European Statistical Forum - Relatori

Jens-Otto received a diploma in Mathematics in 1993. In 1994 he started his career in Biostatistics at Grünenthal GmbH in Aachen. Here he worked in several therapeutical areas like gynecology and pain. Later on he became a specialist in the Phase 1 area. In 2005 he started to UCB (legacy Schwarz Pharma) as a Project Biostatistician in Phase 1. With the restructuring at UCB in 2008 Jens-Otto became the Head EU Biostatistics supervising Biostatisticians located in Monheim (Germany) and Brussels. Since 2016 he is also the Head of the East Asia Biostatistics of UCB. UCB’s key indications are CNS and immunology. From 2017 to 2019  Jens-Otto was the Head of Statistical Sciences – Bone & New Diseases at UCB Biosciences GmbH. Currently Jens-Otto is holding the position of a SSI Business Operations Excellence Senior Lead at UCB Biosciences GmbH. 

Lisa has over 20 years of experience in the clinical research industry. In her current role, Lisa is responsible for the management of the biostatistics team including the development professional growth, supervision of the quality of deliverables and outputs, as well as the management of processes for biostatistical activities to ensure they are up-to-date and aligned with the business need and regulatory requirements. Lisa’s areas of expertise include DSMB support, submission studies, integrated summaries, writing Statistical Analysis Plans and contributing to Clinical Study Reports. She has worked in a variety of therapeutic areas and has particular expertise in respiratory, cardiovascular, infectious diseases and oncology. She is a committee member of ESF (European Statistical Forum) and is also a member of several associations including PSI (Statisticians in the Pharmaceutical Industry) and EFSPI (European Federation of Statisticians of the Pharmaceutical Industry). Lisa has been a contributing author on scientific articles in cardiology, diabetes and oncology.

Marco Eigenmann started his career in the pharmaceutical industry joining Novartis in 2020 as a Principal Biostatistician in the Immunology, Hepatology and Dermatology (IHD) department. In his role, Marco has been supporting several programs in late phase development (phase 2b to phase 4) across the Dermatology and Rheumatology therapeutic areas. Marco holds a Master degree in mathematics from ETH Zurich and has a PhD in statistics from the same university. During his PhD Marco specialized in causal inference and graphical models. Marco’s current interests include the development and standardization of causal methodologies in drug development, effective scientific communication using interactive tools such as R Shiny, and machine learning.

Dr Victoria Strauss is TAM Chapter Head, Global Biostatistics & Data Science in Boehringer-Ingelheim, and a honorary research in University of Oxford.She specifies in real world evidence methodology including incorporating real world evidence methodology into clinical trials, propensity score, trial emulation, bias minimization in real world data. Prior to join BI, she was the lead Statistician in pharamaco and device epidemiology research group in Centre for Statistics in Medicine, University of Oxford. She is a faculty member of “ISPE pre-conference course: machine learning ” and was a co-lead in the UK NIHR routine data SIG.

Biography available soon

Since graduating from ENSAI (Biostatistics M. Sc.) 10 years ago, Guillaume has been immersing himself in precision medicine.
Data-driven, he is passionate about answering scientific questions and making sure we convey the right message to stakeholders, both internally & externally.
He feels very fortunate to have had the chance to work with various kinds of OMICs data and leverage the power of biomarkers to strengthen drug development.
He also feels incredibly lucky to have worked in a diverse set of settings, be it in academia (UCSF, U.S.), in a biotech (Enterome, France) or in the pharmaceutical industry (BMS, Servier & AstraZeneca, France & Sweden). He now works as a Statistical Science Director for AstraZeneca in Gothenburg, Sweden.

Apart from his day job at AstraZeneca, Guillaume teaches a course about OMICs data analysis at ENSAI (www.ensai.fr), is actively involved in the ENSAI alumni association (www.ensai.org) and is a mentor for Article 1, a non-profit organization promoting equal opportunity (https://article-1.eu/) and together with Nicole Krämer, he leads the EFSPI/PSI Biomarkers Special Interest Group.

Dr. Li is a statistician and computational biologist by training with more than twelve years of work experience in statistical methodology development and analysis in the fields of biomarker biostatistics, precision medicine, and statistical genomics. His expertise includes biomarker statistics and omics data science with applications in drug discovery and development. Some of his work has been published in high profile journals. Dr. Li is US Head of Statistics and Data Science at PharmaLex, a global specialized service provider for the pharma, biotech, and MedTech industries. He received his doctoral degree in computational biology from Cornell University and was a Postdoctoral Research Fellow in the Department of Biostatistics at Harvard School of Public Health.

Biography available soon

Oliver Pain is a biostatistician within the Statistical Sciences and Innovation Predictive Analytics team at UCB Pharma. He also holds a Sir Henry Wellcome Postdoctoral Research Fellowship at King’s College London. Oliver’s research mainly leverages results from genome-wide association studies (GWAS) and Bayesian machine learning methodology to calculate ‘polygenic scores’ predicting complex health-related outcomes. Currently at UCB, Oliver and colleagues have developed the ‘Polygenic Score Knowledge Base’ – a platform for integrating genetic data into clinical trials to improve their efficacy and efficiency.

Dr. Kathryn Rough is an Associate Epidemiology Director at IQVIA with over 13 years of experience in healthcare research, including 4 years of creating deep learning-based health technologies at Google. She has extensive experience with machine learning/deep learning, evaluation of health technologies, comparative safety/effectiveness studies, observational research, and methods for causal inference. Kathryn was one of the core development team members for the Apple/Google privacy-preserving COVID-19 Exposure Notification System. She also worked at the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital, conducting comparative safety research using health insurance claims data. She received her doctoral degree in Epidemiology from Harvard University, with concentrations in pharmacoepidemiology and infectious disease.

Konstantinos (Kostas) is an Associate Director of Data Science in Novartis’ Advanced Exploratory Analytics group and his main areas of interest are machine learning based biomarker discovery, subgroup identification, and development of digital endpoints. He obtained his PhD in statistical machine learning from the Department of Computer Science of the University of Manchester. Afterwards he spent many years as post-doctoral researcher on developing novel methodologies for analysing: self-reported epidemiological data with Manchester’s Health e-Research Center, clinical trials data for personalised medicine with AstraZeneca and digital healthcare data for digital biomarker development with Roche. He is member of the editorial board of the Machine Learning Journal (MLJ) and vice-chair of the technical committee on Statistical Pattern Recognition Techniques of the International Association for Pattern Recognition (IAPR) and more information about his work can be found at: https://sechidis.netlify.app/