Non-alcoholic fatty liver disease is a condition that affects 25% of the population. Non-alcoholic steatohepatitis (NASH) is a progressive form of the disease that can lead to severe complications such as cirrhosis and hepatocellular carcinoma. Despite its high prevalence, there are no drugs currently approved to treat NASH. The drug development pipeline in NASH is very active, yet most assets do not progress to Phase 3 trials and those that do reach Phase 3 often fail to achieve the endpoints necessary for approval by regulatory agencies. Amongst other reasons, the methodological and operational features of traditional clinical trials in NASH might impede optimal drug development. In this regard, platform trials might be an attractive complement or alternative to conventional clinical trials by using a master protocol which allows for evaluating multiple investigational medicinal products concurrently or sequentially with a single, shared control arm. Through Bayesian interim analyses, these trials allow early exit of drugs from the trial based on success or futility, while providing participants better chances of receiving active compounds through adaptive randomization. Overall, platform trials represent an alternative for patients, pharmaceutical companies and clinicians in the quest for accelerating pharmacologic treatment for NASH.
Marta Bofill Roig, Pavla Krotka, Carl-Fredrik Burman, Ekkehard Glimm, Stefan M. Gold, Katharina Hees, Peter Jacko, Franz Koenig, Dominic Magirr, Peter Mesenbrink, Kert Viele & Martin Posch. On model-based time trend adjustments in platform trials with non-concurrent controls, August 2022. DOI: 10.1186/s12874-022-01683-w
Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for a treatment entering the trial at a later time point, the control group is divided into concurrent controls, consisting of patients randomised to control when that treatment arm is in the platform, and non-concurrent controls, patients randomised before. Using non-concurrent controls in addition to concurrent controls can improve the trial’s efficiency by increasing power and reducing the required sample size, but can introduce bias due to time trends.
Stefan M. Gold, Marta Bofill Roig, J. Jaime Miranda, Carmine Pariante, Martin Posch & Christian Otte. Platform trials and the future of evaluating therapeutic behavioural interventions, January 2022. DOI:10.1038/s44159-021-00012-0
Therapeutic interventions are typically evaluated in individual, parallel group trials, which are time consuming and provide limited information on comparative efficacy. Clinical psychology should leverage advances in other fields to improve and accelerate the evaluation process by adopting more efficient platform trials. Platform trials could have a transformative effect on clinical psychology more broadly by increasing the speed with which treatment effects are estimated, getting effective interventions into clinical care more quickly, and providing much needed comparisons between different interventions for the same condition. This would ultimately enable patients, care providers and payers to make better informed decisions and achieve better outcomes.
Olivier Collignon, Anja Schiel, Carl-Fredrik Burman, Kaspar Rufibach, Martin Posch, Frank Bretz. Estimands and Complex Innovative Designs, Clinical Pharmacology & Therapeutics, March 2022. DOI:10.1002/cpt.2575
Since the release of the ICH E9(R1) document in 2019, the estimand framework has become a fundamental part of clinical trial protocols. In parallel, complex innovative designs have gained increased popularity in drug development, in particular in early development phases or in difficult experimental situations. While the estimand framework is relevant to any study in which a treatment effect is estimated, experience is lacking as regards its application to these designs. In a basket trial for example, should a different estimand be specified for each sub-population of interest, defined for example by cancer site? Or can a single estimand focusing on the general population (defined, for example, by the positivity to a certain biomarker) be used? In the case of platform trials, should a different estimand be proposed for each drug investigated? In this work we discuss possible ways of implementing the estimand framework for different types of complex innovative designs. We consider trials that allow adding or selecting experimental treatment arms, modifying the control arm or the standard of care, and selecting or pooling populations. We also address the potentially data-driven, adaptive selection of estimands in an ongoing trial and disentangle certain statistical issues that pertain to estimation rather than to estimands, such as the borrowing of non-concurrent information. We hope this discussion will facilitate the implementation of the estimand framework and its description in the study protocol when the objectives of the trial require complex innovative designs.
Elias Laurin Meyer, Peter Mesenbrink, Cornelia Dunger-Baldauf, Ekkehard Glimm, Yuhan Li, Franz König, EU-PEARL (EU Patient-cEntric clinicAl tRial pLatforms) Consortium. Decision rules for identifying combination therapies in open-entry, randomized controlled platform trials, Pharmaceutical Statistics, ISSN 1539-1612, DOI: 10.1002/pst.2194
Platform trials have become increasingly popular for drug development programs, attracting interest from statisticians, clinicians and regulatory agencies. Many statistical questions related to designing platform trials—such as the impact of decision rules, sharing of information across cohorts, and allocation ratios on operating characteristics and error rates—remain unanswered. In many platform trials, the definition of error rates is not straightforward as classical error rate concepts are not applicable. For an open-entry, exploratory platform trial design comparing combination therapies to the respective monotherapies and standard-of-care, we define a set of error rates and operating characteristics and then use these to compare a set of design parameters under a range of simulation assumptions. When setting up the simulations, we aimed for realistic trial trajectories, such that for example, a priori we do not know the exact number of treatments that will be included over time in a specific simulation run as this follows a stochastic mechanism. Our results indicate that the method of data sharing, exact specification of decision rules and a priori assumptions regarding the treatment efficacy all strongly contribute to the operating characteristics of the platform trial. Furthermore, different operating characteristics might be of importance to different stakeholders. Together with the potential flexibility and complexity of a platform trial, which also impact the achieved operating characteristics via, for example, the degree of efficiency of data sharing this implies that utmost care needs to be given to evaluation of different assumptions and design parameters at the design stage.
Luca Sforzini ✉, Courtney Worrell, Melisa Kose, Ian M. Anderson, Bruno Aouizerate, Volker Arolt, Michael Bauer, Bernhard T. Baune, Pierre Blier, Anthony J. Cleare, Philip J. Cowen, Timothy G. Dinan, Andrea Fagiolini, I. Nicol Ferrier, Ulrich Hegerl, Andrew D. Krystal, Marion Leboyer, R. Hamish McAllister-Williams, Roger S. McIntyre Andreas Meyer-Lindenberg, Andrew H. Miller, Charles B. Nemeroff, Claus Normann, David Nutt, Stefano Pallanti, Luca Pani, Brenda W. J. H. Penninx, Alan F. Schatzberg, Richard C. Shelton, Lakshmi N. Yatham, Allan H. Young, Roland Zahn, Georgios Aislaitner, Florence Butlen-Ducuing, Christine Fletcher, Marion Haberkamp, Thomas Laughren, Fanni-Laura Mäntylä, Koen Schruers, Andrew Thomson, Gara Arteaga-Henríquez, Francesco Benedetti, Lucinda Cash-Gibson, Woo Ri Chae, Heidi De Smedt, Stefan M. Gold, Witte J. G. Hoogendijk, Valeria Jordán Mondragón, Eduard Maron, Jadwiga Martynowicz, Elisa Melloni, Christian Otte, Gabriela Perez-Fuentes, Sara Poletti, Mark E. Schmidt, Edwin van de Ketterij, Katherine Woo, Yanina Flossbach, J. Antoni Ramos-Quiroga, Adam J. Savitz and Carmine M. Pariante. A Delphi-method-based consensus guideline for definition of treatment-resistant depression for clinical trials. Molecular Psychiatry, December 2021 DOI: 10.1038/s41380-021-01381-x
Criteria for treatment-resistant depression (TRD) and partially responsive depression (PRD) as subtypes of major depressive disorder (MDD) are not unequivocally defined. In the present document we used a Delphi-method-based consensus approach to define TRD and PRD and to serve as operational criteria for future clinical studies, especially if conducted for regulatory purposes. We reviewed the literature and brought together a group of international experts (including clinicians, academics, researchers, employees of pharmaceutical companies, regulatory bodies representatives, and one person with lived experience) to evaluate the state-of-theart and main controversies regarding the current classification. We then provided recommendations on how to design clinical trials, and on how to guide research in unmet needs and knowledge gaps. This report will feed into one of the main objectives of the EUropean Patient-cEntric clinicAl tRial pLatforms, Innovative Medicines Initiative (EU-PEARL, IMI) MDD project, to design a protocol for platform trials of new medications for TRD/PRD.
Marta Bofill Roig, Pavla Krotka, Carl-Fredrik Burman, Ekkehard Glimm, Katharina Hees, Peter Jacko, Franz Koenig, Dominic Magirr, Peter Mesenbrink, Kert Viele, Martin Posch.On model-based time trend adjustments in platform trials with non-concurrent controls, ArXiv.org, Cornell University (2022) November 2021, arxiv.org/abs/2112.06574
Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for treatments entering the trial at later time points, not all patients in the control group are randomised concurrently. The control group is then divided into concurrent and non-concurrent controls. Using non-concurrent controls in addition to concurrent controls can improve the trial’s efficiency, but can introduce bias due to time trends.
L Cash-Gibson, JM Pericàs, C Spiertz, E van de Ketterij, E Molero, F Patalano, D Kalra, A Ussi, A Van Dessel, J Genescà, EU-PEARL: Changing the paradigm of clinical trials in Europe, European Journal of Public Health, Volume 31, Issue Supplement_3, October 2021, ckab165.657, doi.org/10.1093/eurpub/ckab165.657
Recently, innovative clinical trial designs have been proposed, which have the potential to revolutionize clinical research. Whereas classical trials mostly evaluate only one investigational drug, platform trials embed various trials under a shared master protocol to enable the evaluation of multiple interventions for a disease or condition. Platform trials have mostly been used to evaluate cancer therapies, but also recently for COVID-19. The EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project aims to expand the use of platform trials as the backbone of drug development.
Britt A.E.Dhaenens, Rosalie E.Ferner, D. Gareth Evans, Guenter Heimann, Cornelia Potratz, Edwin van de Ketterij, Angela M.Kaindl, Geesje Hissink, Charlotte Carton, Annette Bakker, Marco Nievo. Eric Legius; Rianne Oostenbrink. Lessons learned from drug trials in neurofibromatosis: A systematic review, European Journal of Human Genetics, July 2021. doi.org/10.1016/j.ejmg.2021.104281
Neurofibromatosis (NF) is the umbrella term for neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2) and schwannomatosis (SWN). EU-PEARL aims to create a framework for platform trials in NF. The aim of this systematic review is to create an overview of recent clinical drug trials in NF, to identify learning points to guide development of the framework. We searched Embase, Medline and Cochrane register of trials on October 1, 2020 for publications of clinical drug trials in NF patients. We excluded publications published before 2010, systematic reviews, secondary analyses and studies with <10 patients. Data was extracted on manifestations studied, study design, phase, number of participating centres and population size. Full-text review resulted in 42 articles: 31 for NF1, 11 for NF2, none for SWN. Most NF1 trials focused on plexiform neurofibromas (32%). Trials in NF2 solely studied vestibular schwannomas. In NF1, single-arm trials (58%) were most common, and the majority was phase II (74%). For NF2 most trials were single-arm (55%) and exclusively phase II. For both diseases, trials were predominantly single-country and included five centres or less. Study population sizes were small, with the majority including ≤50 patients (74%). In conclusion, NF research is dominated by studies on a limited number out of the wide range of manifestations. We need more trials for cutaneous manifestations and high-grade gliomas in NF1, manifestations other than vestibular schwannoma in NF2 and trials for SWN. Drug development in NF may profit from innovative trials on multiple interventions and increased international collaboration.
Britt A. E. Dhaenens, Rosalie E. Ferner, Annette Bakker, Marco Nievo, D. Gareth Evans, Pierre Wolkenstein, Cornelia Potratz, Scott R. Plotkin, Guenter Heimann, Eric Legius & Rianne Oostenbrink. Identifying challenges in neurofibromatosis: a modified Delphi procedure, European Journal of Human Genetics, April 2021. DOI:10.1038/s41431-021-00892-z
Neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2) and schwannomatosis (SWN) are rare conditions with pronounced variability of clinical expression. We aimed to reach consensus on the most important manifestations meriting the development of drug trials. The five-staged modified Delphi procedure consisted of two questionnaires and a consensus meeting for 40 NF experts, a survey for 63 patient representatives, and a final workshop. In the questionnaires, manifestations were scored on multiple items on a 4-point Likert scale. The highest average scores for NF experts deciding the ‘need for new treatment’ were for malignant peripheral nerve sheath tumour (MPNST) (4,0) and high grade glioma (HGG) (3,9) for NF1; meningioma (3,9) for NF2 and pain (3,9) for SWN. The patient representatives assigned high scores to all manifestations, with plexiform neurofibroma being highest in NF1 (4,0), vestibular schwannoma in NF2 (4,0), and pain in SWN (3,9). Twelve experts participated in the consensus meeting and prioritised manifestations. MPNST was ranked the highest for NF1, followed by benign peripheral nerve sheath tumours. Tumour manifestations received highest ranking in NF2, and pain was the most prominent problem for SWN. Patient representative ratings for NF1 were similar to the experts’ opinions, except that they ranked HGG as the most important manifestation. For NF2 and SWN, the patient representatives agreed with the experts. We conclude that NF experts and patient representatives consent to prioritise development of drug trials for MPNST, benign peripheral nerve sheath tumours, cutaneous manifestations and HGG for NF1; tumours for NF2; and pain for SWN.
Elias Laurin Meyer, Peter Mesenbrink, Tobias Mielke, Tom Parke, Daniel Evans and Franz König on behalf of EU-PEARL (EU Patient-cEntric clinicAl tRial pLatforms) Consortium (2021). Systematic review of available software for multi-arm multi-stage and platform clinical trial design, BioMed Central. DOI: 10.1186/s13063-021-05130-x
In recent years, many highly specialized software packages targeting single design elements on platform studies have been released. Only a few of the developed software packages provide extensive design flexibility, at the cost of limited access due to being commercial or not being usable as out-of-the-box solutions. In this publication, its authors argue that both an open-source modular software and a collaborative effort will be necessary to create software that takes advantage of and investigates the impact of all the flexibility that platform trials potentially provide.
Nigel Stallard, Lisa Hampson, Norbert Benda, Werner Brannath, Thomas Burnett, Tim Friede, Peter K. Kimani, Franz Koenig, Johannes Krisam, Pavel Mozgunov, Martin Posch, James Wason, Gernot Wassmer, John Whitehead, S. Faye Williamson, Sarah Zohar & Thomas Jaki (2020) Efficient adaptive designs for clinical trials of interventions for COVID-19, Statistics in Biopharmaceutical Research, DOI: 10.1080/19466315.2020.1790415
The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial’s scientific validity or integrity. In this paper we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs.
Key w0rds: Adaptive trial Group sequential design, Multi-arm multi-stage, Platform trial, SARS-CoV-2, Pandemic research
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|