Switzerland 2017 | PhUSE Single Day Event | 1
BaselSingle Day Event
Workflow Automation and/or Optimisation16th May 2017Novartis Offices, Basel
2 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 3
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4 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 5
Dear Single Day Event Attendees,
It is our pleasure to welcome you to the PhUSE Single Day Event (SDE) in
Basel. This event will serve as a forum for interactive discussions, mindshare
and knowledge enhancement.
The theme for this year is “Workflow automation and/or optimisation”, to
respond to the ongoing problem of facing repetitive tasks and manual steps
that could be optimised in the biometrics environment, where fundamental
processes have not changed.
Content from our agenda will address current challenges, concerns and
issues related to key topics around technology, metadata and processes.
Out of a broad range of topics, we have selected presentations such as
Data-integration Automation; Automated Self-documenting Programs,
Automated Table Shells, Landing Zones and the Importance of Standards;
Metadata-driven Programming of Clinical Statistical Results Displays; An
Iterative Approach to Workflow Automation and Optimisation; Metadata-
driven Automation of TFL Programs; Metadata-driven Process from Global
Definition to Analysis Specifics; and Autoquery Manager. We will also have
demos such as The eRAP Tool: An Aid to Improving the Quality and Delivery
of Analysis Plans and From Standards Management to Final Analysis:
Workflow-driven Automation in Primary Research.
We hope you find this agenda interesting and will join us in making this
PhUSE SDE an enjoyable and productive experience!
We look forward to meeting you in Basel.
Best regards,
Anne & Nicolas
Basel Single Day Event Chairs 2017
IntroductionYour guide to the day
AgendaTime Title and Speaker
08:30–09:00 Registration and coffee
09:00–09:30 Welcome
Anne Mounier & Nicolas Dupuis, Novartis
09:30–10:00 Review and Highlights of the 2016 Survey of the Top 20 Biopharmaceutical
Companies' Statistical Computing Environments (SCEs)
Jean-Marc Ferran & James McDermott, JM Partners
10:00–10:30 Data-integration Automation
Florence Buchheit & Gregory Pinault, Novartis
10:30–11:00 Morning break
11:00–11:30 Automated Self-documenting Programs, Automated Table Shells,
Landing Zones and the Importance of Standards
Christoph Ziegler, Roche
11:30–12:00 Metadata-driven Programming of Clinical Statistical Results Displays
Florian Storch, Analytical Software
12:00–12:30 The eRAP Tool: Demo of an Aid to Improving the Quality
and Delivery of Analysis Plans
Michael Roughton, Novartis
12:30–13:30 Lunch
13:30–14:00 An Iterative Approach to Workflow Automation and Optimisation
Dave Iberson-Hurst, Assero Limited
14:00–14:30 Metadata-driven Automation of TFL Programs
Rafi Rahi, Shafi Consultancy Limited
14:30–15:00 Demo: From Standards Management to Final Analysis:
Workflow-driven Automation in Primary Research
Daniel Christen, SAS
15:00–15:30 Afternoon break
15:30–16:00 Metadata-driven Process from Global Definition to Analysis Specifics
Marjorie Nowak & Aurélien Guillouche, Novartis
16:00–16:30 Autoquery Manager: Self-healing Software & High-performance Reporting
Ceferino Garcia, Roche
16:30–17:00 PhUSE
Jules van der Zalm, PhUSE
17:00–17:30 Closing and Get-together
Anne MounierNovartis
Nicolas DupuisNovartis
Welcome to Basel
6 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 7
The Committee Speakers and abstracts
Abstract
The authors will present their recent 2016 SCE survey, on
behalf of Novartis, of the system owners of the 20 largest
biopharmaceutical companies. They will examine any observed
differences between the needs of the estimated 20,000 users of
SCEs in the companies surveyed and the industry in general. This
presentation will feature trends in the pharmaceutical industry
with regards to definition, usage and areas for development of
SCEs, whether they are commercial-off-the-shelf (COTS) or
custom solutions or a composite of interoperable solutions. This
session will also allow the attendees to share their experience,
expectations and visions of the challenges and opportunities for
the next generation of SCEs.
Biographies
Jean-Marc Ferran is an independent consultant based in
Copenhagen, with 14 years’ experience in the life sciences
industry. Prior to starting his company Qualiance, he worked
as a statistician, standards manager and director of statistical
programming at Novo Nordisk and Ferring Pharmaceuticals.
Jean-Marc has more than 10 years’ experience working on SCE
implementation projects across various sponsors in business
lead and technical lead positions. He also leads the PhUSE De-
identification Working Group. Prior to joining the PhUSE Board of
Directors in 2014 as Special Projects Director and since 2016 as
Strategic Partnerships Director, Jean-Marc was a member of the
PhUSE Annual Conference Committee and chaired the Annual
Conference in 2012 in Budapest. He recently joined forces with
James McDermott to co-found a new consultancy called JM
Partners.
James McDermott is an independent consultant based in
Oxford, UK with 25 years’ experience in the life sciences
industry. A Chartered Statistician and a Chartered Director,
James plays a leading role in shaping the biometrics sector of
our industry. James was the founder of Oxford Pharmaceutical
Sciences (now Quanticate) in 1996 and co-founder of PhUSE
with Stephen Bamford in 2004. For the last eight years, James
has worked on many systems implementation projects across
various sponsor companies. The competencies required
include systems governance, software development life cycle,
process improvement, organisational change, computer systems
validation, compliance and data integrity. He recently joined
forces with Jean-Marc Ferran to co-found a new consultancy
called JM Partners.
Abstract
Automated self-documenting programs: how to achieve SAS
programs documenting themselves without maintaining separate
documentation (e.g. Word files).
Automated table shells: how to achieve harmony between
the actual tables/listings produced with the specifications (as
defined in the statistical analysis plan).
Landing zones: this deals with project management and
documentation/information-sharing, etc.
Standards: key of automated workflows.
Biography
From 2003 to 2004, Christoph Ziegler worked part-time at the
University of Ulm in Germany in the Department of Biometrics
and Medical Documentation, developing SAS macros and
supporting statisticians within the department, where he also
completed his “Medical documentation and computer science”
studies.
In 2004 Christoph joined the pharmaceutical industry
(Boehringer Ingelheim, Germany) as a SAS programmer, where
he developed standard reporting macros. In 2005 he joined
the statistical programming group within Boehringer, where he
worked on the reporting of Phase I to III studies. In 2006 he took
over as the sub-team programming lead in cardiology within
Boehringer.
Christoph joined F. Hoffmann-La Roche (Roche) in 2006 as
a statistical programmer, where he worked as lead project
programmer for different international teams and held the
position of Biometrics Functional Team Lead for the projects in
Basel, Switzerland. In 2016, Christoph took on the position of
Manager, Statistical Programming.
Abstract
Most pharmaceutical companies invest considerable amounts of
resources to automatise the reporting of clinical study results.
Over the past years, methods such as the implementation of
CDISC, use of metadata, and tools to generate standard tables,
figures and listings, etc. have enabled a more consistent and
efficient way to report these results. Nevertheless, the demand
for analysis across trials is increasing, creating the need to
further optimise data-integration processes. Identified challenges
range from increasing volumes and novel sources of data to
the development of ready-to-use data sets on a tight schedule.
The objectives of this presentation are to introduce the Novartis
approach to address these emerging needs and solicit feedback
and knowledge-sharing. Principles of process implementation,
tools and practical case studies will be discussed.
Biography
Florence Buchheit is a Lead Programmer at Novartis. She has
13 years’ experience in the pharmaceutical industry. She has
successfully led pooling activities for multiple purposes such as
publications, Periodic Safety Update Reports (PSURs) and
US/Europe/Japan submissions. She recently led the creation and
regular updates of a CDISC-compliant compound pool involving
more than 50 studies in several indications and including
safety and efficacy domains. Florence is also involved in the
development and improvement of data-integration processes at
Novartis.
Gregory Pinault is a statistician by training and a technology
enthusiast. He started his career in 2001 as a statistician in
a CRO and then joined Novartis’ programming team in early
development projects a few years later. In 2006, he started
focusing on Modeling & Simulation’s data requirements across
several compounds and indications, multiple data domains
and the full range of development phases. In 2009, he
started to look into sustainable data-integration methodology.
Gregory now holds a Director position in Data Integration and
Pharmacometrics and leads a team of programmers, with the
goal to develop efficient and sustainable purposed integration
of clinical data at scale. His technological skills include
programming in SAS, Python, R and Javascript, under multiple
platforms and various applications, essentially oriented towards
data science and web-based applications.
Review and Highlights of the 2016 Survey of the Top 20 Biopharmaceutical Companies' Statistical Computing Environments (SCEs)
Automated Self-documenting Programs, Automated Table Shells, Landing Zones and the Importance of Standards
Data-integration Automation
09:30–10:00 11:00–11:3010:00–10:30
Jean-Marc Ferran & James McDermott, JM Partners
Christoph Ziegler, Roche
Florence Buchheit & Gregory Pinault, Novartis
8 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 9
Speakers and abstracts Speakers and abstracts
Abstract
For all Novartis studies, the trial statistician must produce a TFL
(Tables, Figures & Listings) shells document, which gives details
about each output required for the analysis of the study. In the
past, producing the TFL shells was often a time-consuming and
inefficient process.
Novartis has now rolled out the eRAP tool, which is designed
to streamline the production of the TFL shells document. A
demonstration of the tool will be given, along with a focus on
three key areas in which the tool has a positive benefit:
• Efficiency: helping to speed up the production of the document,
new outputs and the review & approval process
• Quality: ensuring that Novartis standard outputs are routinely
used, and identifying new outputs which need approval
• Consistency: cultivating the use of milestone and project-
specific analysis plans for consistent reporting across the
Company.
Biography
Michael Roughton has a master’s degree in statistics from the
University of Southampton in the UK. He has worked for Novartis
Oncology as a Trial Statistician for almost four years. Michael
was involved in the testing and development of a new tool for
creating analysis plans at Novartis, and also gave training to other
statisticians on how to use it.
Abstract
As pressure increases on speed of TFL delivery, how
do we programmers manage to complete multiple
studies while at the same time maintain quality? The
use of SDTM and ADaM data sets allows us to have
standard input data structures for TFL programs,
which means that we can finally automate the
generation of TFL programs. Defining standard output
templates and associated macros are the only key
missing ingredients. Automation ensures consistency
both within and across studies, and reduces the effort
required both for production and validation of TFLs.
This will then finally give us the possibility to devote
more time to new and innovative analysis to further
the reporting of clinical trials.
Biography
Rafi Rahi has been a Statistical Programmer for eight
years at Shafi Consultancy. He has worked in many
different therapeutic areas and phases of clinical
trials, and specialises in developing SAS training
materials. He has been heavily involved in risk-based
monitoring over the last few years and thinks this can
have huge potential for clinical trials to improve the
quality of data.
Rafi loves training people and has trained many
people in SAS programming over the years. He has
also produced many SAS training videos designed to
teach small modules at a time. He regularly attends
PhUSE events and loves meeting people from the
industry and sharing knowledge and ideas.
Abstract
The industry has long talked about ‘end to end’ and ‘metadata-driven
approaches’ as a way of automating and optimising workflows within clinical
research. Meanwhile, the FDA talks about issues with the data quality and
integrity of electronic submissions and has recently announced further rules
and checks that are to be performed on submissions. Sponsors want to
ensure they pass these checks. This presentation will describe significant
tangible progress that has been made in moving towards the vision against
this backdrop of increased data scrutiny, and quickly outline the vision to
align the audience. It will mainly detail the current progress, demonstrating
improved version control and visibility of the impact of change including
changes across CDISC terminology and SDTM releases. The creation of
CRFs, the automated creation of annotated CRFs and the ability to build
studies will also be discussed and demonstrated. Automated traceability and
version control will be running themes.
The presentation will then consider some immediate next steps (iterations)
regarding the automated creation of Define-XML from a study build, ongoing
work in the PhUSE CSS forum on the feasibility of the creation of SDTM
domains from captured data and the potential to link back to the protocol.
The focus will then be on the longer-term vision and next steps of including
analysis and TFLs into the picture, as the iterations in capability take us
towards the end-to-end goal.
The summary will review the presentation and discuss how this approach
can help a sponsor meet their submission goals.
Biography
Dave Iberson-Hurst has over 35 years’ industry experience, with nearly 20
years in the pharmaceutical industry, during which time he has been using
and helping develop the CDISC standards.
He is now exclusively focused on the effective management and use of
metadata within pharmaceutical companies to improve process and data
quality. He currently volunteers with the CDISC XML Technology and
Define-XML teams and is a member of the CDISC Technical Leadership
Committee. Dave also participates in the PhUSE FDA Computational
Science Symposium Linked Data & Graph Databases and Emerging Trends
and Technologies Working Groups.
The eRAP Tool: Demo of an Aid to Improving the Quality and Delivery of Analysis Plans
Metadata-driven Automation of TFL Programs
An Iterative Approach to Workflow Automation and Optimisation
12:00–12:30 14:00–14:3013:30–14:00
Michael Roughton, Novartis
Rafi Rahi, Shafi Consultancy LimitedDave Iberson-Hurst, Assero Limited
Abstract
A typical task for a statistical programmer is to perform statistical
analyses of clinical trials. They are responsible for creating
analysis data sets and developing SAS programs to display the
results of the statistical analysis – based on several specification
documents (e.g. ADS plan, SAP).
Cutting information from the specification documents and
pasting it into SAS programs is not only tedious and time-
consuming, but also error-prone and ineffective. For example, if
the text or the order of footnotes is altered, the change must be
applied to all SAS programs which use the same specifications
for a table creation.
To get around this issue, a metadata-driven programming
concept was developed as part of a master’s thesis. The idea
is to implement an automated table creation of statistical
results displays for the Clinical Trial Report by using metadata.
This presentation provides the methods and results of the
implementation.
Biography
Florian graduated with a master’s degree in medical biometry/
biostatistics from the University of Bremen earlier this year. He
gained professional experience by writing his master’s thesis on
metadata-driven programming in the Statistical Programming
department at Boehringer Ingelheim, and during several
internships. Since February 2017, Florian has been working as a
Statistical Programmer at HMS Analytical Software.
Metadata-driven Programming of Clinical Statistical Results Displays
11:30–12:00
Florian Storch, Analytical Software
10 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 11
Speakers and abstracts Thanks
ContributorsThank you to all our contributors for their generous support
Abstract
The whole of the industry is trying to standardise the clinical study process
including the creation of SDTM and ADaM data sets, following CDISC
guidance and health authority requirements. A possible solution is to
automate this creation using a metadata-driven approach. When dealing
with metadata, several questions arise: What is the content of the metadata
needed? What metadata flow shall be in place? How do we adapt to clinical
study needs in regard to the collected data, the reporting needs and the
study-specific needs? What are the ADaM specificities in terms of metadata:
grouping, analysis sets and criteria, creation of analysis parameters, etc.?
How do we implement them? The concept presented tries to cover all these
questions in order to present a global metadata-driven approach for the
reporting activity from collection to submission.
Biography
Marjorie Nowak has 17 years’ SAS programming experience, including more
than eight years at Novartis. She previously worked for pharma industries
and CROs doing SAS programming for data management, as well as
validation of IT systems and SAS tools for clinical trials. At Novartis, Marjorie
has been leading clinical trial/project programming activities, gaining
experience in CDISC standards and in using metadata for a more efficient
and standardised automation of SDTM and ADaM data set creation. For the
past few years, as a member of the Reporting Data Standards team, she has
been co-organising Basel CDISC-awareness workshops, providing support
to study teams for eData submissions and contributing to the definition of
Novartis CDISC-compliant data standards and metadata. Last year Marjorie
also joined the PhUSE CSS Working Group Optimizing the Use of Data
Standards, as a member of the SDTM/ADaM Implementation FAQ sub-team.
Aurélien Guillouche has nine years’ SAS programming experience at
Novartis. His first position in the pharmaceutical industry was as a statistical
programmer intern working on oncology legacy clinical studies, where he
mainly worked on the creation of Case Report Tabulations (Define package).
He became permanent and continued his work, as well as SAS programming,
to review, create and validate programs for data sets and tables, figures and
listings (TFLs) until becoming a Trial Programmer. After more than two years
in this role, Aurélien moved to the Statistical Programming Standards Group,
where he was introduced to Computer Systems Validation (CSV) and project
management. Aurélien has been project manager on several applications
including the Case Report Tabulation and the CTC Grading. He has been
working for a few years on the CDISC implementation of metadata and,
being part of the CDISC programming support, Aurélien is now part of the
CDISC workshops training team.
Abstract
The Autoquery Manager is the query system you always wanted…
but never dared to ask for: a central repository for your safety
queries that automatically generates reports and distributes the
results on schedules you define. Set it and forget it! It knows
when it gets ill and it knows how to heal itself. It runs 7 days a
week, 24 hours a day, highly available and secure. It runs high
performance, executing thousands of queries per day. It scales
easily according to your needs without sophisticated servers.
It leads a frugal life and does not require any payment of third-
party licences. It provides a modern graphical user interface for
all required maintenance tasks. It does not solve all the problems
in your life, but it definitely makes your job easier!
Biography
Ceferino García studied computer science at the University of
Zurich. In the mid-eighties he wrote his licentiate about artificial
intelligence (AI) and started a career as a software developer/
architect. He has built successful software for high-speed trading
systems in the Swiss financial sector. Today, Ceferino works
as a consultant for Hoffmann-La Roche as a solution architect
and software developer in the .NET Framework/C# domain.
He is responsible for the system architecture and software
development of the Autoquery Manager application.
Metadata-driven Process from Global Definition to Analysis Specifics
Autoquery Manager: Self-healing Software & High-performance Reporting
15:30–16:00 16:00–16:30
Marjorie Nowak & Aurélien Guillouche, NovartisCeferino Garcia, Roche
Abstract
SAS® Life Science Analytics Framework is a secure
and collaborative clinical data framework that can
harbour all clinical data information coming from EDC
systems such as Medidata Rave and Oracle InForm
and from other external systems and providers
including deliverables from CROs.
This clinical data can be transformed or matched
against organisational and study-specific clinical
data standards. The SAS® Life Science Analytics
Framework allows converting the incoming data to
standard SDTM domains by means of SAS programs,
and performing clinical data management activities.
These activities can be tied to specific triggers and
workflows.
Biography
Daniel Christen is the Technical Account Manager
for Novartis at SAS Switzerland. He joined SAS in
May 2010 as Senior Solutions Architect, to support
SAS’ life sciences customers. Daniel’s business
background is in biostatistics for clinical research and
development.
Before joining SAS, he worked for Eli Lilly and
Company in Indianapolis, IN, where he was also
responsible for coordinating all aspects of their
functional outsourcing projects and managing
relationships with business partners for Lilly’s
biostatistics department.
Demo: From Standards Management to Final Analysis: Workflow-driven Automation in Primary Research
14:30–15:00
Daniel Christen, SAS
12 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 13
Things to come
Looking forward
Visit the PhUSE website for dates and further information –
phuse.eu/single-day-events-2017
India SDE
Mumbai
China SDE
Shanghai
November USA SDE
Chapel Hill, NC
Belgium SDE
Beerse
June Denmark SDE
Copenhagen
USA SDE
Raritan, NJ
India SDE
Hyderabad
CSS EU
London, UK
Mon 19th-Tues 20th
July USA SDE
North Chicago, IL
May China SDE
Beijing
UK SDE
London
August USA SDE
Whippany, NJ
October PhUSE Annual
Conference
Edinburgh, UK
Sun 8th–Wed 11th
September France SDE
Chilly-Mazarin
phuse.eu
PhUSE EU CSS
Computational Science Symposium19th–20th June 2017Grange Tower Bridge Hotel, London
14 | PhUSE Single Day Event | Switzerland 2017 Switzerland 2017 | PhUSE Single Day Event | 15
In your own words
NotesIn your own words
16 | PhUSE Single Day Event | Switzerland 2017
Conference Chair Jules van der Zalm, OCS ConsultingConference Co-Chair Katja Glaß, Bayer PharmaFor more information visit the PhUSE website phuse.eu/annual-conference.aspx
Annual Conference
Edinburgh Castle
Digital Innovation in Healthcare8th–11th OctoberEdinburgh International Conference Centre
Edinburgh 2017