Introduzione

Medical and pharmaceutical statistics have become a highly specialized field with technically advanced methods for exposure and response modeling, dose-finding, adaptive study designs, etc. However, teams sometimes struggle with issues and phenomena that appear much more basic but have a massive impact in practice.

Do we see patterns in data where there are none? Can we distinguish association from causation? How reproducible are subgroup findings, or scientific results in general?

The resolution of these and similar issues is often difficult in interdisciplinary settings, as it requires a blend of statistical, common-sense, and communicative skills.
It is however of vital importance that the results generated from the analyses of the clinical study data is properly understood and interpreted because wrong conclusions can result in a waste of time, effort, increase of costs and can compromise the safety and well-being of patients.

The European Statistical Forum (ESForum) shall include presentations focusing on various aspects of statistical reasoning:

  • Reproducibility
  • Hidden bias
  • Multiplicity (endpoint selection, subgroups, etc.)
  • Choice of scales and effect measures
  • Prediction, attribution, estimation
  • Association vs. causation
  • Statistical significance vs. clinical relevance
  • Pattern detection
  • The interpretation of inferential statistics both in the frequentist as well as in the Bayesian framework.

Methodological approaches to the above issues as well as case studies and practical experiences will be presented.

Scientific Board
Jens-Otto Andreas - SSI Business Operational Excellence Senior Lead at UCB Biosciences GmbH
Lisa Comarella - Director Biostatistics at Alira Health Biometrics
Giacomo Mordenti - Head of Biostatistics & Data Management Europe at Daiichi Sankyo Europe GmbH
Marc Vandemeulebroecke - Global Group Head for Dermatology at Novartis Biostatistics

Who should attend?
This statistical conference is addressed to statisticians, pharmacometricians, regulatory affairs specialists, academia and other experts interested in the field belonging to: Pharmaceutical, and Biotechnology companies, CROs, Universities/Hospitals, Academic Research.

Programma
25 October 2022
08:30
09:00
Registration
09:00
09:10
Welcome from the Scientific Board
09:10
09:50
Medical Statistics: only science, or also some art?
Robert Hemmings - Consultant at Consilium Salmonson and Hemmings

Clinical trials aim to provide reliable evidence of efficacy and safety to support approval of experimental medicines and to inform prescribers as to their use. To generate reliable data, designs aim to minimise bias, including through pre-specification of methods for analysis. Pre-specification has come to include not just identification of a primary endpoint, but families or hierarchies of secondary endpoints that are subject to study-wise type I error control. Also, investigations that aim to explore limitations in the data and to gain a full understanding of the dataset. The benefits of pre-specification are clear but, given the complexities of a clinical trial dataset, are there also risks?

Interpretation of clinical trial data can rely on statistical rules and algorithms, with only pre-specified analyses subject to error control being considered reliable for decision making and for labelling. Information on secondary endpoints outside of the hierarchy (or analysed after a test in the hierarchy has failed) and other, scientifically justifiable, investigations identified only post hoc can be dismissed as unreliable. Is this too restrictive, potentially ignoring what can be learned from a full interrogation of the dataset, from other trials, and from a biological and pharmacological understanding of the experimental treatment? The talk will consider whether a strict application of statistical rules preclude a well-informed, proportionate interpretation of clinical trial data with potentially detrimental consequences for drug approvals and labelling.

09:50
10:30
The Value of Biostatistics in the Interpretation of Clinical Studies
Hans Ulrich Burger - Senior Director at Hoffmann-La Roche Ltd

The role of biostatistics in the planning and conduct of a clinical study is established and pretty undisputed today.

Biostatistician’s role in the interpretation of results is however still undervalued. With the availability of more and more simple to use tools, however, correct planning and execution of a clinical trial becomes easier and less of an issue and problems in the interpretation of study results more dominant. This presentation will focus on issues in the interpretation of study results, for example the challenges between predefined controlled analyses versus the use of exploratory analyses or the need to understand the data in detail before the interpretation or the many different aspects to be considered when interpreting study results; and it will highlight the value of biostatistics there.

The talk will discuss the different aspects of clinical trial interpretation in the example of external control analyses in more details.

10:30
11:00
Coffee break
11:00
11:50
Cases of Multiplicity in Clinical Development – Same Zoo, Different Animals
Cornelia Kunz - Methodology Statistician at Boehringer Ingelheim Pharma GmbH & Co. KG
Frank Fleischer - Head of Therapeutic Area and Methodology Statistics at Boehringer Ingelheim Pharma GmbH & Co. KG

From a traditional perspective, multiplicity in clinical trials has related to advanced testing procedures in confirmatory trials with respect to considering a hierarchy or multitude of endpoints. In recent years it has become obvious that multiplicity in clinical development may have very different meanings ranging from indications, populations, and treatment groups up to having combined criteria for (GoNoGo) decision making and number of trials. The common theme is that statistical reasoning needs to play a key role in considering, evaluating and judging upon these aspects both from a companies’ and a regulators perspective.

In this presentation we will address and present some typical examples of multiplicity in clinical development and trial design. A special focus will be given to two areas. The first one is multiplicity in early phase trials and in particular combined decision criteria considering multiple endpoints and populations. Here examples and principles will be presented on how to address this topic in the context of GoNoGo decision making. This will also be contrasted against the classical way of dealing with this aspect in confirmatory settings.

The second area to be discussed is examples for designing Phase 3 programs with multiple pivotal trials, endpoints, doses and/or interim analyses. Here complications can arise for example, from pooling data across trials for testing secondary endpoints or from changing testing strategies after interim analyses.

11:50
12:30
Planning of Clinical Trials Using Unconditional Probabilities
Andy P Grieve - Statistical Research Fellow at UCB Pharma

Traditionally, the planning of clinical trials has been based on considerations of the power of a test of a given alternative hypothesis. Power as we understand it was based on ideas introduced by Neyman and Pearson in 1933. In 1939, Jeffreys pointed out that if the true value was unknown, so was the power and he suggested to understand the true power of a study the conditional power values should be averaged with respect to their prior probabilities or uncertainties, leading to an unconditional probability ot power. More recently O’Hagan and Stevens introduced the concept of assurance, again an unconditional probability.

In this talk I review recent ideas in the use of these unconditional probabilities in planning trials.

12:30
13:30
Networking lunch
13:30
14:10
Bayesian Statistics for Rare Diseases: from incorporation of auxiliary data to prediction of disease trajectory
Bruno Boulanger - Senior Director, Global Head Statistics and Data Science at PharmaLex

The small sample sizes in rare disease settings is a challenge for clinical trial design.

Bayesian adaptive trial methods are often the only rescue by allowing the cautious incorporation of auxiliary data, such as registry data,and other relevant information such as natural history to inform the trial itself. First a strategy with a one-arm trial augmented by the participants’ own natural history data will be envisaged. From such one-arm trial the predictive distribution of the future course of the disease in the absence of intervention will be derived. Patient response is then be defined by the degree to which post-intervention observations are unlikely with the predicted disease trajectory. Such one-arm trials offer obvious advantages in efficiency and ethical hazard but they cannot offer a protection against bias arising from the presence of “placebo effect,”. In the second part we’ll present the impact of various scenarios of placebo effects on one-arm responder studies, as well as two-arm versions that incorporate a small concurrent placebo group but still borrow strength from the natural history data and auxiliary data.

We will propose Bayesian changepoint models that specify a parametric functional form for the patient’s post-intervention trajectory, which in turn allow quantification of the treatment benefit in terms of the model parameters. Operating characteristics of the different scenarios will be presented.

It suggests that the two-arm responder and changepoint methods can offer protection against placebo effects, improving power while protecting the trial’s Type I error rate.

14:10
14:50
Generalized Pairwise Comparisons as a Statistical Method for Patient-Centric Medicine
Marc Buyse - Chief Scientific Officer at IDDI

Patient-centric medicine is in full swing, yet there are no statistical methods that allow patients to make individualized treatment decisions based on all relevant efficacy and toxicity outcomes. There has been much recent work on the new statistical method of “generalized pairwise comparisons” (GPC) to allow formal decisions to be made on the totality of the available information in a rigorous way. With GPC, all efficacy, toxicity and quality of life data from patients enrolled in clinical trials comparing various interventions can be used to analyse any number of prioritized outcomes of any type (binary, continuous, time to event, etc.) The method compares all possible pairs of patients formed by taking one patient from the experimental group and one patient from the control group of a randomized trial. A measure of the overall treatment effect, called the “Net Treatment Benefit” (NTB), is the difference between the probability that a patient taken at random in the experimental group has a better outcome than a patient taken at random in the control group. The interpretation of the NTB is simple, and as such it may facilitate patient-centric treatment choices. Other measures of treatment benefit have been proposed, including the win ratio and the win odds. All these measures of treatment benefit can be expressed as functions of standard measures in the case of a single variable and under some distributional assumptions (e.g., normality for continuous outcomes or proportional hazards for times to event). Several applications will be used to illustrate the interest of GPC over a wide range of clinical situations.

14:50
15:20
Coffee break
15:20
16:00
Use of Bayesian Predictive Power for Interim Decisions with Time-to-Event Endpoints
Rajat Mukherjee - VP Advanced Statistics and Data Science at Alira Health

In classical adaptive designs of RCTs with time-to-event (TTE) endpoints the conditional power (CP) is routinely used for making interim decisions such as sample size re-estimation, dose selection, population enrichment, etc. This CP is calculated under the assumption of constant and proportional hazard rates. Under non-proportionality and/or time dependent hazard, the CP can easily mis-inform decision makers and thus increase the chance of an incorrect interim decision. The use of Bayesian predictive power (PP) or the probability of success (PoS) have recently gained popularity due to the flexibility with respect to such assumptions. However, the complexity of calculations limits their use, especially when carrying out simulations to establish the operating characteristics of such adaptive designs. We discuss different ways and simplifications for the calculation of PP for TTE and discuss applications of PP in Bayesian as well as Hybrid adaptive designs. We will make a general comparison of different methods for PP calculations along with comparisons with the traditional CP under non-proportionality of hazards.

16:00
16:30
Round Table: Statistical Reasoning in Drug Development
16:30
16:40
Conclusions
Relatori
Jens-Otto Andreas
Info Scientific Board

Jens-Otto Andreas

SSI Business Operations Excellence Senior Lead at UCB Biosciences GmbH
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 Comarella
Info Scientific Board

Lisa Comarella

Director Biostatistics at Alira Health Biometrics
Lisa Comarella joined CROS NT in 2000 as a Statistician and Data Manager. In the past 19 years, she has developed a career in CROS NT as a Principal Statistician and since 2010 has been managing the team of biostatisticians as Director of Biostatistics. In her role as head of the department, Lisa is responsible for the management of statistics resources, supervision of the quality of deliverables, and contributing to complex and strategic projects as statistical lead. Lisa holds a Master’s degree in Statistics and Demographic Sciences from the University of Padua in Italy. She is a scientific committee chair for ESF – the European Statistical Forum, she is a member of associations of statisticians in Europe (PSI, EFSPI).
Giacomo Mordenti
Info Scientific Board

Giacomo Mordenti

Head of Biostatistics & Data Management Europe at Daiichi Sankyo Europe GmbH
After the degree in statistical sciences from the University of Florence (1998), Giacomo stared his career in drug development in Menarini where he was exposed to different therapeutic areas and development phases. In 2007 he moved to Geneva to join Merck Serono, where he led a biostatistical team dedicated to early development in oncology. In 2013 Giacomo joined Grunenthal as global head of Biostatistics. In 2016 he moved to medical device industry in Livanova as Global Head of Data Management and Statistics. In 2020 he joined Daiichi-Sankyo as Head of Biostatistcs and Data Management Europe. Since 2011 he is part of the scientific board of European Statistical Forum; since 2013 he is part of the European Statistical Leader group of EFSPI. His main research interests are in the field of Bayesian statistics, adaptive design and applications of data science techniques to drug development.
Marc Vandemeulebroecke
Info Scientific Board

Marc Vandemeulebroecke

Global Group Head for Dermatology at Novartis Biostatistics
Marc Vandemeulebroecke joined Novartis in 2006, coming from Schering AG in Berlin. He has been supporting development programs in early and late phase development across various disease areas (incl. Neuroscience, Gastrointestinal, Parasitology, Cardio-metabolic, Immunology, Transplant and Hepatology) as statistician and pharmacometrician. Currently he is Global Group Head for Dermatology. Marc holds a maîtrise in mathematics from the University Paris XI, a diploma in mathematics from the University of Münster, a PhD in mathematical statistics from the University of Magdeburg, and an MSc in PKPD modeling from the University of Manchester. He received the Gustav-Adolf-Lienert award from the German Region of the International Biometric Society (IBS) for his PhD thesis, which focused on adaptive designs. He co-authored various scientific publications and one R package and is Associate Editor of Pharmaceutical Statistics. Marc’s current interests include statistical graphics and machine learning.
Bruno Boulanger
Info Speaker

Bruno Boulanger

Senior Director, Global Head Statistics and Data Science at PharmaLex
Bruno has 25 years of experience in several areas of pharmaceutical research and industry including discovery, toxicology, CMC and early clinical phases. He holds various positions in Europe and in USA. Bruno joined UCB Pharma in 2007 as Director of Exploratory Statistics. Bruno is also since 2000 Lecturer at the Université of Liège, in the School of Pharmacy, teaching Design of Experiments and Statistics. He is also a USP Expert, member of the Committee of Experts in Statistics since 2010. Bruno has authored or co-authored more than 100 publications and co-edited one book in applied Bayesian statistics.
Hans Ulrich Burger
Info Speaker

Hans Ulrich Burger

Senior Director at Hoffmann-La Roche Ltd
Biography available soon
Marc Buyse
Info Speaker

Marc Buyse

Chief Scientific Officer at IDDI
Marc Buyse holds degrees from Brussels University (Belgium), Cranfield University (UK) and a ScD in biostatistics from the Harvard School of Public Health (MA). He is the founder of the International Drug Development Institute (IDDI) and of CluePoints, two companies offering biostatistical services in Europe and the US, and is Associate Professor of Biostatistics at Hasselt University (Belgium).
Frank Fleischer
Info Speaker

Frank Fleischer

Head of Therapeutic Area and Methodology Statistics at Boehringer Ingelheim Pharma GmbH & Co. KG
Frank has started in the biostatistics group at Boehringer Ingelheim in 2007. Initially, he worked as a project statistician in oncology, immunology and biosimilars. In 2016 he became one of the founding members of the methodology group at Boehringer-Ingelheim and served this team as the Head of Methodology Statistics from 2018. In 2021 he became the Head of Therapeutic Area and Methodology (TAM) Statistics. This group of data scientists is supporting clinical development teams regarding TA strategy, statistical methodology, statistical approaches to biomarker, pharmacokinetic and real-world evidence analyses as well as randomization and unblinding. Frank is also interested in agile methods and efficient organizational structures. He is passionate about collaborating across industry and with academia, in particular regarding the detection and promotion of data science talents via internships and thesis opportunities. Frank holds a PhD in statistics from Ulm University and MScs in mathematics and business mathematics from UW Milwaukee and Ulm University, respectively.
Andy P Grieve
Info Speaker

Andy P Grieve

Statistical Research Fellow at UCB Pharma
Biography available soon
Robert Hemmings
Info Speaker

Robert Hemmings

Consultant at Consilium Salmonson and Hemmings
Rob is a partner at Consilium, a consultancy partnership between Rob Hemmings and Tomas Salmonson, both long-standing contributors to the EU regulatory network.  Consilium supports companies in the design of clinical development programmes, the design, analysis and interpretation of clinical trials, regulatory strategy and regulatory interactions. Previously Rob worked at AstraZeneca and then for 19 years at the Medicines and Healthcare products Regulatory Agency, heading the group of medical statisticians and pharmacokineticists.  Rob is a statistician by background and was co-opted as a member of EMA’s CHMP for expertise in medical statistics and epidemiology.  Over 11 years at CHMP, Rob served as was Rapporteur for multiple products and was widely engaged across both scientific and policy aspects of the committee’s work.  Rob also chaired the CHMP’s Scientific Advice Working Party for 8 years and also chaired EMA expert groups on Biostatistics, Modelling and Simulation and Extrapolation.  Rob has co-authored multiple regulatory guidance documents, including those related to estimands, subgroups, use of conditional marketing authorisation, development of fixed-dose combinations, extrapolation, missing data and adaptive designs and continues to work on any and all aspects of evidence generation in respect of medicine’s development.
Cornelia Kunz
Info Speaker

Cornelia Kunz

Methodology Statistician at Boehringer Ingelheim Pharma GmbH & Co. KG
Cornelia Kunz is currently working as a methodology statistician at Boehringer Ingelheim (BI). After completing her PhD at the Institute of Medical Biometry and Informatics at the University of Heidelberg, Cornelia moved to the UK where she continued her research at Warwick Medical School. She then became a lecturer at Lancaster University’s Maths and Stats department while also receiving the MRC Career Development Award in Biostatistics. Her research interest lies in adaptive and group sequential designs as well as in multiple testing problems.
Rajat Mukherjee
Info Speaker

Rajat Mukherjee

VP Advanced Statistics and Data Science at Alira Health
Biography available soon
Contatti

Valeria Quintily
Project and Scientific Manager
valeria.quintily@lsacademy.com

Ilaria Butta
Events and Training Manager
ilaria.butta@lsacademy.com


Quote di iscrizione

€ 670,00* Early Bird fee until 27 September 2022
€ 790,00* Ordinary fee
€ 430,00* Freelance, Academy, Public Administration

Fee includes: seat at the conference, copy of presentations of Speakers who allow the distribution, networking lunch, coffee breaks, organisational office assistance, certificate of attendance.

* for Italian companies: +22% VAT


Informazioni utili

The conference will take place at:

H10 Marina Barcelona
Av. Bogatell, 64-68 – E08005 – Barcelona

H10 Marina Barcelona is 10 minutes walk from the beach and 5 minutes away you have the Olympic Village. Closer to the Metro stop, Bogatell: it is just 2 minutes behind the hotel and can take you into the city centre in 15 minutes, or you could even walk in about 30-40 minutes.

100 m from Bogatell metro station (Line 4)
300 m from Marina metro station (Line 1)
15 km from Barcelona-El Prat airport


COVID-19
LS Academy is aware of the evolving impact of COVID-19 and is committed to offering safe and secure face-to-face courses and conferences. From physical distancing, protect, detect, cleaning and hygiene.  LS Academy ensures that all our events are conducted in accordance with official government guidelines and regulations, understanding that these measures may vary and change as the situation evolves.

Edizioni Passate
2021
Application of Causal Inference in Drug Development
2020
Data Science and the Rise of New Analytical Techniques. The Evolution of the Clinical Development Paradigm and Biostatistics
2019
Statistical Methodology for the Assessment and Analysis of Risk and Safety Data in Clinical Development
2018
Innovative Clinical Trial Designs
2017
Statistical Methods for Rare Diseases and Special Populations
2016
Estimand and Missing Value
2015
Applications of Statistical Methodology in Early Drug Development
Acquista
Early bird
Acquistabile fino al 27/09/2022
670,00
Ordinaria
Acquistabile fino al 24/10/2022
790,00
Freelance - Accademia - Pubblica Amministrazione
Acquistabile fino al 24/10/2022
430,00
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<p style="text-align: center;"><strong>H10 Marina Barcelona<br />
</strong><span>Av. Bogatell, 64-68</span><br />
<span>E-08005 – Barcelona</span></p>

H10 Marina Barcelona
Av. Bogatell, 64-68
E-08005 – Barcelona

<p style="text-align: center;"><strong>H10 Marina Barcelona<br />
</strong><span>Av. Bogatell, 64-68</span><br />
<span>E-08005 – Barcelona</span></p>
<p style="text-align: center;"><strong>H10 Marina Barcelona<br />
</strong><span>Av. Bogatell, 64-68</span><br />
<span>E-08005 – Barcelona</span></p>
<p style="text-align: center;"><strong>H10 Marina Barcelona<br />
</strong><span>Av. Bogatell, 64-68</span><br />
<span>E-08005 – Barcelona</span></p>