CSS Winners

Anders Vidstrup: Cloud Adoption Project Lead, Emerging Trends & Technologies

Anders Vidstrup is Project Lead for the Cloud Adoption project. Since taking on this responsibility, he has worked tirelessly with the team to co-ordinate and develop a set of comprehensive guides for implementing cloud services for regulated use. The current 2019 Version 4 framework provides users with authoritative materials for ensuring that the full benefits of cloud services can be realised in our industry. We would like to take this opportunity to thank Anders for his efforts over the last year and we look forward to his continued contribution to the project in this important area.

Bev Hayes: Data Engineering Project Lead, Educating for the Future

Bev Hayes has been an active contributor and leader within the Educating for the Future Working Group. She was a driving force behind the formation of the Data Engineering project within the Working Group right from its inception. She has attended many SDEs and conferences and has been a tireless advocate for the project. Bev’s drive and keen desire to educate and be educated in future technologies has been an inspiration to many within the PHUSE community. Her ability to attract colleagues from different disciplines and collate their thoughts and experiences has brought new perspectives to common problems in the industry.

Maria Francomacaro: Data Consistency: SEND Datasets and the Study Report Project Lead, Nonclinical Topics

Maria Francomacaro has been nominated for a CSS Project Reward for her outstanding contributions in co-leading the Data Consistency project within the Nonclinical Topics Working Group. Maria has actively contributed to PHUSE projects, Nonclinical core team meetings and CSS breakouts for well over four years. With her co-lead, Fred Wood, Maria managed the organisation of the Data Consistency project with enthusiasm, strong team engagement and good project management practices, while motivating very innovative approaches to how the project team delivers value. Maria and her teammates took a little risk and had a lot of fun performing a live role play during a PHUSE webinar, to demonstrate the challenges in differences between a final study report and the associated SEND dataset, faced by data producers and reviewers. The team was the first to implement a “living white paper” approach, on the PHUSE Wiki, to deliver solutions to those challenges. Maria brings many years of experience in nonclinical toxicology, laboratory and project management to her volunteer work with PHUSE, and the Nonclinical Topics Working Group greatly appreciates her contributions.  

Lukasz Kniola: Data De-identification Standards Project Lead, Data Transparency

Lukasz Kniola is a Data Sharing Expert at Biogen and a member of the EMA Technical Anonymisation Group (EMA TAG). He joined the Data Transparency Working Group in 2016 and has contributed to and led important projects within the Working Group, in particular the analysis of the first-year Policy 0070 submissions. The EMA requested this analysis be presented at the first EMA TAG meeting in 2017, and the presentation was very well received. Lukasz currently leads the Data De-identification and Risk Analysis project and recently gave an industry workshop on this topic. Lukasz is a thought leader in the field of data transparency and is always available to discuss related topics, share his knowledge and provide input.

Bob Friedman: Code Sharing (Repository) Project Lead, Standard Analyses & Code Sharing

Bob Friedman helped review, comment and add new elements in the Script Metadata for Sharing White Paper. He created the R test case for using the script metadata and presented both the white paper and the use case in the March webinar. He also presented a poster at the PHUSE US Connect for the project. Bob has actively participated and contributed in the Code Sharing project, as well as ensuring cross-group communication to bring information on the script metadata project to the Nonclinical core and Nonclinical script groups.

Vincent Guo: Industry Experiences Submitting Standardised Study Data to Regulatory Authorities Project Lead, Optimizing the Use of Data Standards

Vincent Guo co-leads the Industry Experiences Submitting Standardized Study Data to Regulatory Authorities project. He has been instrumental in getting the project to its current state by taking an active role in leading the project’s team meetings, participating in four sub-team meetings, and curating content for the project deliverable, which is a white paper.

Lisa Brooks: Working Group Lead, Optimizing the Use of Data Standards

Lisa Brooks has been a highly active participant of the Working Groups Steering Committee. Her efforts in reviewing all new deliverables have been instrumental in driving forward the efforts of all the Working Groups. Lisa (along with Jane) has continued to guide the Optimizing the Use of Data Standards Working Group, with multiple projects delivering over the course of the last year.


Introduction to the CSS for First-time Attendees
Chris Price, PHUSE/Working Groups Director

Introduction and Overview
Lilliam Rosario, FDA/CDER

FDA Update on Technical Rejection Criteria for Study Data
Ethan Chen, FDA/CDER

The Impact of SEND Data on FDA Review of Nonclinical Studies
Matthew Whittaker, FDA/CDER

Safety Review: Approach & Tools
Alan Shapiro, FDA/CDER

Review-Ready Submissions: Helpful Tips when Preparing Submissions to FDA
Matilde Kam, FDA/CDER

CBER Nonclinical Study Data Review Considerations
Andrew O’Carroll, FDA/CBER

CBER (OVRR): Clinical Review Using Standardized Data
Darcie Everett, FDA/CBER

Closing Session
Chris Price, PHUSE/Working Groups Director

Let's Make a Knowledge Graph! - An Interactive, Hands-on Workshop
Tim Williams, UCB



Poster No. Poster Title Authors


A Joint Venture: DRG-XML & ODM4Submissions

Mike Hamidi, CDISC
Sam Hume, CDISC


TDF – Overview and Status of the Test Dataset Factory Project

Peter Schaefer, VCA-Plus


Artificial Neural Network for SDTM Mapping and Beyond

Sam Tomioka, Sunovion Pharmaceuticals
Kevin Lee, Clindata Insight


Common Adjudication Practices and Data Preparations for Event Outcomes

Cen Zhou, GlaxoSmithKline


#KillTFLs: Providing Analysis with Context

Chris Decker, d-Wise


Streamline Clinical Trial Operations Using Blockchain Technology

Mohit Juneja, LyfeScience
Rohit Banga, LyfeScience


Consolidating Study Outcomes in a Standardized SEND-compatible Structure

Philip Drew, PDS Consultants


If You Host It, They Will Come: Progress Made in the Implementation of the CPE Plan for the SACS Working Group

Jared Slain, Charles River Laboratories


Data Quality Findings from JumpStart

Jesse Anderson, FDA
David Jacobs, IBM


Vaccine Study Data Standardization Plan (SDSP) Experience

Ashokvardhan Gunuganti, Pfizer


Analysis of Clinical Pathology Parameters and Histopathologic Findings from eTOX

Robert Thomas, Lhasa


Ready, Set, Automate – Best Practices in Using Automated Tools for Validation

Gayathri Kolandaivelu, Janssen Research & Development
Eli Miller, Covance


Subject-level Variables for Oncology in the Subject-level Analysis Dataset (ADSL)

Madhusudhan Reddy Papasani,
Merck & Co. Inc.
Virginia Redner, Merck & Co. Inc.


Data Engineering Project of the Educating for the Future PHUSE Working Group

Vijay Pasapula, Gilead Sciences
Parag Shiralkar, Sumptuous Data Sciences



Introduction of Check Tool for SEND Datasets via the Checklist Prepared by the CJUG SEND Team

Yuta Sakakibara, Kyowa Hakko Kirin


The FDA’s Virtual Assistant: Utilizing Machine Learning for Automated Customer Service

Vannessa Williams, FDA
Tatiana Sokolova, IBM


Interactive Data Visualizations for Clinical Trials and Pharmacovigilance

Shiva Katepalli, Sunovion Pharmaceuticals
Sam Tomioka, Sunovion Pharmaceuticals


No ADaM is an Island – Planning Study Implementation of ADaM Programming

Alice Ehmann, Clinical Solutions Group
Kirsty Lauderdale, Clinical Solutions Group


The Truth About False Positives

Kristin Kelly, Pinnacle 21
Michael Beers, Pinnacle 21


How To Handle Increasing Volume of Data? Turn Up the Automation and Continuously Improve Processes

Jack Slattery, IBM
Christine Wang, FDA


Cloud Adoption in Regulatory Environments Project

Anders Vidstrup, NNIT


SEND 3.1 FOCID: Visualization and Validation

Tania Smith, Covance
Eli Miller, Covance


Adjudication Data – How Would You Map in SDTM?

Dana House, Syneos Health
Rama Kudaravalli, Syneos Health


SEND Data Factory

Bob Friedman, Xybion Corporation
Kevin Snyder, FDA


Drug-Induced Liver Injury (DILI) Classification Using US Food and Drug Administration (FDA)- Approved Drug Labeling and FDA Adverse Event Reporting System (FAERS) Data

Qais Hatim, FDA


Standard Analyses and Displays for Common Data in Clinical Trials: The Journey Continues

Nhi Beasley, FDA
Mary Nilsson, Eli Lilly


PHUSE GDPR Project: Data Transparency Working Group

Arlene Coleman, Pfizer
Shannon Labout, Data Science Solutions


Interactive Safety Review Using R Shiny Dashboard

Stella Guo, Bayer


A Doubly-programmed Analysis of the SEND 3.1 PoC LS Design Cardiovascular Safety Pharmacology Pilot

Jared Slain, MPI Research
Kevin Snyder, FDA


Identifying Hurdles for Submission of Electronic Nonclinical Data (SEND)

Janice Flori, Lilly
Lou Ann Kramer, CDISC


Computable Eligibility Criteria Using the Resource Description Framework (RDF)

Armando Oliva, Semantica


PHUSE CDISC Implementation Primer Project Overview and Update

Bess LeRoy, CDISC
Beate Hientzsch, HMS Analytical Software


Implementing SDTM and ADaM Data Standards for Trials Designed by Master Protocol

Yaling Teng, Amgen


Best Practices of ISS/ISE Dataset Development for
Submission to the FDA and PMDA: A PHUSE White Paper

Aatiya Zaidi, Gilead Sciences
Kapila Patel, Syneos Health


Data Visualization Working Group Project: Subject-level Data Review & Visualization – Final Results

Eric Herbel, Integrated Clinical Systems
Ingeborg Holt, IBM


Exploring the Efficacy of Agile at the FDA

Jack Slattery, FDA
Christine Wang, FDA




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