The State Laboratory, Ireland
Session 1: Data Quality - Chaired by: Helen Cantwell
Stefano Cappe, Data Management Team Leader, DATA Unit, European Food
10:15 - 11:00
Safety, Italy: ‘Can we quantify the quality of the data?’
Ricardo Bettencourt da Silva, FCUL - University of Lisbon: ‘Setting data
11:00 - 11:40
requirements’
David Milde, Palacky University, Czech Republic: Traceability, validation and
11:40 - 12:00
measurement uncertainty - 3 pillars for quality of measurement results
12:00 - 13:00 Lunch & Exhibition
Session 2: Data Analysis - Chaired by: Hugh Fay
Bertrand Colson, QuoData, Germany: ‘Valid machine learning algorithms for
13:00 - 13:40
multiparameter methods’
Perihan Yolci Ömeroğlu, Uludag University, Turkey: Importance of sampling
13:40 - 14:00
step to interpret analytical results in food safety analysis
Stephen Ellison, LGC, UK: Applications of robust estimators of covariance in
14:00 - 14:20
examination of inter-laboratory study data
14:20 - 14:40 Coffee & Exhibition
Session 3: Data Integrity - Chaired by: Seán Hyland
Kyriacos C. Tsimillis, Division of Quality Assurance, Pancyprian Union of
14:40 - 15:20
Chemists, Cyprus: ‘Requirements of the accreditation standards’
15:20 - 15:40 Janine Arvizu, United States: A process for assessment of forensic data integrity
Freek Varossieau, Senior Product Specialist, Lab Informatics at Agilent
15:40 - 16:20
Technologies: ‘Data Integrity in CDS’
Laura Gonzales-Macia, Osasen Sensores SL, Spain: Validation steps
16:20 - 16:40
for a Point-of-Care (POC) diagnostic device: from prototype to market
16:40 - 17:00 Flash Presentations
17:00 - 18:00 Poster and Networking Session
19:30 Conference Dinner at the Guinness Storehouse
8 www.eurachem2018.com
[ Workshop
Programme ]
Day 2 - Tuesday May 15th
Theme “Risks and emerging challenges/Where to go from here?”
Session 1: Data Quality - Chaired by: Ted McGowan
Bertil Magnusson, RISE (Research Institute of Sweden) and Trollboken AB:
9:30 - 10:10
‘Revised internal QC from NORDTEST’
Dinesh Kapu, Athlone Institue of Technology, Ireland: A correlation of
10:10 - 10: 30 the physical attributes of a potent anti-onychomycotic dosage form with
microbiological performance.
10:30 - 11:00 Coffee & Exhibition
Session 2: Data Analysis - Chaired by: Patrice Behan
Wolfhard Wegscheider, University of Leoben, General and Analytical Chemistry,
11:00 - 11:40 Austria: ‘Multivariate analysis (chemometrics) - quality of multivariate
calibration’
Saorla Kavanagh, Dublin City University, Ireland: Assessing the relationship
11:40 - 12:00
between honey chemistry and landscape composition
12:00 - 13:00 Lunch & Exhibition
Session 3: Data Integrity - Chaired by: Colmán Ó'Ríordáin
Ilya Kuselman, Independent Consultant on Metrology, Israel: ‘Risks of a
13:00 - 13:40 false decision on conformity of a multicomponent material and quality of
chemical analytical results’
Alessandra Rachetti, Montanuniversität Loeben, Loeben, Austria: Fake Data-
13:40 - 14:00
Rationale, Detection and Implications
Session 4: Breakout Sessions
Parallel Breakout Sessions
14:00 - 15:20
Data Quality Data Analysis Data Integrity
15:20 - 15:40 Coffee & Exhibition
15:40 - 16:00 Feedback from Breakout Sessions
Session 5: Closing Session
Ruth Morgan, UCL, UK: ‘Future challenges for data: interpretation,
16:00 - 16:40
application, communication’
16.40 - 16.50 Closing Address
@eurachem2018 9
[ Conference
Chair ]
Blánaid White
Blánaid White is an Associate of molecular mechanisms
Professor in the School of which initiate and propagate
Chemical Sciences in DCU oxidative stress, particularly
and is Associate Dean for that which leads to DNA
Teaching and Learning in the damage.
Faculty of Science and Health.
A further research focus is
Her research interests focus the development of analytical
on the development of platforms. She coordinates
intelligent analysis tools and the Interreg-funded project
the application of analytical Monitool, which seeks
chemistry for the investigation to develop new tools for
of chemical and biochemical monitoring the chemical
processes in the world around status in transitional and
us. A primary focus of her coastal waters under the
research is the elucidation Water Framework Directive.
10 www.eurachem2018.com[ Invited
Speakers ]
Aoife Morrin focus has been on responsive
Associate Professor, School of materials for low-cost
Chemical Sciences, INSIGHT sensing. She is funded by
Centre for Data Analytics, Science Foundation Ireland
National Centre for Sensor for a work programme on
Research wearables and epidermal
sensing as a means to collect
Aoife Morrin obtained her PhD health diagnostic data. She,
in electroanalytical chemistry in collaboration with Prof.
in 2004 at Dublin City Dermot Diamond, has co-
University (DCU) under Prof. authored the book ‘Advanced
Malcolm Smyth. Following Data Processing using
her PhD she gained post- Microsoft Excel’. Their book
doctoral experience at the Sciences at DCU as lecturer in gives an overview of how
National Centre for Sensor Analytical Science in 2008. basic and advanced statistical
Research at DCU. She took methods can be used in the
up an academic position She has an active research teaching and practice of the
in the School of Chemical group where a lot of her analytical sciences.
Vicki Barwick with responsibility for the
Head of Commercial Training, development and delivery of
Science & Innovation Division, quality assurance training.
LGC, UK
She has worked in education
Vicki graduated with a and training in relation to
degree in chemistry from the analytical measurement
University of Nottingham in for almost 20 years. Vicki
1990. She began her career is actively involved in the
as an analytical chemist at Eurachem network and
LGC (formerly the Laboratory is currently Chair of the
of the Government Chemist) Education and Training
working in the area of Working Group and a member
consumer product safety. She is currently the head of of the Method Validation
commercial training at LGC Working Group.
@eurachem2018 11[ Invited
Speakers ]
Ita Kinahan international analytical affairs
State Chemist, The State and the State Chemist has
Laboratory, Ireland enforcement and referee
status under various Acts
The State Laboratory is a of the Oireachtas and their
scheduled office under the implementing regulations.
aegis of the Department The Laboratory provides
of Public Expenditure and representation for client
Reform which provides a Government Departments at
comprehensive analytical EU meetings.
and advisory service to
Government departments and The State Laboratory is a
offices, thereby enabling them designated EU National
to implement and formulate spirits or possession of illegal Reference Laboratory for
the technical aspects of medicines. residues of a wide range of
national and EU legislation. veterinary medicines in food
Analyses for the presence of of animal origin; for additives
The State Laboratory alcohol and drugs assist the for use in animal nutrition; for
undertakes chemical analyses Coroners to determine the dioxins and polychlorinated
for a variety of different cause of deaths, e.g. in cases biphenyls (PCBs); and for
purposes which include of alcohol / drug overdoses, mycotoxins and heavy
monitoring the quality and while, in the Customs area, metals in animal feed. It has
safety of Irish food and analysis can show whether also been designated as the
prosecuting fraud e.g. illegal additional duties or fines responsible Irish body for
use or laundering of marked may be payable. Staff are traceability of measurement
diesel, sale of counterfeit actively involved in EU and in chemical metrology and
bio-analysis.
Stefano Cappe The collected data provide
Data Management Team the basis for many EFSA risk
Leader, DATA Unit, European assessment works in the
Food Safety above areas.
S. Cappe is responsible for the His main work is around data
team “Data management” in collection, data integration,
the “Evidence management” data quality, data warehouses
unit of EFSA. The team is in and business intelligence to
charge of the data collections support data analysis and
of chemical contaminants, risk assessment. From 2001
additives, pesticide and to 2007 he worked in EMA
veterinary medicinal products (European Medicines Agency)
residues, zoonoses and in the development of the
antimicrobial resistance, European pharmacovigilance
molecular typing. system.
12 www.eurachem2018.com[ Invited
Speakers ]
Alex Williams Eurachem working group on
Alex Williams, formerly the UK Uncertainty Evaluation and
Government Chemist. Alex Traceability and is joint editor
is a proposer and founder of the Eurachem guides on,
member of Eurachem. Uncertainty, Traceability,
He is a member of the Compliance and Setting
Target Uncertainty.
Ricardo Bettencourt Eurachem working group
da Silva on Qualitative Analysis
Environmental and a member of the
Biogeochemistry Group - Eurachem working group on
Centro de Química Estrutural Measurement Uncertainty and
(CQE@FCUL), University of Traceability of Eurachem.
Lisbon
He is co-editor of the
After working in accredited Eurachem/CITAC guide
laboratories as analyst and for Setting the Target
consultant for 15 years, Measurement Uncertainty.
Ricardo started a research His research interests are
and teaching career at the Metrology and Examinology
University of Lisbon. Since and in training staff of in chemistry which are the
2002 he has collaborated with laboratories. Ricardo is sciences of measurements
the Portuguese Accreditation currently the secretary of and qualitative analysis in
Body, as technical assessor, CITAC, a member of the chemistry, respectively (http://
executive board, chair of the webpages.fc.ul.pt/~rjsilva/).
@eurachem2018 13[ Invited
Speakers ]
Bertrand Colson solutions and powerful web
QuoData, Germany applications.
Bertrand Colson is an As an expert in method
experienced data scientist development and validation,
involved in a variety of he contributes to several
projects focusing on analytical projects in international
quality assurance in the standardization e.g., to
fields of food safety, process ISO/TC 34/SC 9/WG 2, a
validation, forensics, and working group developing
diagnostics. an international standard for
validation of methods in the
He develops and validates field of food safety.
novel approaches for data applying machine learning
analysis and interpretation by techniques to realize tailored
Kyriacos C. Tsimillis others as a member of peer
Division of Quality Assurance, evaluation teams.
Pancyprian Union of
Chemists. Since 1997 he represents the
Pancyprian Union of Chemists
Kyriacos Tsimillis holds a BSc (PUC) in Eurachem, including
and a PhD in chemistry from a two-year period as its
the University of Athens where Chair and for many years as
he was later a lecturer of a member of the Executive
physical chemistry. Committee; he is the author
of research papers and review
Since 1982 he has been articles and a co-author of
involved in standardization books on Quality. Since 2014
and certification activities in (Director 2009-2013). he is a member of the Division
Cyprus and for twelve years He participated in the of Quality Assurance of the
in accreditation activities activities of EA, among PUC.
14 www.eurachem2018.com[ Invited
Speakers ]
Freek Varossieau Phase-I and II studies and
Senior Product Specialist: Phase-I studies in patients.
Lab Informatics at Agilent
Technologies In 1990 Freek joined Perkin-
Elmer responsible for support
Freek graduated in 1977 as a contracts and expanded this
clinical chemist and worked to LIMS and networked CDS.
for 10 years at the Netherlands At Agilent Technologies Freek
Cancer Institute in New Drug currently holds a network
Development for the EORTC, specialist position for CDS,
focusing on pre-clinical SDMS and ELN in Europe.
Bertil Magnusson with analysis and quality in
RISE (Research Institute of measurements including
Sweden) and Trollboken AB. accreditation, quality control,
validation, measurement
Bertil started as a marine uncertainty and decision
chemist looking for traces making.
of metals in the Oceans in
the 70’s. After his PhD he A major part is teaching
joined a chemical company, and taking part in writing
AKZO-NOBEL, and worked guidelines from e.g. Nordtest
there as a specialist in and Eurachem. In 2016 he
analytical chemistry mainly started a small company
with spectroscopy (XRF, XRD, supporting labs with quality in
ICP) and wet chemistry. In RISE (Research Institutes measurement,
2002 Bertil joined SP, now of Sweden), he is working www.trollboken.se.
@eurachem2018 15[ Invited
Speakers ]
Wolfhard Wegscheider Chemistry - ASAC. In 2010
Professor of General and he was appointed a Fellow
Analytical Chemistry at the of the International Union of
Montanuniversitaet Leoben, Pure and Applied Chemistry
Austria. (IUPAC).
W. W. received his education He is a consultant to the
from the Graz University Austrian Federal Ministry
of Technology majoring in for Agriculture, Forestry,
technical chemistry with a Environment and Water
specialisation in biochemistry Management and a lead
and food chemistry. His auditor in the Austrian
diploma thesis and doctoral Accreditation of Laboratories
thesis were in analytical and Eurachem where he is System. Presently he is chair
chemistry with an emphasis also a founding member of the Board of Trustees of
on trace analysis and of the Working Group on OeAD GmbH, the Austrian
environmental analysis. Education and Training and Agency for International
of the Working Group on Cooperation in Education and
W.W. is a member of several Measurement Uncertainty Research. W.W. is a member
learned societies such as and Traceability. He is of the Statistics Committee
GDCh, GOECh, Co-operation currently is a Member of the of AOAC International for the
on International Traceability in Board of Directors of the period 2016-2019.
Analytical Chemistry (CITAC) Austrian Society of Analytical
Ilya Kuselman From 1991 to 2014 he was
Independent Consultant on a Director of the National
Metrology, Israel. Physical Laboratory of Israel.
Now Ilya is an independent
Ilya Kuselman received his consultant on metrology in
Ph.D. in inorganic chemistry Israel.
from Kalinin State University,
and his D.Sc. in analytical He has published more than
chemistry - from the R&D 200 papers on metrology and
Institute for Rare Metal quality in analytical chemistry.
Industry, Moscow, Russia. Ilya is a member of CITAC,
ISO/REMCO and IUPAC
From 1971 to 1990 Ilya was Analytical Chemistry Division.
firstly a researcher before of Non-ferrous Secondary
becoming Head of Metrology Metals, Donetsk, Ukraine,
in the Chemistry Division USSR.
of All-Union R&D Institute
16 www.eurachem2018.com[ Invited
Speakers ]
Ruth Morgan Morgan has received the
Professor Ruth Morgan is the PW Allen Award from the
Founder and Director of the Chartered Society of Forensic
UCL Centre for the Forensic Sciences for best publication
Sciences and Professor of in the Chartered Society of
Crime and Forensic Science Forensic Science journal
at UCL. ‘Science and Justice’ in 2006
and 2017.
The Centre facilitates a
network of researchers from She sits on a number of
a wide range of different advisory bodies including
disciplines, to enable a groups at the Home Office
strategic and multidisciplinary and the Knowledge Transfer
research programme in research group is focussed Network, and is the Vice Chair
collaboration with external on developing the field of of the London Geological
partners and forensic forensic science evidence Society Forensic Geoscience
science stakeholders. Her interpretation. Professor Group.
@eurachem2018 17[ Sponsors/
Exhibitors ] Gold Sponsors
Agilent
Agilent is a leader in Pharmaceutical, Life Sciences, Diagnostics,
and applied markets. The company provides laboratories
worldwide with instruments, services, consumables, applications
and expertise, enabling customers to gain the insights they seek.
Agilent has about 13500 employees globally and had revenues of
$4.47 billion in fiscal year 2017.
Agilent
Tel.: 01 605 8324
customercare_ireland@agilent.com
www.agilent.com
Agilent Technologies Ireland Ltd
Unit 3 Euro House, Euro Business Park, Little Island
Cork, Ireland
QuoData
QuoData is based in Dresden and Berlin and provides statistical
expertise and consulting services to support industry, research
and government in quality assurance and process optimization.
They specialize in proficiency testing, validation of measurement
methods, experimental and sampling design. Utilizing state-
of-the-art data science methods and novel approaches for
data analysis and determination of measurement uncertainties,
QuoData develops software solutions, online platforms and
provides expertise to an international clientele.
The interdisciplinary Data Science team of QuoData has been
involved in the design and the evolution of proficiency tests
and validation studies for more than 20 years in the fields of
environmental issues, food safety, diagnostics, material research
and more.
QuoData
Tel.: +49 351 40 28 867 0
info@quodata.de
www.quodata.de/en
QuoData GmbH, Quality & Statistics, Prellerstraße 14
01309 Dresden, Germany
18 www.eurachem2018.com[ Sponsors/
Exhibitors ] Silver Sponsors
Anton Paar
Anton Paar produces high-end measuring and laboratory
instruments for industry and research. It is the world leader in the
measurement of density, concentration and CO2 and in the field
of rheometry.
Other areas of specialty are: petroleum testing, microwave
synthesis, viscometry, polarimetry, refractometry, x-ray
scattering, sample preparation and surface characterization.
The core competence of Anton Paar - high-precision production
- and close contact to the scientific community form the basis
for the quality of Anton Paar’s instruments.
Anton Paar’s strong sales network in more than 110 countries
guarantees customers rapid support and answers to their
application and service queries.
Anton Paar GmbH Anton Paar Ltd
Anton-Paar-Str. 20 Unit F, The Courtyard
A-8054 Graz St Albans, AL4 0LA
Austria UK
Tel.: +43 (0) 316 257-0 Tel: +44(0)1992514730
Fax: +43 (0) 316 257-257 info.gb@anton-paar.com
info@anton-paar.com www.anton-paar.com
www.anton-paar.com
BIPEA
Provider of proficiency testing programmes in microbiology,
chemistry and physics.
Created in 1970, BIPEA is a nonprofit organization providing
proficiency testing programmes and reference materials
for laboratories concerned by quality control and analytical
accuracy. Present in more than 120 countries, services cover
different fields like food, feed, drinks, waters, soils and cosmetics.
BIPEA is certified to ISO 9001 by the Lloyd’s Register Quality
Assurance and accredited by COFRAC according to the ISO/
IEC 17043 standard for the organization of proficiency testing
programmes (scope 1-1495 available on www.cofrac.fr).
Today BIPEA provide a service to over 2000 laboratories.
Feel free to contact BIPEA - www.bipea.org
@eurachem2018 19www.eurachem2018.com
ENTRANCE
CONFERENCE
Table 1 Table 2 Table 3 Table 4
Tea & Coffee
EXHIBITION AREA
POSTER AREA
EXHIBITORS
Key
]
Table 1
Floor
Plan
Table 2
Table 3
Table 4
[
20[ Abstract
Index ]
Lecture (L)
Contributed Communication (CC)
Poster (P)
@eurachem2018 21[ Abstracts
]
L02
Can we quantify the quality of the data?
Cappè S1
Evidence Management Unit (EFSA)
1
EFSA is mandated1 to collect data to support results are shared with the user community (the
risk assessment activities. The Evidence data providers) and with governance bodies
Management Unit is responsible for collecting responsible for the data quality. The setting up
data in several areas (contaminants, additives, of a governance process is essential to guide
zoonoses, pesticide and veterinary medicines the investment on data quality in a sounding
residues) from Member States’ competent and cost-effective manner. They control the
authorities, academia and industry. This specific investments to improve data quality:
information is used by the unit to assess dietary e.g. new validation rules, training for data
exposure to chemicals and deliver annual providers change to data quality objectives
reports. The availability of data has been placed and KPIs. This approach is currently piloted in
at centre of EFSA 2020 strategy2, setting up EFSA to quantify the quality of the data received
strategic objectives to widen and open the data from the domains describe above. The case of
at the basis of EFSA’s scientific advice process. analytical data on contaminants is here used
Within this effort, data quality is a fundamental as an example to show how to define data
component, guaranteeing the “fitness for quality objectives and the related KPIs. The
purpose” of the collected data for the risk development of these indicators was developed
assessment process, as also clarified in the in strong collaboration with the national
outcome of EFSA Prometheus project3. organizations providing this data to EFSA
and was piloted through a grant agreement
We often define data as of “good” or including five Member States institutions. The
“poor” in quality. In the past years EFSA and data quality measures have been integrated
MSs were fully engaged on data quality, in the EFSA Scientific Data Warehouse. With
improvements were obtained through the use this example it is also possible to highlight the
of data standardisation with Standard Sample limitations of the current approach and the
Description4, grants to support electronic lessons learnt.
transmission, automatic validation rules,
training of data providers, annually revised 1. Article 33 of Regulation (EC) No 178/2002
guidance documents, and the constant 2. EFSA 2020 Strategy, available at https://www.
update of standard terminologies. Based efsa.europa.eu/sites/default/files/151008.pdf
on this experience EFSA decided to adopt 3. Prometheus (Promoting Methods for
a quantitative approach on quality in order Evidence Use in scientific assessment
to better focus its investments and initiate a described in EFSA (European Food Safety
process of continuous improvement. Authority), 2015. Scientific report on
Principles and process for dealing with data
As for quality in general, the process starts with and evidence in scientific assessments. EFSA
the definition of the data quality objectives as Journal 2015;13(5):4121, 35 pp. doi:10.2903/j.
defined by the data users and complemented efsa.2015.4121
by in-depth analysis of the data (data quality 4. EFSA (European Food Safety Authority),
profiling). Once the objectives are clarified, 2013. Standard Sample Description ver. 2.0.
it is essential to define measurable Key EFSA Journal 2013;11(10):3424, 114 pp.,
Performance Indicators (KPIs) and the expected doi:10.2903/j.efsa.2013.3424
targets. The KPIs are regularly acquired and
22 www.eurachem2018.com[ Abstracts
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L03
Setting data requirements
da Silva R1, Williams A2
Centro de Química Estrutural (CQE@FCUL) University of Lisbon, Lisbon, Portugal, 2Eurachem
1
A prime requirement is the reliable associated with a particular sample or similar
and accurate collection of all the data samples, but also to meet possible future needs
associated with the sample from its arrival is discussed.
in the laboratory, through the measurement
process, to the final report to the customer. A The above is dealing with specifying the
Laboratory Information Management System data required by the laboratory to produce a
(LIMS) provides a facility for doing this and, satisfactory result and report. A much wider
if well designed, eliminates the need for any problem is how to structure this data so that
manual transcription of data and by using, for not only can data from a specific sample be
example, barcoding reduces the possibility of retrieved but the data can be used for much
errors when manually entering information. wider applications, for example.
However, it is still necessary to determine
what data is required particularly for the • What percentage of samples showed non-
measurement process. compliance, subdivided by types of samples
e.g. food, environment and even subdivided
This presentation concentrates on the further types of food, environment
measurement data required to ensure that contaminants. This information can be
the measurement result is fit for purpose, useful, for example, to redefine the target
a requirement that is addressed during measurement uncertainty.
measurement procedure validation but should
also be checked in routine measurements. • Comparison of the uncertainty achieved as
a function of the procedure, type of sample,
As an example, setting the data requirements approach used for uncertainty evaluation,
to achieve the target measurement uncertainty cost of analysis et cetera.
will be discussed. This includes determining
the number of replicate signals or analytical Structuring the data to be able to carry out
portions, the number of points on the such analysis is quite a problem for just a single
calibration curve, and the uncertainty of used laboratory, since it is not known what future
reference materials. Also discussed are the applications might be desirable. In addition, it is
requirements for the traceability of the values wider issue if such analyses want to be carried
of the reference materials used and how the out for example across accredited laboratories
data is processed to check that the required or any other group laboratories such as within
uncertainty has been achieved. Eurachem.
Additionally, the issue of structuring the data,
not only to meet the management needs
@eurachem2018 23[ Abstracts
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L04
Data integrity: Requirements of the accreditation standards
Tsimillis K1
1
Division Of Quality Assurance, Pancyprian Union Of Chemists, Nicosia, Cyprus
The requirements for the competence of [2] for “information systems”. Both standards
laboratories are described in two standards, provide for the laboratory information
namely ISO/IEC 17025:2017 [1] and ISO management system(s) used for the collection,
15189:2012 [2]. The former applies to all processing, recording, reporting, storage or
laboratories except to medical laboratories retrieval of data; the standards also provide
where the latter is the most appropriate. for the need for validation for functionality of
After the new standard ISO/IEC 17025 [1], these systems including the proper functioning
laboratory activities may include, further to of interfaces within the laboratory information
testing and calibration, sampling associated system(s) before introduction as well as
with subsequent testing or calibration. These whenever changes are made. The standards
standards are the ones used by accreditation specify certain requirements with regard to
bodies in the assessment of laboratories the protection from unauthorized access,
for their accreditation. This is why the term against tampering and loss, inappropriate
“accreditation standards” is used throughout environmental conditions and other factors
this presentation. The requirements of these which may affect the integrity of data and
standards include specific references to data, information. Particular requirements are also
their protection and integrity. This presentation set regarding documentation and personnel for
refers to the requirements of the accreditation the management of the information system(s).
standards for laboratories in a comparative Particular requirements are set for cases when
way. According to ISO 9000 [3], data is defined a laboratory information management system is
as facts about an object i.e. an entity, an item, managed and maintained off-site or through an
anything perceivable or conceivable. This may external provider. In general, the two standards
include among others a product, a service, a set requirements for data integrity in a similar
process, a person, an organization, a system, way; however, ISO 15189 [2] addresses these
a resource. Data is also the primary product of issues in a way that reflects the particular needs
laboratory work and represents the basis on of the sector dealing with personal data of the
which results, reports and certificates can be patients.
issued and opinions and interpretations and
statements of compliance can be reported.
The recently published ISO/IEC 17025:2017 [1] 1. ISO/IEC 17025 (2017) General requirements
introduces additional provisions compared to for the competence of testing and
the 2005 edition for the control of data and calibration laboratories.
information management. According to this
standard, “laboratory information management 2. ISO 15189 (2012) Medical laboratories –
system(s)” includes the management of Requirements for quality and competence
data and information contained in both
computerised and non-computerized systems. 3. ISO 9000 (2015) Quality management
Similar is the definition given in ISO 15189 systems – Fundamentals and vocabulary.
24 www.eurachem2018.com[ Abstracts
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L06
Revised internal QC from 'NORDTEST’
Magnusson B1
1
RISE, Research Institutes of Sweden and Trollboken AB
The aim of the “Trollbook1” is to give good About the Trollbook - The handbook starts,
and practical guidance on internal quality after an introduction, with two chapters
control for the analysts in their daily work with (Chapters 2 and 3) on general issues of
the analytical methods. This 5th version of the analytical quality, described with specific
handbook is a minor revision. The main updates reference to internal quality control. They are
are: followed by an introduction to control charting
(Chapter 4). The tools of control charting are
• more focus on target control limits. In cases described in the following chapters: control
where the clients demand is lower than the charts (Chapter 5), control samples (Chapter
performance of the method wider control 6) and control limits (Chapter 7). Chapter 8
limits can be set. Since this will results in summarises the tools in a description of how to
fewer out of control values we recommend start a quality control program.
laboratories to consider this option,
How the data of internal quality control are
• long-term evaluation (chapter 10) now used is described in the following two chapters.
discusses changing of control limits and Chapter 9 explains the interpretation of quality
central line in separate paragraphs, control data to be performed after every
analytical run, whereas Chapter 10 explains
• pooled standard deviation is recommended how the quality control programme should
to obtain the standard deviation for setting be reviewed periodically to investigate if the
the control limits in a range chart, program is still optimal to control the quality of
the analysis.
• combined standard deviation is now more
correctly called pooled standard deviation The last chapter contains nine examples
illustrating how control charts can be started as
• a detailed example (10) of pooling standard well as practical application of the control rules
deviation for the repeatability, sr and the and the yearly review.
within-la reproducibility, sRw from an
internal control measuring three replicates 1. B. Magnusson, H. Hovind, M. Krysell, U. Lund
in every analytical run is added. If all results and I. Mäkinen, Handbook of internal control,
would be used to calculate sRw a too low Nordtest Report TR 569 (ed. 5) 2018. Available
estimate will be obtained resulting in too from www.nordtest.info.
narrow control limits.
@eurachem2018 25[ Abstracts
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L07
Multivariate analysis (chemometrics) - quality of multivariate
calibration
Wegscheider W1
1
Department of General, Analytical and Physical Chemistry, Montanuniversitaet Leoben, Austria
The observation of multiple signals for one consequences is that there is not direct way to
and the same sample simultaneously or within visualize or plot the signals vs. concentration
short time intervals has paved the way for due to the multidimensionality of the signals
many measurement systems that are lacking and/or concentrations. It also follows that the
selectivity for producing meaningful data. The classical approach to monitor the stability of a
introduction of fast recording instruments measurement process over time by Shewhart
has driven the development of equally fast control charts is not viable.
and efficient data reduction strategies in the
analytical laboratory, in process monitoring and Over the years, however, there has been
in modern sensing in general. This has not just established a number of alternative procedures
made available procedures that take much less - multivariate themselves - that aid in
time than classical ones, but also made possible giving insight in the internal structure of the
the measurement of completely new quantities multivariate calibration processes. These can
so far not accessible to analytical chemical be used to identify particularly influential
laboratories. calibration samples, the distinction between
useful and less useful, or even confusing,
In practice, there are frequently measured signals/wavelengths, and unknowns for which a
multiple signals on representative samples particular calibration can or cannot be applied
that for the purpose of calibration have been to.
characterized with respect to the analyte(s) by
independent, often time consuming methods Some recent examples of multivariate
of analysis. calibration that have been incorporated into
modern commercial instrumentation will be
These advances, however, have a couple of provided to stress the growing impact of this
consequences that require special attention type of analytical measurement.
in optimization and validation of these
multivariate measurements. One of the
26 www.eurachem2018.com[ Abstracts
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L08
Risks of a false decision on conformity of a multicomponent
material and quality of chemical analytical results
Kuselman I1, Pennecchi F2, da Silva R3, Hibbert B4
1
Independent Consultant on Metrology, Modiin, Israel, 2Istituto Nazionale di Ricerca Metrologica
(INRIM), Turin, Italy, 3Faculdade de Ciências da Universidade de Lisboa, Lisboa, Portugal, 4School of
Chemistry, UNSW Sydney, Sydney, Australia
Comparing chemical analytical (test) results is successful, the total probability of a false
with the material specification, regulatory or decision (total consumer’s risk or producer’s
acceptance limits of the component content, risk) on the conformity of the sample as a
one should decide whether the tested sample whole may still be significant. The total risk
(batch/lot) conforms or not. It is known that due to measurement uncertainty can be
measurement uncertainty, which characterizes evaluated as a combination of the particular
the quality of a result, leads to risks of false risks of conformity assessment of the sample
decisions. Evaluation of such risks for a components, whenever there is independence
multicomponent material or object involves among their test results. Possible correlation
calculation of probabilities of false decisions can be viewed as a further quality parameter
for the different components of the material or of the results, influencing the total risk of false
object (particular consumer’s and/or producer’s decisions. It should be also taken into account
risks). At the same time, even when conformity at the risk evaluation.
assessment for each component of a sample
@eurachem2018 27[ Abstracts
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L09
Future challenges for data: interpretation, application,
communication
Morgan RM1,2
1
UCL Department of Security and Crime Science, London, UK, 2UCL Centre for the Forensic
Sciences, London, UK
The innovations and developments in data trends have led to transformation, but also
analysis in the last 10 years have been produced significant challenges in a complex
phenomenal. The capacity for accuracy, interdisciplinary space. A specific challenge for
precision and reliability in measurements, many applied disciplines is understanding the
combined with the ability to interrogate decision-making processes that are integral
larger datasets than ever before has created to establishing robust inferences from data.
significant opportunities to identify and Examples of the importance of using data to
understand trends, relationships and networks. understand the significance of the data itself,
and also the decision making that occurs in
This talk will draw out the importance of drawing conclusions will be presented.
not only ensuring good data quality, analysis
integrity and compliance, but also addressing The value of both good data for making
the importance of ensuring this foundation is robust and accurate classifications but also for
the basis for robust and transparent inferences demonstrating the significance of conclusions
about the meaning of the data in different that are reached from that data will be
contexts. Examples will be presented from the discussed.
field of forensic science, a field where these
28 www.eurachem2018.com[ Abstracts
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CC01
Traceability, validation and measurement uncertainty - 3
pillars for quality of measurement results
Milde D1
Palacky University in Olomouc, Olomouc, Czech Republic
1
This presentation will provide an overview of References
establishing so called 3 pillars (metrological 1. EURACHEM/CITAC Guide: Traceability in
traceability, validation of measurement Chemical Measurement (2003). Available
procedure and measurement uncertainty) for from www.eurachem.org and
quality of measurement results in chemical www.citac.cc.
laboratory. The brief introduction of each
concept based on International vocabulary 2. B. Magnusson and U. Örnemark (eds.)
of metrology will be provided as well as Eurachem Guide: The Fitness for Purpose of
approaches how to establish and demonstrate Analytical Methods – A Laboratory Guide to
them in practice. This will be linked to Method Validation and Related Topics, 2nd
Eurachem guidance that is freely available on ed. 2014. www.eurachem.org. ISBN 978-91-
www.eurachem.org website [1-3]. 87461-59-0.
Several practical examples from analytical 3. S. L. R. Ellison and A. Williams (eds).
laboratory will be also presented. Firstly Eurachem/CITAC guide: Quantifying
examples dealing with determination of Uncertainty in Analytical Measurement, 3rd
elemental impurities in pharmaceutical edition, 2012, www.eurachem.org. ISBN
products (US Pharmacopeia 232, ICH Q3D) by 978-0-948926-30-3.
ICP-MS in the laboratory working under good
manufacturing practice will be shown. The 4. M. Jarošová, D. Milde, M. Kuba: Comparison
second group of examples origination from a of ICP-MS and AAS – Elemental analysis
research analytical laboratory with focus on a of coffee. Czech J. Food Sci. 32, 354-359
metrological part and three mentioned pillars (2014).
[4, 5].
5. L. Veverková, Š. Hradilová, D. Milde,
Acknowledgements A. Panáček, J. Skopalová, L. Kvítek,
This work was supported by Ministry of K. Petrželová, R. Zbořil: Accurate
Education, Youth and Sports of the Czech determination of silver nanoparticles in
Republic (LTV 17015, LO 1305). animal tissues by inductively coupled
plasma mass spectrometry. Spectrochim.
Acta, part B 102, 7-11 (2014).
@eurachem2018 29[ Abstracts
]
CC02
Valid machine learning algorithms for multiparameter
methods
Colson B1, Gowik P2, Hettwer K1, Simon K1, Stoyke M2, Uhlig S1
1
QuoData GmbH Quality & Statistics, Dresden, Germany, 2BVL, Berlin, Germany
In the light of recent food fraud cases, the issue Consider the example that, on the basis of a
of food authenticity is receiving increasing batch of 100 fish, the task is to decide which
attention. New analytical methods and come from origin A and which from origin B.
evaluation approaches are currently being In the case of the training set, each sample is
proposed in order to address this issue. In this allocated to one of the two subpopulations.
framework, the evaluation of mass spectral Once the measurements have been performed,
profiles constitutes a promising avenue, e.g. the resulting multiparameter spectral dataset
for the determination of food origin. Relevant is so large and manifold that it will always
evaluation approaches include PCA, cluster be possible to identify criteria which will
analysis, discriminant analysis, etc. The aim is to result in satisfactory levels of discriminatory
derive criteria for the assignation of unknown power – in the sense that test decisions after
samples to subpopulations. These criteria application of the criteria agree with the “true
are derived on the basis of samples whose answers”. However, the question is whether the
origin is known – the training set. A reliable application of the criteria to a test set will yield
evaluation requires that the number of samples reliable test decisions.
must be considerably larger than the number
of parameters. However, in the framework of One possible approach consists in developing
multiparameter mass spectrometry methods, a function which measures the “distance”
the required ratio between sample and between a particular sample’s spectrum and
parameter numbers is inverted, with e.g. 100 the spectra of all the samples belonging
samples versus over 10 000 parameters. In to the subpopulation under consideration.
this presentation, approaches for a reliable The reliability of the criteria depends on an
specification of criteria in spite of insufficient appropriate consideration of the measurement
sample numbers are discussed. uncertainty of the multiparameter method.
30 www.eurachem2018.com[ Abstracts
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CC03
Importance of sampling step to interpret analytical results in
food safety analysis
Yolci Ömeroğlu P1
1
Uludag University Faculty of Agriculture Food Engineering Department, Bursa, Turkey
The European Commission aims to assure a to customer if a representative sample
high level of food safety within the EU from reflecting the properties of lot being sampled
farm-to-fork by effective monitoring the can be provided. The primary samples from a
market. To facilitate the international food trade lot must be taken randomly and should consist
and to protect consumers’ health, European of sufficient material to provide laboratory
Union, and National Authorities set legal samples required from a single lot. Variations,
limits for the analyte being into consideration. caused by heterogeneity, contamination, loss
For those purposes, each year more than of analyte or use of an incorrect sampling plan,
thousands of food samples are analyzed may be observed between the compositions
worldwide. of random samples taken from a lot. These
variations can lead to uncertainty in sampling
Food safety testing methods include two step and should be taken into account. It
main steps: sampling performed outside of was reported that sampling uncertainty
the laboratory, and laboratory operations is the biggest contributor in major food
comprising of sample preparation, sample testing including aflatoxin and pesticide
size reduction, sample processing, extraction, residue analysis. In this presentation, various
clean-up, and determination. Sample is sampling plans in food testing, contribution of
defined as one or more units selected from sampling uncertainty to overall measurement
a population of units, or a portion of material uncertainty, interpretation of analytical results
selected from a larger quantity of material. taking into account sampling uncertainty are
Reliable analytical results can only be reported aimed to be explained and discussed in detail.
@eurachem2018 31[ Abstracts
]
CC04/P05
Applications of robust estimators of covariance in
examination of inter-laboratory study data
Ellison S1
LGC, Teddington, United Kingdom
1
Many inter-laboratory studies involve the an observation as anomalous; for example, for
collection of results for more than one univariate outlier detection, critical values for
measurand from each participant. For example, common statistical outlier tests are used to
in a collaborative study aimed at validation of a decide whether follow-up action is appropriate.
new standard measurement procedure, results For multivariate data, such criteria will
for more than one test material are usually commonly require information on covariance
collected, either to obtain information on between different measurands. Since most
precision at different levels or as part of a split- interlaboratory data sets show at least some
level design. In reference material certification outliers, however, the usual measures, such as
by inter-laboratory study, results for multiple covariance and Pearson correlation, can badly
analytes in the same candidate reference overestimate the covariance of the underlying
material may be obtained, or a separate distribution.
quality control material of known properties
may be included for assessing laboratory There are, however, a number of outlier-
performance. Proficiency testing rounds also resistant procedures for obtaining estimates
frequently collect data for multiple measurands, of covariance or correlation. These include,
on multiple test items, or both. In these for example, a simple pairwise procedure due
circumstances, the identification of anomalous to Gnanadesikan and Kettenring, and more
results can be challenging, as it is possible for complex iterative procedures such as the
a laboratory to have results with an acceptable minimum covariance determinant method.
range for each individual measurand on each Rank correlation is also relatively resistant to
test item but nonetheless differ substantially extreme values compared to the usual Pearson
from the remainder of the population in terms correlation.
of the general pattern of results. Identifying
such anomalies is an important step in initial This short paper illustrates the use of selected
data inspection and ‘clean-up’. robust estimators of covariance or correlation
in the identification on anomalous laboratory
Several approaches for outlier identification results in inter-laboratory data. It is shown that
in multivariate data are available. For bivariate robust estimators can substantially reduce
data, Youden plots can be effective. For the impact of outlying values on multivariate
multivariate data, principal component analysis confidence regions and consequently lead to
and measures such as Mahalanobis distance sharper identification of anomalies even where
can be valuable aids. However, while visual traditional univariate outlier detection may fail
inspection is always useful for inspection, it is to locate anomalous results.
often useful to include criteria for declaring
32 www.eurachem2018.com[ Abstracts
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CC05
A process for assessment of forensic data integrity
Arvizu J1
Independent, Tijeras, United States
1
In recent years, reports of invalid forensic This presentation draws from decades of
methods (e.g., bullet lead analysis; microscopic experience conducting audits of analytical
hair analysis) and analyst misconduct (e.g., laboratories and their work product. A summary
dry labbing; falsified credentials) have of forensic integrity problems will be provided,
rocked the legal community and led to including the most common problems (widely
numerous exonerations. Forensic laboratories distributed and frequently identified) and the
throughout the United States have been most serious problems (those with the highest
plagued by instances of blatant fraud, analyst risk of false incrimination).
incompetence, and procedural deficiencies.
Though the legal community relies on forensic This presentation will also introduce a process
results, it often lacks scientific training and for objectively evaluating the integrity of
remains ignorant of data integrity problems, forensic results based on a practical and
resulting in case outcomes that are based on universally applicable definition of forensic data
invalid scientific conclusions. integrity. The principle behind this process is
that an analytical result has integrity and can
Hundreds of forensic laboratories have be reliably used as the basis for consequential
developed quality systems and been accredited forensic decisions if records demonstrate:
to ISO/IEC 17025, but accreditation does not
ensure that a laboratory’s reported results 1. the sample(s) is(are) unambiguously
have integrity. While the scientists who work in representative of the original evidence;
forensic laboratories are generally aware of the 2. the analytical method has been empirically
importance of quality assurance, operational validated and found to be appropriate for its
pressures and pragmatic considerations may intended forensic use; and
limit their focus to those aspects of forensic 3. the analysis was reliably conducted and
science that are within their direct control reported in accordance with relevant
inside the laboratory. Forensic analysts standards.
responsible for production testing may have
little, if any, direct knowledge of the theoretical This process for evaluating forensic integrity
principles or practical constraints that influence is applicable to the full scope of test methods
the quality of the evidentiary samples that conducted by forensic laboratories—from
are delivered to the laboratory for testing. Yet DNA and toxicology to gunshot residue and
analysts may testify based on the unverified controlled substances—and addresses the
assumption that the evidence tested in the problems that adversely affect the integrity
laboratory was representative of the evidence of forensic results, including fraud, sampling
in the field. Similarly, a validation study that errors, metrological failures, and invalid
effectively characterizes the qualitative and methods. The efficacy of this assessment
quantitative performance of an analytical process will be demonstrated, using examples
method may nevertheless be insufficient for drawn from criminal cases in the United States.
forensic use.
@eurachem2018 33You can also read
