Annual Conference 2016

Fast Track to Approval: Speed and Efficiency

9th - 12th October 2016

Conference Summary:

PHUSE 2016 was held at the Princesa Sofia Gran Hotel from the 9th to the 12th October and was chaired by Åsa Carlsheimer (Trialbee) and was a great success. With nearly 600 attendees, 44 exhibitors, 15 streams including > 120 papers, six Hands-on Workshops and Discussion Clubs, this was the biggest PHUSE conference ever. Both the venue and the location in beautiful Barcelona were perfectly suited for PHUSE.

The conference kicked-off on Sunday evening with the poster session followed by a buffet dinner and drinks. This was a perfect opportunity for networking and catching up with friends in other companies. Earlier on Sunday there was an opportunity to contribute to PHUSE in the Scriptathon.

Each day of the conference started with an inspirational talk by a keynote speaker. This year we were very fortunate to have a good mix of scientific topics presented by Alok Jah, Aseem Malhotra and Jack Lewis. Alok Jah (journalist and broadcaster) spoke about using story telling as a tool for presenting complicated topics. Dr Aseem Malhotra told us about over use of medicines and the importance of informing patients about alternative options to standard treatment. Finally Dr Jack Lewis gave a very inspirational talk about our brains and how we can train them to make better decisions. I think everyone who listened and wakes up at night knows what to do – go clean the oven! Don’t reward the brain by doing something nice. Both doctors touched upon the importance of a healthy diet without sugar. 

The theme of the conference was “Fast Track to Approval: Speed and Efficiency”. Many of the workshops and presentations discussed how we as data scientists can standardize, automatize and become more efficient in order to reduce the time to approval for our drugs. This year two new streams were introduced “Real World Evidence” and ”Data Visualization”, both were well attended and received positive feedback from the audience. The management stream continued on the interactive path with three different topics that were presented by senior leaders and lively and fruitful discussions.

All the Hands-on Workshops and Discussion Clubs were sold out and very well received as they interactively engaged and brought relevant information to the attendees. The topics featured this year were: Semantic Technology, SAS Life Science Analytics framework, CDISC, R, Computational Science Symposium and Good Programming Practice.

In addition to industry presentations, this year the regulatory stream included presentations from three different regulatory authorities. During the FDA presentation by Lilliam Rosario all seats were filled and people were standing in the back to hear the view and expertise of one of our key stakeholders.

The Conference Committee faced a significant challenge this year in selecting only the very best abstracts, and this was reflected in the high quality of all the presentations and posters at the conference. During the closing session, we had the pleasure to announce the Best Paper Awards for each stream.

We are looking forward to meeting many of you again at PHUSE events during 2016 and, of course, in Edinburgh for the next Annual Conference.

 

Papers & Presentations: 

Keynote Presentations: (Audio files)

Monday 10th October - Alok Jha

Tuesday 11th October - Aseem Malhotra (available December 2016)

Wednesday 12th October - Jack Lewis (shortened version)

 

Semantics Workshop

Semantics 101 for Pharma

Best in Stream Winners are highlighted in bold text.

 

Applications and Software Development

AD01: The TFL Workbench: Tools to Standardise and Accelerate Table, Figure and Listing (TFL) Programming

Iain Humphreys & Hansjörg Frenzel, PRA Health Sciences
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AD02: ICON's DIAMOND, or an Enhanced Way to Automate Statistical Reporting

Nathalie Fuchs, ICON

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AD03: QC of the aCRF Using SAS

Rune Pedersen & Niels Both, S-cubed

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AD04: How to Create your Define-XML as Early as Possible with the Click of a Button

Roman Radelicki, SGS Life Sciences Services

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AD05: Efficiency and Delivery Driven by Metadata

Magnus Mengelbier, Limelogic

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WINNER AD06: Making the Leap from Excel to a Database Used for Reporting

Shafi Chowdhury, Marco Ackermann & Md Zobair, Shafi Consultancy

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AD07: A Tool to Automate TFL Bundling

Mark Crangle, ICON

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AD08: Peaceful Co-existence: R and SAS

Martin Gregory & Manuel Cornes, Merck

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AD09: Programmed Patient Narratives Using SAS

Prafulla Girase & Daniel Boisvert, Biogen

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AD10: SAS Environment Upgrade: The PRA Experience

Gary Stevens, PRA Health Sciences

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AD11: Clinical SAS Application Development in a GRID environment

Giri Balasubramanian & Edwin Ponraj Thangarajan, PRA Health Sciences

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AD12: ValidR Enterprise: Developing an R Validation Framework

Andy Nicholls, Mango Solutions

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Coder's Corner

CC01: Compress It More

Linda Palm Simonsson, I-Mind

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CC02: Unicode Characters in a Table of Contents

John Hendrickx, Danone Nutricia Research

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CC03: Macro-free Parsing of Multiple Text Files with SAS

Adam Amborski, inVentiv Health

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CC04: Colour Me Useful

Robert de Gois, Veramed

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CC05: Writing Reusable Macros

Philip Holland, Holland Numerics

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CC06: How Macro Design and Program Structure Impact GPP (Good Programming Practice) in TFL Coding

Galyna Repetatska, Chiltern

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CC07: Add Derived Parameters with Multi-dimensional Arrays

Siddharth Kumar, GCE Solutions

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CC08: Perish the Sort: Using Indexes and Hash Objects for Efficient Programming

Jason Smith, Argo Analytics

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WINNER CC09: Fundamental Advice to Save Time in SAS Programming

Mickael Borne, 4Clinics

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CC10: Keeping Track of Database Changes During Database Lock

Sanjiv Ramalingam, Biogen
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CDISC Workshops

What's New

Exercise: Define v2.0 and the Need for Value Level Metadata

Standards Conceptual Model - Understanding the Potential and Possibilities

Live Demo
Peter Van Reusel and Nick De Donder, Business & Decision Life Sciences, David Iberson-Hurst, Assero

 

CDISC & Industry Standards

CD01: Protocol Representation: The Forgotten CDISC Model

Jeff Abolafia, Rho & Frank Dilorio, CodeCrafters

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CD02: CDASH V2.0: What is it Good For?
Éanna Kiely, inVentiv Health

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CD03: DIY: Create Your Own SDTM Mapping Framework

Bas van Bakel, OCS Consulting

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CD04: Assessing CDISC Therapeutic Area User Guides in a Machine Readable Format

Johannes Ulander & Niels Both, S-cubed

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CD05: Device Domains: Examples of their Use in Clinical Trials

Oksana Voevutska, Chiltern

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CD06: Analysis Datasets for Baseline Characteristics and Exposure Time for Multi-stage Clinical Trials

Kimberly Umans, Katherine Riester, Manjit McNeil, Wei Liu & Lukasz Kniola, Biogen

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CD07: OCCS - Creating Flags or Records

Rob Wartenhorst, GSK

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CD08: Increasing Work Group Transparency: ADaMIG v1.2 Update and New Team Working Process Review

Terek Peterson, Chiltern & Brian Harris, MedImmune

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CD09: Constructing a Clinical Data Warehouse for Nutrition Studies

Paul Vervuren, Danone Nutricia Research

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CD10: Linking Metadata from CDASH to ADaM

João Gonçalves, Business & Decision Life Sciences

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WINNER CD11: Analysis Results Metadata...Are We There Yet?

Carla Santillán, Chiltern

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CD12: Pattern-based MDR: Towards High-quality Data Standards

Alan Cantrell & Julius Kusserow, PAREXEL

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CD13: To Create Define-XML Using -XML and the OpenCDISC Validator

Murali Neela, GCE Solutions

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CD14: Out-of-the-box %Define-XML – Just a Simple SAS Macro

Katja Glass, Bayer Pharma

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CD15: How to Handle Different Versions of SDTM & Define Generation in a Single Day

Edwin Ponraj Thangarajan & Giri Balasubramanian, PRA Health Sciences

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CD16: Placing a Moratorium on the Madness

Scott Bahlavooni, d-Wise

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CD17: Understanding the Potential of Share: A Visual Business Case and Technical Use Case

Peter Van Reusel, Business & Decision Life Sciences

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Coding Solutions

CS01: Boosting the Efficiency of Data Review by using SAS Integration Technologies and VBA

Giuseppe Di Monaco, UCB Biosciences

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CS02: SAS, Java & Excel: A Ménage á Trois

Dana Vinzelberg, Bay Pharma

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CS03: Exploring Newer Techniques in SAS to Enhance Interactive Web Applications

Volker Harm, Bayer Pharma

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CS04: Reducing Build Time of Integrated Clinical Databases with SAS Grid and SAS/OR

Eric Brinsfield, Meridian Analytics

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CS05: Dictionary Tables – A Programmer's Friend?

Marcin Pracz, Quintiles

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CS06: Coding WHO-DDE: An Automatic, Easy and Powerful SAS Tool

Gianluca Mortari, CROS NT

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CS07: Get a JumpStart on Clinical Data Analysis and Visualisation with Standard Scripts

Jared Slain, MPI Research & Hanming Tu, Accenture

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WINNER CS08: CompareDirectory – Macro Bits and Pieces in Action

Lawrence Heaton-Wright, Quintiles

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CS09: Top 10 Uses of Macro %VARLIST – In Proc SQL, Data Step and Elsewhere

Jean-Michel Bodart, Business & Decision Life Sciences

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Data Handling

DH01: Effective Use of a Metadata Repository Across Data Operations: The Need for a Machine Readable Form

Isabelle de Zegher, PAREXEL

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DH02: Data De-identification Made Simple
Jørgen Mangor Iversen, LEO Pharma

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DH03: Grading Lab Toxicities using NCI Common Terminology Criteria for Adverse Events (CTCAE)

Srinivas Veeragoni & Ankur Mathur, Bayer Healthcare

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DH04: Integrating the New EMA Requirements on Public Disclosure in the Study Conduct (Back-up presentation, no paper available).

Jean-Marc Ferran, Qualiance

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DH05: How a Metadata Repository Enables Dynamism and Automation in SDTM-like SAS Dataset Generation

Judith Goud, Akana & Priya Shetty, Intelent Inc.

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DH06: A Standardised Approach to De-identification

Chris Hurley, MMS Holdings

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DH07: How to Review a CRF – A Statistical Programmer's Perspective

Elsa Lozachmeur, Novartis

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DH08: Efficiency comes From Reusability and Repeatability

Hanming Tu & Dave Evans, Accenture

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WINNER DH09: Calculating the Risk of Re-identification of Patient-level Data Using a Quantitative Approach

Lukasz Kniola, Biogen

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DH10: Metadata on the Go: Achieving Metadata Accuracy and Consistency Continually

Swapna Pothula, SGS Life Sciences Services

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DH11: How to Effectively Deal with Hard-coding and CDISC Controlled Terminology in Clinical Studies

Lennert van der Zee, OCS Consulting

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DH12: Data Sharing 3 Years on – From Baby to Toddler...

Katherine Tucker, Roche

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DH13: From SDTM to Displays, through ADaM & Analysis Results Metadata, a Flight on Board Metadata Airlines

Omar Sefiani & Stéphane Bouget, Boehringer Ingelheim
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Data Visualisation

DV01: Interactive Visualisation for Precision and Translational Medicine
Christof Gaenzler, PerkinElmer
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DV02: Communicating Results with R & Shiny
Mika Mäkinen, Roche
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DV03: Interactive Data Visualisation and Exploration Using the Loon R Package
Adrian Waddell, Roche
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DV04: Clinical Graphs Using SAS
Sanjay Matange, SAS
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DV05: A Cost-effective Data Visualisation Using Base SAS
Kevin Kane, PHASTAR
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WINNER DV06: Interactive Visualisation of Linked Data
Tim Williams, UCB
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DV07: Clinical Data in Business Intelligence
Mike Collinson, Oracle Health Sciences Consulting
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DV08: End-to-end Data and Metadata: It’s Not Only a Dream, It’s a Reality
Gerald Neveu, Danone Research
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DV09: Concepts and Strategies for Developing Effective Data Visualisation
Rebecca Bates, GCE Solutions
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Industry Starters

IS01: Adventures in Data Science
Kieran Martin, Roche
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IS02: The Hardships of Finding your Way in Biometrics
Evi Creebsburg, OCS Consulting
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IS03: How Well Can you Speak SAS or is What you See What you Get?
Bahatska Yuliia, inVentiv Health
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WINNER IS04: The Data Detective: Hints and Tips for Independent Programming QC
Bethan Thomas, PRA Health Sciences
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IS05: Good Programming Practice and its Importance in Metadata
Jennifer Chin, Eisai, Mark Foxwell, PRA & Shafi Chowdhury, Shafi Consultancy
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IS06: Get Kitted Out – A Practical Guide to SAS Certifications, MOOCs and Hands-on Experience
Hannes Engberg Raeder, PRA Health Sciences
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IS07: Developing Better Training Guides
Alastair Scarlett, d-Wise
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Management

MA01: Developing Agile and Adaptive Processes in the Modern Fast-packed Data Rich World
Sam Warden, d-Wise, Chris Price, Roche & Shafi Chowdhury, Shafi Consultancy

MA02: Dancing with the Grizzly – An interactive workshop to define the perfect SCE (Statistical Computing Environment) Implementation Project for a Global Biopharmaceutical Company
James McDermott, Ab Tartarus & Jean-Marc Ferran, Qualiance

MA03: Enhanced Data Analytics: A Reality Check of Aspiration, Current Progress and Organisational Implementation
Christian Mueller, Roche, Sascah Ahrweiler, Bayer, Leo Valms, Quintiles & Jari Ahvenainen, Aastat

 

Professional Development & Training

PD01: The Process and Development of the SAS/STAT® Programmer Role from a Retroactive Perspective
Jonathan Bishop, PRA Health Sciences
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PD02: Size Doesn't Matter – Little Fish Can be Leaders Too
Jennifer Dootson, d-Wise
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PD03: Why Programmers Make the Best Functional Leads: Do Statisticians Really Know Best?
Tom Ward, PPD
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PD04: Continuous Improvement for TFL Production
Caroline Terrill, CROS NT
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PD05: How to Enjoy Working in Virtual Teams
Petra Auclair & Antje Rossmanith, Roche
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PD06: Program-level Programming Strategy – Oh, I Wish I’d Thought of That Beforehand!
Jennie McGuirk, ICON
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PD07: Desired Competencies for Speed and Efficiency (in the Drug Approval Process)
Ramesh Satyavarapu, inVentiv Health
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WINNER PD08: So You’re a Superstar Programmer…Why You Still Might Not Be Picked for the Team
Diana Stuart, Veramed
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PD09: On the Fast Lane to a Successful Submission – A Lead Programmer’s Guide to Efficient, High-quality Submission Programming Deliverables
Michael Reich, Hannes Engberg Raeder, James Witt & Doris Kolb, PRA Health Sciences
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PD10: Is the Statistical Programming Process Lean Enough?
Simon Jennings, ICON
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PD11: Integration & Innovation: Pharma-CRO Relationship
Nalin Gupta, GCE Solutions
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Poster Presentations

PP01: SAS Grid Migration – Challenges, Solutions and Learnings
Amol Waykar, Eric Brinsfield & Alistar Dootson, d-Wise
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PP02: Efficiently Converting Datasets to Vertical Structure using Metadata
Thevaki Mahadevan, ICON
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PP03: CONSORT Diagram: Doing it with SAS
Anusha Mallavarapu & Dean Shults, Cytel
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PP04: Using Metadata to Drive Standards, Speed, Consistency and Quality in Reporting
Shafi Chowdhury, Shafi Consultancy & Daniel Boisvert, Biogen
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PP05: Early Data Review
Graham Oakley, ICON
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PP06: Developing MDR Metadata Requirements for Operational Implementation
Andy Richardson & Scott Bahlavooni, d-Wise
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WINNER PP08: The Tortoise Versus the Hare – And the Winner is...
Meena Rahman, AstraZeneca & Rebecca Leivers, PAREXEL
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PP09: Creating a PDF File Containing Multiple Outputs
Spencer Renyard, PHASTAR
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PP10: Non-printable and Special Characters? BYTE Me!
Louise Sims, PHASTAR
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PP11: Automating ADaM
Helen Hart & Christof Binder, Roche
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PP12: Implementation Effort Estimation: Important Aspects
Patrick Warnat, HMS Analytical Software
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PP13: Shopping for your CRF: Combining Sources for a Simple Data Collection Browser
Rod Bower, Roche
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PP15: Automating Frequency Tables with ClinXport SAS Macro Package
Loizos Nicolaou & Julien Vanwinsberghe, ClinBAY
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PP16: Crossover to High-quality Graphics
Simon Clancy, Sue McKendrick & Martin Clancy, Quanticate
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PP17: Stylising your SAS graph – A Needs-based Approach
Jérôme Lechere, Novartis
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PP18: Fast and High-quality Validation Process
Andrea Parodi, Dmitri Petratchenko & Alessia Sacco, Valos
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PP19: The Development of Standards Management Using EntimICE-AZ
Shyamprasad Perisetla & Per-Arne Stahl, AstraZeneca
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PP20: Fast Track to Domain: SDTM.PC and SDTM.PP
Lina Ulkjær Jørgensen, Novo Nordisk
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PP21: Reflections on the Effects of Data Pooling
Catharina Dahlbo, Capish Nordic
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PP22: KeyDan – A Data Anonymisation Tool
Cathy Scoupe, Stéphane Chollet & Mathilde Laffitte, Keyrus Biopharma
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PP23: Constructing Interoperable Study Documents From A Semantic Technology-based Repository
Colin de Klerk, UCB Biosciences
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PP24: Scientific Data Curation: Efficiently Extracting Structured Data from Publications
Rupali Desai & Nand Kishore Rawat, Cytel
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Regulatory Agencies

FDA
Electronic Submissions, Study Data Standardization Efforts, and the Impact on Regulatory Review in CDER, FDA
Lilliam Rosario, FDA

IDIBAPS
Regulatory Statistical Implications of "Fast Track Approval"
Ferran Torres, IDIBAPS (Hospital Cliníc de Barcelona)

EMA
IDMP/SPOR Project: A New Way of Conducting Business
Francisco Peñaranda, EMA

 

Regulatory

RG01: What is High-quality Study Metadata?
Sergiy Sirichenko & Max Kanevsky, Pinnacle 21
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WINNER RG02: Planning for Data-reporting Processes for Submission: Key Considerations
Parag Shiralkar, Interdependent Consultant
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RG03: Japanese Electronic Submission in CDISC Formats
Takashi Kitahara, Novartis
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RG04: What Auditors Want
Angelo Tinazzi & Cédric Marchand, Cytel
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RG05: Case Study in Support of German Payer Evidence
Frank Senk, AstraZeneca
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Real-world Evidence

RW01: The Playbook: Real-world Data to Real-world Intelligence
Laurie Rose & Robert Collins, SAS
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WINNER RW02: Real-world Evidence: A Comparison Between Countries
Edith Heintjes & Jetty Overbeek, PHARMO Institute
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RW03: Proposal of a General Macro Framework for Propensity-score Matching
Holger Langkabel, Roche
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RW04: An Algorithm to Distinguish Between COPD and Asthma
Berber Snoeijer & Jetty Overbeek, PHARMO Institute
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RW05: Considerations in the Use of Propensity Scoresin Observational Studies
Lawrence Rasouliyan, Estel Plana & Jaume Aguado, RTI Health Solutions
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RW06: What Have I Done? Analysis Specifications Document for Retrospective Database Studies
Knut Mueller, UCB Biosciences
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Software Demonstrations

SD01: Data Standards Governance
João Gonçalves, Business & Decision Life Sciences
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SD02: Fast Track to Define-XML v2.0 – SDTM and ADaM
Jörn Bilow, Entimo
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SD03: Pinnacle 21 Enterprise – Facilitating eSubmission Preparation
Max Kanevsky, Pinnacle 21
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SD04:  EnForeSys – An Advanced Patient Enrolment Forecaster with Monte Carlo Simulations
Ritika Yadav & Swechhya Bista, Cytel
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SD05: Blur Software Demonstration
Cathal Gallagher, d-Wise
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SD06: encapsia™ – Providing Real-time, Interactive Visualisations of Clinical Data
Jon Carter, Cmed
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SD07: SAS Studio – Getting to Know SAS Studio
Andy Bayliss, SAS
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SD08: Standard Safety Visualisation Set-up Using Spotfire
Michaela Mertes, Roche
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Statistics & Pharmacokinetics Programming

SP01: Standard Methods for Analysis and Reporting of VAS or NRS Derived Pain Relief Response Scores
James Johnson, Flexion Therapeutics
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SP02: Probability Plots as an Instrument for Comparing Distributions
Holger Langkabel, Roche
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WINNER SP03: Upstream with Your Statistician and a Data Visualisation Paddle
Nick Cowans, Veramed
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SP04: Multiplicity Issues in Clinical Trials – Look at it with a Magnifying Glass!
Madhusudhan Bandi, Cytel
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SP05: Using Graphics to Review and Present PK/PD Data for Maximum Impact
Shafi Chowdhury, Rajwanur Rahman & Marco Ackermann, Shafi Consultancy
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Trends & Technology

TT01: Does the Concept of a ‘Sentient Enterprise’ Apply to the Clinical Trial Execution Process?
Peter Grolimund, Teradata
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TT02: SCAPROC Impact Analysis – Providing QA and Compliance Insights
Sandeep Juneja, Ben Bocchicchio & Stijn Rogiers, SAS
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TT03: An Update from the PHUSE Working Group on Cloud Adoption in the Regulated Life Sciences Industry
Tony Hewer, Medidata Solutions
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TT04: Challenges and Opportunities with the Implementation of a Single-instance Cloud Research Platform
Doug Bain, eClinicalHealth
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TT05: Generating Analysis Results and Metadata – Report from a PHUSE CS Project
Marc Andersen, StatGroup & Marcelina Hungria, DIcore Group
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TT06: Reflect on Your Data
Peter Tormay & Henrik Drews, Capish Nordic
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WINNER TT07: R Beyond Statistics
Namrata Deshpande, Cytel
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