PUBLICATIONS
At Qualiance, we believe in knowledge sharing to progress the Industry and regularly speak at events and conferences. We try to publish our work at every opportunity. Please find below our contribution to the community.
ANALYTICS
Long-term effectiveness and safety of daily growth hormone therapy in Japanese children with Noonan syndrome: a post-marketing surveillance study – Muroya et al. (Endocrine Journal, 2025)
This analysis of GHT in Noonan Syndrome patients in Japanese children was supported by Qualiance (Co-Author) who provided statistical support to produce the underlying analyses.
Comparative Outcomes of GH Treatment in Pediatric Idiopathic Short Stature and GH Deficiency – Phillip et al. (JES, 2025)
This comparitive analysis of GHT in GHD and ISS patients is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Paediatric Growth Hormone Programs. Qualiance (Co-Author) provided statistical support to produce the underlying analyses.
Using RWD to Inform the Next Study: a Case Study – JM. Ferran (PHUSE Strasbourg EU Connect, 2024)
This conference presentation shares the background of an analysis of RWD from a patients registry for ISS patients, which was then used to inform the next study on predictors of response to GHT in this disease area.
Clinical Predictors of Good/Poor Response to Growth Hormone Treatment in Children with Idiopathic Short Stature – Dauber et al. (HRP, 2024)
This analysis of Clinical Predictors for response in ISS patients is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Paediatric Growth Hormone Programs. Qualiance (Co-Author) provided statistical support to produce the underlying analyses.
Handling missing data in exploratory analyses using RWD, ”Collect the data you love or love the data you get” – A case study – JM. Ferran (PHUSE Birmingham EU Connect, 2023)
This conference presentation shares the background of an analysis of RWD from a patients registry for AGHD patients for CV risk, where missing data was handled carefully to produce robust analyses.
Long-term Effectiveness and Safety of GH Replacement Therapy in Adults ≥60 Years: Data From NordiNet® IOS and ANSWER – Biller et al. (JES, 2023)
This analysis of GHT in Eldery Patients patients is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Adult Growth Hormone Programs. Qualiance (Co-Author) provided statistical support to produce the underlying analyses.
Early GH Treatment Is Effective and Well Tolerated in Children With Turner Syndrome: NordiNet® IOS and Answer Program – Backeljauw et al. (JCEM, 2023)
This analysis of GHT for Turner Syndrome Patients patients is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Paediatric Growth Hormone Programs. Qualiance (Co-Author) provided statistical support to produce the underlying analyses.
Reduced CV risk with long-term GH replacement in AGHD: data from two large observational studies – Höybye et al. (Endocrine Connections, 2022)
This analysis of CV risk in AGHD patients is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Adult Growth Hormone Programs. Qualiance (Co-Author) provided statistical support to produce the underlying analyses.
Pregnancy outcomes in women receiving growth hormone replacement therapy enrolled in the NordiNet® International Outcome Study (IOS) and the American Norditropin® Studies: Web-Enabled Research (ANSWER) Program – Biller et al. (Pituitary, 2021)
This analysis of pregnancy outcomes in women receiving growth hormone is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Paediatric Growth Hormone Programs. Qualiance (Acknowledgement) provided statistical support to produce the underlying...
Long-term safety of growth hormone treatment in childhood: Two large observational studies NordiNet ® IOS and ANSWER – Sävendahl et al. (JCEM, 2021)
This long-term safety analysis is based on the pooled analysis of the NordiNet IOS (Europe) and ANSWER (US) Paediatric Growth Hormone Programs. Qualiance (Acknowledgement) provided statistical support to produce the underlying analyses.
STATISTICAL COMPUTING ENVIRONMENTS
Danone Nutricia Research’s SCE Roadmap Towards Efficiency and Automation – P. Vervuren & JM. Ferran (PHUSE Copenhagen SDE, 2023)
This conference presentation summarises Danone Nutricia Research. 5-year SCE journey and how they leveraged their resources and LSAF to stay up to date and provide a modern environment to their users community. Qualiance co-led this project, and this paper highlights...
Managing a Custom-built SCE: The Janssen Journey for SPACE – M Bertolino & JM. Ferran (PHUSE Belfast EU Connect, 2022)
This conference presentation provides insight into Janssen's custom-built SCE journey and lessons learned along the way.
R and SAS working together – DNR’s experience moving to LSAF 5.3 – P. Vervuren & JM. Ferran (PHUSE EU Connect (Virtual), 2021)
This conference presentation summarises the approach and findings in implementing R within LSAF 5.3 at Danone Nutricia Research over a period of 9 months in 2021. Qualiance co-led this project, and this paper highlights the approach we followed with Danone, as well as...
Manage TFLs Development in Life Science Analytics Framework 5.3 using SAS and R code – JM. Ferran & S. Rogiers (PHUSE EU Connect (Virtual), 2020)
This conference presentation highlights the findings from a prototype in LSAF 5.3 around the management of both SAS and R programs using the new TFL metadata module in combination with workflows.
Checking the Completeness of Validated SAS Programs in LSAF – H. Ament & JM. Ferran (PHUSE EU Connect (Virtual), 2020)
This conference presentation outline the implementation of a simple Development Life Cycle in LSAF, supporting tools to check dependencies and report on status and how it is used at Danone Nutricia Research.
Migrating to LSAF – The Danone Nutricia Research Journey – P. Vervuren & JM. Ferran (PHUSE EU Connect, Amsterdam, 2019)
This paper summarises an LSAF implementation run with Danone Nutricia Research over a period of 10 months in 2018. Qualiance co-led this project, and this paper highlights the approach we followed with Danone, as well as some recommendations and learnings.
Managing Program Development Life Cycles in SAS LSAF – JM. Ferran & B. Klein (PHUSE Utrecht SDE, 2019)
Managing program development life cycles efficiently is often a challenge in clinical study reporting. This conference presentation details the implementation of a simple Development Life Cycle in LSAF and how it is used at Ferring Pharmaceuticals.
Managing Program Development Life Cycles in SAS LSAF – JM. Ferran (PHUSE US Connect, Raleigh, 2018)
Managing program development life cycles efficiently is often a challenge in clinical study reporting. Manual processes often lead to inconsistencies and audit findings. This conference paper details the implementation of a simple Development Life Cycle in LSAF.
Review and Highlights of the 2016 Survey of the Top 20 Biopharmaceutical Companies’ Statistical Computing Environments – JM. Ferran & J. McDermott (PHUSE SDE, Basel, 2017)
This presentation features main findings and trends from a survey conducted for Novartis with 15 of the top 20 pharmaceutical companies about their Statistical Computing Environments, their usage and evaluation.
SDD APIs: Extending the Capabilities of SAS Drug Development – JM. Ferran (SAS SDD Briefing, Copenhagen, 2014)
This presentation features the SDD APIs and implementation examples, as well as highlights from the latest API release including possible applications.
DATA ANONYMISATION & SHARING
Clinical Document Anonymization and Disclosure, a Global Perspective – JM. Ferran (CBI Data Disclosure Conference, Coral Gables, 2020)
This presentation provides an overview of regulatory requirements across agencies with regards to data sharing, reviews the FDA Clinical Data Summary Pilot, and provides some insight into 2020 main announcements to come in the field.
European Medicines Agency Policy 0070: An Exploratory Review of Data Utility in Clinical Study Reports for Academic Research – JM. Ferran & S. Nevitt (BMC Medical Research Methodology, 2019)
This publication features the highlights of a review of 13 academic research reports, with the goal to better understand Data Utility in anonymised CSRs. Their different research purposes have been analysed and classified against the required data to support them.
European Medicines Agency Policy 0070: An Exploratory Review of Data Utility in Clinical Study Reports for Academic Research – S. Nevitt & JM. Ferran (6th SAS CTDT Forum, Heidelberg, 2019)
This presentation features the highlights of a review of 13 academic research reports, with the goal to better understand Data Utility in anonymised CSRs. Their different research purposes have been analysed and classified against the required data to support them.
EMA, Health Canada, FDA and PMDA: Four Agencies Tackle Data Sharing. Synergies and Differences – JM. Ferran & L. Roberts (PHUSE US Connect, Baltimore, 2019)
There are various policies around Data Sharing of submission documents which are effective or in preparation. This paper explores how four agencies' policies differ or align in terms of processes and anonymisation requirements.
Anonymising Clinical Data –Key Principles, Methods and Considerations – JM. Ferran (EFSPI/PSI Webinar, 2017)
This Industry presentation features key principles around risk quantification, use of different disclosure contexts and reference populations. It also provides insights into the PHUSE De-Identification Standards for SDTM 3.2.
Integrating the New EMA Requirements on Public Disclosure in the Study Conduct Process – JM. Ferran (PHUSE SDE, Copenhagen, 2016)
This presentation compares requirements between ClinicalTrials.gov and EudraCT and discusses the process of publishing study results in multiple registries. It also tackles the future of Policy 0070 and how sponsors could consider updating their processes.
PHUSE De-Identification Working Group: Providing De-Identification Standards to CDISC Data Models – JM. Ferran et al. (PHUSE Annual Conference, Vienna, 2015)
This conference paper explains in more details the different principles of the PHUSE De-Identification Standard for SDTM 3.2, their rationale and how to use them in practice. It is authored by five key members of the PhUSE Data Transparency Working Group.
Data De-Identification: New Challenges for the Data Scientist – JM. Ferran (PHUSE SDE, Copenhagen, 2015)
This presentation features examples of re-identification attacks, key principles on risk quantification and use of reference populations. A research request also illustrates how researchers use shared data.
Data Transparency: Important Considerations for Data De-Identification – JM. Ferran (PHUSE SDE, London, 2014)
This presentation discusses Data Sharing requests handled through a portal and details related processes, along with basic "safe-harbour" data de-identification principles to consider.
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