Clinical Trials Methodology

Fundamentals in Clinical Trials, EJP RD partners and collaborators (ECRIN, UKA and APHP) recommend the following three freely accessible online courses:

EURORDIS Medical research and development (Very Beginner level)

1. 1. 1. Short description: Many aspects of medical research concern problem solving and asking the right questions. In this course, you will be able to learn more about the process of medicine discovery, such as pre-clinical testing, clinical trials and the methodology and statistics used in medicine development, including evidence-based medicine, blinding and study protocol. This course also includes training on the development of medicines for small populations.
      2. Topics covered: Study design, controlled trial, randomisation, endpoints, criteria of inclusion, analysis of results
      3. Provider: EURORDIS
      4. Level: Very beginner
      5. Language: English
      6. Cost: Free
      7. Venue: Online
      8. Duration: 1-2 days
      9. Certificate of completion: Available/ Free

Design and Interpretation of Clinical Trials (Basic level)

1. 1. Short Description: The course will explain the basic principles for the design of randomized clinical trials and how they should be reported. In the first part of the course, students will be introduced to terminology used in clinical trials and the several common designs used for clinical trials, such as parallel and cross-over designs. The course will also explain some of the mechanics of clinical trials, like randomization and blinding of treatment. In the second half of the course, clinical trials analysis and interpretation will be explained. Finally, the course will provide a review the essential ethical consideration involved in conducting experiments on people.
   2. Topics covered: Types of Trial Designs: parallel, crossover, group allocation, factorial, large simple, equivalency, non-inferiority, and adaptive designs.
   3. Provider: Johns Hopkins University via Coursera
   4. Level: Basic
   5. Language: English
   6. Cost: Free
   7. Venue: Online
   8. Duration: 6 weeks; 2-3 h per week
   9. Certificate of Completion: Available/ Paid

Study Designs in Epidemiology (Advanced level)

1. 1. Short Description: the course is an Introduction to Study Designs: Ecological and Cross-Sectional Studies
   2. Topics covered: The main epidemiological study designs, including cross-sectional and ecological studies, case-control and cohort studies, as well as the more complex nested case-control and case-cohort designs. The final module is dedicated to randomised controlled trials, which is often considered the optimal study design, especially in clinical research. You will also develop the skills to identify strengths and limitations of the various study designs. By the end of this course, you will be able to choose the most suitable study design considering the research question, the available time, and resources.
   3. Provider: Imperial College London via Coursera
   4. Level: Advanced
   5. Language: English
   6. Cost: Free
   7. Venue: Online
   8. Duration: 4 weeks; 2-4 h per week
   9. Certificate of Completion: Available/ Paid

The intermediate course aims to provide a specialized statistical training at an intermediate level, tailored for a diverse audience. Its primary goal is to fill the knowledge gap in clinical trial methodologies, ensuring a comprehensive understanding among participants. The target audience encompasses healthcare professionals, basic researchers, patient/patient representatives, CRO representatives, industry professionals, and methodologists/statisticians.

Topic 1: Statistical Methodology for Very Small (and Very Large) Studies (VIDEO)
Speaker’s Presentation (PDF)
Description: Using data from various clinical trials and other studies, methodology and statistical concepts are presented that remain solid also when studies are very small, such as in rare diseases, or very large. In the former case, we need to ensure that the statistical methodology leads to reliable estimates, without being riddled with computational instability. In the latter case, we need to ensure that running times remain feasible. Specific attention is devoted to the potential of surrogate markers and the omnipresent problem of incomplete data. The focus is on concepts and illustration, not on mathematical detail.  
Lecturer: Prof. Geert Molenberghs – Hasselt University and KU Leuven, Belgium 

Geert Molenberghs (geert.molenberghs@uhasselt.be, geert.molenberghs@kuleuven.be) is Professor of Biostatistics at UHasselt and KU Leuven. He received a degree in mathematics (1988) and a Ph.D. in biostatistics (1993) from UAntwerpen. He published on surrogate markers in clinical trials, and categorical, longitudinal, and missing data. He was Editor for Applied Statistics, Biometrics, and Biostatistics, and is currently Executive Editor of Biometrics. He was President of the International Biometric Society. He is Fellow of the American Statistical Association, received the Guy Medal in Bronze from the Royal Statistical Society,  and held visiting positions at Harvard. He is founding director of the Center for Statistics at UHasselt and of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (UHasselt and KU Leuven). He received research funding from FWO, IWT, the EU (FP7), U.S. NIH, U.S. NSF, UHasselt, KU Leuven, ECDC, and EMA. He is member of the Belgian Royal Academy of Medicine. He has been active (as advisor, researcher, and communicator) in the SARS-CoV-2 pandemic response. He has taken part in various grant funded research programs on rare diseases, including IDEAL, EJP RD, ERDERA (future), and RealiseD (future).  

Topic 2: Bayesian Methods in Clinical Research (VIDEO)
Speaker’s Presentation (PDF)
Description: In the last two decades, the Bayesian approach has become increasingly popular in virtually all application areas. The approach is especially known for its capability to tackle complex statistical modeling tasks and for providing an intuitive outcome of the statistical analysis. In Session 1, Bayes Theorem will be explained using a simple illustration. The construction of the prior distribution and the computation of the posterior distribution will then be illustrated using a variety of examples.  In Session 2, we indicate the popularity of the Bayesian approach in various research areas, not only medical areas. In Session 3, we show the application and usefulness of the Bayesian approach in the area of randomized clinical trials. The ultimate aim of this crash course is to introduce the participants smoothly into Bayesian statistical methods and trigger them to apply them in practice. The course is partly based on the Wiley book of Lesaffre and Lawson, published in 2012 and entitled: Bayesian Biostatistics and the Chapman & Hall edited book Bayesian Methods in Pharmaceutical Research by E. Lesaffre, G, Baio and B. Boulanger published in 2020.
Lecturer: Prof. Emmanuel Lesaffre – Professor emeritus Biostatistics – KU Leuven 
Emmanuel Lesaffre is emeritus Professor at the Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat) of the Catholic University of Leuven, Belgium and is honorary professor of Erasmus MC at Rotterdam, the Netherlands. He has more than 600 peer-reviewed publications in biostatistics. He was one of the three founding editors of International Statistical Modelling Journal, he has been Associate Editor of Biometrics and of Biostatistics, and statistical advisor of various clinical journals. He is the founding chair of the International Statistical Modelling Society (IWSM), and a former President of the International Society for Clinical Biostatistics (ISCB). He is an ASA and ISI Fellow, and is honorary member of ISCB and IWSM. He (co)-authored nine books, with the latest book entitled: Bayesian Statistics applied to pharmaceutical research, an edited book with editors E. Lesaffre, G. Baio and B. Boulanger, published in Chapman and Hall, 2020. 

Topic 3: Early Phase Trial designs in Rare diseases (VIDEO)
Speaker’s Presentation (PDF)
Description: The development of novel therapies for rare diseases involves many challenges due to small and heterogeneous patient populations, limited knowledge of natural history data, ethical constraints, etc. This tutorial will focus on statistical methods for early phase clinical trials. It will start with some background on the drug development issues for rare diseases. After that, we will consider adaptive phase 1 trial designs that facilitate learning of the underlying dose–toxicity relationship while protecting study participants from exposure to overly toxic doses. We will discuss data analysis issues following these designs and the approaches for making decisions on the maximum tolerated dose (MTD). We will also cover adaptive phase 1/2 trial designs that incorporate toxicity and early efficacy (response) in dose-finding objectives and discuss the added value of such designs. Some additional important topics on early development clinical trials will be highlighted.  

Lecturer: Alex Sverdlov is a Neuroscience Disease Area Statistical Lead at Novartis. He earned his BSc in Applied Mathematics from V.N. Karazin Kharkiv National University, Ukraine, MSc in Statistics from University of Maryland, Baltimore County, and PhD in Information Technology with Concentration in Statistical Science from George Mason University. With 17 years of career in the biopharmaceutical industry, Alex has been actively involved in methodological research and applications of innovative statistical approaches in drug development. His most recent work involves design and analysis of clinical trials of novel treatment modalities such as digital therapeutics and gene therapies. Alex has co-authored over forty refereed articles, edited three monographs, and co-authored a book “Mathematical and Statistical Skills in the Biopharmaceutical Industry: A Pragmatic Approach” (CRC Press/Chapman & Hall, 2019).  

Topic 4: Interim Analysis, Adaptations and Master Protocols (VIDEO)
Speaker’s Presentation (PDF)
Description: In this lecture, we will focus on the role of interim analysis to react to new data emerging from inside and outside the trial. How to incorporate an interim analysis in a confirmatory clinical trial without inflating the risk of declaring a treatment as efficient when it is not. Regulatory guidelines document stresses that for confirmatory clinical trials one of the key features is the strict control of the type 1 error risk. The concept of group sequential designs will be explained which allow both early stopping for efficacy and futility. Adaptive designs will be discussed which allow the adaptations such as sample size reassessment, treatment selection or change of allocation ratio. Both regulatory guidance documents and the Consort extension on adaptive design (Dimairo et al. 2020) will be presented. The latter includes several adaptive case studies in its explanatory document. Finally, the concept of master protocols will be presented highlighting some of the key statistical concepts (Koenig et al. 2024, Meyer et al 2020), especially how to increase efficiency by data sharing concepts.

Lecturer: Franz König (franz.koenig@meduniwien.ac.at) is Associate Professor at the Center for Medical Data Science (CeDAS) at the Medical University of Vienna MUW), Austria. He has a master and PhD in statistics from the University of Vienna. The CeDAS cooperates in numerous international research consortia involving academia, industry and regulatory authorities. Franz is currently the head of the working group on adaptive designs at the Institute of Medical Statistics. Furthermore, he is the coordinator of the PhD “Programme Medical Informatics, Biostatistics and Complex Systems” since 2022. 

He is currently member of ethics committee of the Medical University of Vienna and was also of the ethics committee of the community of Vienna (Ethikkommission der Stadt Wien). From 2008 till 2010 he was seconded to the European Medicines Agency (London, UK) as statistical expert in the Unit Human Medicines Development and Evaluation. His main research interests are multiple testing, adaptive designs, interim analyses, master protocols and data safety monitoring boards (DSMB). Franz König was associate editor of the journal “Statistics in Biopharmaceutical Research”. Before he served as Guest Editor for Special Issues in Biometrical Journal and Statistics in Medicine. Franz König has published >150 papers (see https://orcid.org/0000-0002-6893-3304). 

He has been involved in several international research projects both on methodological and applied studies. For example he was the work package leader on « adaptive designs » in the EU FP7- funded research project IDEAL (Grant Agreement No 602552) and deputy coordinator of an EU Horizon 2020 funded Marie Curie ITN network IDEAS on early drug development studies (Grant Agreement No 633567). He was work package co-lead in the IMI project Pearl on platform trials (start November 2019). He was also member of the drafting team which developed a CONSORT extension for randomised trials using an adaptive design (ACE –project) which were published in BMJ and trials. 

Topic 5: Key Solutions to Model Longitudinal Natural History Data with  
Application in Ataxia Diseases (VIDEO)
Speaker’s Presentation (PDF)
Description: Modelling longitudinal natural history data is challenging and need some special knowledge when reaching efficient results. In the presentation I will discuss some common approaches and their assumptions, invalidating these analysis strategies. I will recommend to use progression modelling via Linear of nonlinear mixed effects modelling. Nonlinear mixed effects modelling will be important, when observations of the primary endpoint variable are affected by ceiled or floored effects, as with SARA score in the ataxia field, best corrected visus acuity in ophthalmology etc. I will further show and comment on how these methods can be used to inform sample size justification of a comparative clinical trial. As I will derive my arguments mainly along ataxia examples, I will avoid formal description. 

Lecturer: Prof. Dr. Ralf-Dieter Hilgers studied mathematics at RWTH Aachen University. He finished his doctoral thesis at the statistical faculty of the University of Dortmund in 1991. In 2000 he received the Venia Legendi for Medical Statistics at the University of Cologne. Since 2001 he is head of the Institute of Medical Statistics (IMSA) at the Medical Faculty, RWTH Aachen University. His research interest is in optimal design of experiments, randomizations procedure and clinical trials. Since 1987 he gives biostatistical advice to clinical and experimental trials in all clinical and preclinical areas. Professor Hilgers teaches 300 students in different bio-scientific areas per year and is responsible for the education of investigators in clinical trials. He also acts as reviewer for methodological and clinical journals. He receives funding form German funders like BMBF, DFG and also private partners. According to his main research activity, he coordinates the IDeAl project funded by the European Community within the 7th framework program (GA N° 602552) (www.ideal.rwth-aachen.de) form 2013-2017, which established new methodologies for small population group trials. Currently, he is co‐lead of WP20 “Accelerating the validation, use and development of innovative methodologies tailored for clinical trials in RDs“ within the H2020 funded European Joint Program on rare diseases (GA N° 825575). He is co‐lead of WP4 of the European Rare Disease Research Coordination and Support Action consortium (ERICA) project serving for the ERN’s. In the future he will be involved in training activities of the EUDERA project starting from November 2024.

In partnership with IOR (ERN-BOND), APHP (Necker) and UKA, EJP RD delivered and will continue to deliver advanced webinars addressed to people willing to conduct clinical research in rare diseases with the objective to train them in terminology, communication and understanding of RD clinical trial methodology. The webinars are organized as a series of lectures presented by experts in the specific topics.
The webinars listed below have taken place so far, covering the following topics:

Does randomization matter in Clinical Trials? (VIDEO)
Speaker’s Presentation (PDF)
Lecturer: Prof. Ralf-Dieter Hilgers- RWTH Aachen University, Germany
The objectives of the webinar are:

1. To learn about other randomization procedures beyond the most frequently applied permuted bock randomization in a fixed sample scenario,
2. To understand properties of different randomization procedures beyond balancing sample sizes,
3. To argue, which randomization procedure fits best in a particular trial setting,
4. To know about the potential advantages of randomization from design to analysis of clinical trials in RD.

Composite endpoints including patient relevant endpoints Quality of Life (VIDEO)
Speaker’s Presentation (PDF)
Lecturer: Dr. Johan Verbeeck- Hasselt University, Belgium.
The objectives of the webinar are:

1. To learn about procedures to combine multiple endpoints and its limitations,
2. To argue that generalized pairwise comparison is a suitable method to combine any number and type of endpoints (including QoL) in small samples,
3. To understand the properties and the flexibility of the class of generalized pairwise comparison tests,
4. To know the potential advantages and disadvantages of designing a clinical trial in rare disease with generalized pairwise comparisons primary analysis.

The Statistical Evaluation of Surrogate Endpoints in Clinical Trials (VIDEO)
Speaker’s Presentation (PDF)
Lecturer: Prof. Geert Molenberghs- Hasselt University and KU Leuven, Belgium
The objectives of the webinar are:

1. To get an overview of the methodological developments in surrogate endpoint evaluation over the last 30 years,
2. To understand practical use,
3. To understand promise and limitations,
4. To understand how they can be useful in the context of rare diseases

Statistical and Operational Challenges with Master Protocols (VIDEO)
Speaker’s Presentation (PDF)
Lecturer: Prof. Franz König – Medical University of Vienna.
The objectives of the webinar are:

1. To learn about master protocols and the differences between basket, umbrella and platform trials
2. To understand the difference between traditional drug development programs and more complex designs like platform trials using a master protocol
3. To understand the key statistical challenges with respect to multiplicity and sharing control data across the platform trial
4. To know the potential advantages and disadvantages of designing and running platform trials in rare disease