Novel model-based designs for early phase trials of medicines for children

Lead Research Organisation: Lancaster University
Department Name: Mathematics and Statistics

Abstract

In 2006 the European Union introduced legislation (Regulation on Medicines for Paediatric Use) to ensure that new medicines to be prescribed to children are subject to rigorous testing to establish their safety and effectiveness in this age group. Essential to this process is finding the optimal dose of the new medicine in children which balances potential benefits for health against the risks of an adverse side-effect. This dose will often differ from that used in adults because the ways in which the body breaks down and reacts to a drug may change subtly as it matures. Therefore using adult data to infer the optimal dose in children can lead to medicines being prescribed at ineffective or toxic doses, although this is currently often done because clinical trials are predominantly conducted in adults. It is imperative that prescribing decisions in children are supported by evidence from well-designed clinical trials in this patient group. The problem of designing paediatric trials is complex and the Fellow will engage throughout the project with parties with expertise in issues pertinent to developing medicines for children.

The main aim of this research is to devise statistical methods for trials intended to estimate the optimal dose of a medicine in children. Trials allocate each child participant a dose from a range of alternatives; data are then collected on dose received, the concentration of the drug in the blood over time and the patient's response to the drug (which may measure changes in their health). Statistical models are used to summarise how dose affects concentration and how concentration relates to response, and these models are updated as participants in the trial complete their treatment and more data become available. Based upon the updated models, each new patient enrolled in the trial is allocated the dose which is judged to maximise our learning about what the true optimal dose is.

Before the trial begins, data will often be available on how the drug performs in adults and this can influence investigators' beliefs about the optimal dose in children. This project will use methods to incorporate these existing data into the statistical models for the drug's effect in children with the intention of reducing the number of children needed to precisely estimate the optimal dose we seek. Clearly this dose may differ between young children and adolescents, for example. Methods will be extended to incorporate information on patient characteristics such as age, as well as considering adaptations necessary for successful application of the designs to trials of medicines for different diseases. Trial designs will also be proposed which shift to testing the drug's effectiveness at improving health relative to placebo once the optimal dose has been found, using all available data to make a final decision.

Technical Summary

The evidence basis for medicines prescribed to children is often limited with efficacy and dosage extrapolated from data generated by clinical trials in adults. Extrapolation is not straightforward as differences in physiology and function, not just size, separate children and adults; this may lead to dose recommendations being either inefficacious or so high as to be unacceptably toxic. The primary aim of this project is to develop novel dose-finding procedures to estimate the optimal dose of a medicine in children which can formally borrow strength from existing data in adults or data on a different indication in children. Further project aims are to engage with key stakeholders in the clinical trials community (regulators; industry; publicly funded clinical trials units; clinical pharmacologists; clinicians) to increase the relevance of this work.

Dose-finding procedures will use Bayesian non-linear hierarchical models to synthesise available data on dose, pharmacokinetics and pharmacodynamics with the aim of identifying a quantile of the implied dose-response relationship. As each new participant enters the trial dose-assignments are made according to a Bayesian decision theoretic criterion. The performance of procedures will be evaluated. Within the Bayesian paradigm, formal use of existing information on drug behaviour in adults is possible. For the hierarchical model, prior distributions will be constructed for model forms and parameters which correctly reflect the information contributed by adult data. Extensions to dose-finding procedures include incorporating covariates such as age, and relaxing constraints initially made by the hierarchical model. Trials which progress seamlessly to tests of efficacy on termination of dose-finding will be considered, combining information accrued in both stages to make a final decision. Opportunities for applying the proposed methodology to different therapeutic areas will be actively sought throughout the Fellowship.

Planned Impact

This research will develop statistical methods to address a highly relevant problem in health research, that of how to efficiently and accurately find the optimal dose of a medicine in children and confirm its efficacy. As such, research findings have the potential for high impact in terms of changing research practice as novel dose-finding procedures are implemented, and ultimately improving the health of children. Obtaining accurate estimates of the optimal paediatric dose which do not make extrapolations from adult data will improve child health by reducing the number treated at sub-therapeutic or toxic doses. Inaccurate paediatric dosing recommendations may be a significant problem in practice; 53 paediatric studies conducted between 1998-2002 in response to FDA requests for 33 drugs, resulted in new dosing information for seven of them [1]. The benefits of this research for child health would be felt in the short-term as new medicines begin development, since the early-phase trial designs this project proposes are intended to make efficient use of all available data in order to limit the burden of experimentation in children. Long-term benefits would become apparent as new drugs are approved for general use in children at efficacious doses.

The findings of this research activity will be of interest to all parties involved with developing and prescribing medicines to children, specifically the pharmaceutical industry, publicly funded clinical trials units, medicine regulatory bodies, clinicians and clinical pharmacologists. Particularly in the context of industry sponsored studies where paediatric drug development must follow PIPs, our designs may play a part in contributing high-quality evidence to support drug approval. The medical community would benefit as there would be new tools to improve the evidence basis for prescribing decisions. Furthermore, efficient early phase designs may make possible trials in circumstances hitherto unfeasible due to ethical or sample size constraints. Improving the quality of UK clinical research in children has been identified as a government priority [2], as illustrated by the establishment of the NIHR MCRN in 2004. The novel dose-finding designs in this proposal may also be applied more generally in adult studies with the methodology modified so that uninformative priors for models and parameters are used. Realistically, the rate of uptake of our new dose-finding methodology will be increased if user-friendly open-source packages exist for statisticians to implement them.

This project would have a positive impact on the Fellow's skills and future research career. Whilst undertaking this research, the Fellow would develop several transferable skills which could be applied in all employment sectors: leadership and project-management skills as the Fellow leads the project from inception to completion; communication skills as she communicates statistical results with non-statistical collaborators; and skills of managing relationships with inter-disciplinary collaborators.

[1]Roberts R, Rodriguez W, Murphy D, Crescenzi T. (2003) Pediatric drug labelling. Improving the Safety and Efficacy of Pediatric Therapies. JAMA 290: 905-911.
[2] MHRA/Department of Health Strategy on Medicines for Children. Accessed on http://www.mhra.gov.uk/Howweregulate/Medicines/Medicinesforchildren/index.htm#l6

Publications

10 25 50
 
Description Oxford course on Bayesian and adaptive methods for clinical trials
Geographic Reach National 
Policy Influence Type Influenced training of practitioners or researchers
 
Description Response to public consultation on European Medicines Agency's concept paper on extrapolation of efficacy and safety in medicine development
Geographic Reach Asia 
Policy Influence Type Participation in a national consultation
 
Description Training workshop on "Adaptive trial design for early phase trials".
Geographic Reach National 
Policy Influence Type Influenced training of practitioners or researchers
Impact I co-presented a 2 hour invited workshop on "Adaptive trial design for early phase trials" which was run on 21st May 2015 as part of the ECMC (Experimental Cancer Medicine Centres) Annual Network meeting in London. Participants were clinicians currently involved with conducting Phase I clinical trials of new medicines for cancer. The aim of the workshop was to disseminate state-of-the-art designs for such trials to encourage their uptake in practice. This will lead to more efficient trials which will be better placed to inform decisions about whether to continue development of medicines and the maximum safe dose they should be administered at.
 
Description Arthritis Research UK Clinical Studies (tranche II of funding for the MYPAN trial)
Amount £2,784 (GBP)
Organisation Versus Arthritis 
Sector Charity/Non Profit
Country United Kingdom
Start 11/2014 
End 10/2019
 
Description Methodology Research Programme
Amount £293,685 (GBP)
Funding ID MR/M013510/1 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 06/2015 
End 05/2018
 
Description Methodology Research Programme
Amount £49,000 (GBP)
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 04/2016 
End 03/2017
 
Description NIHR Research Methods Opportunity Funding Scheme
Amount £30,000 (GBP)
Funding ID NIHR-RMOFS-2013-03-05 
Organisation National Institute for Health Research 
Sector Public
Country United Kingdom
Start 01/2014 
End 12/2014
 
Description Network of Hubs for Trials Methodology Research
Amount £10,779 (GBP)
Funding ID N68 
Organisation Medical Research Council (MRC) 
Sector Public
Country United Kingdom
Start 10/2015 
End 12/2015
 
Title Bayesian prior elicitation software 
Description User-friendly and interactive statistical software (written in R) for eliciting expert prior opinion about parameters in a novel Bayesian model. The software was written to implement the novel Bayesian design of the MYPAN trial, a rare disease trial in rheumatology, but could be applied more broadly. The methods implemented by the software are the subject of a published statistical paper and a medical paper (currently under peer-review). 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact Software was used to formally elicit experts' prior opinion about treatments for a rare disease during a recent 2-day meeting (September 2013) for the MYPAN trial (a Bayesian multicentre randomized controlled trial of mycophenolate mofetil versus cyclophosphamide for the induction of remission of polyarteritis nodosa). 
URL http://www.lancaster.ac.uk/maths/about-us/people/lisa-hampson
 
Description Dr Marie-Cecile Le Deley 
Organisation Gustave-Roussy Institute
Country France 
Sector Academic/University 
PI Contribution Collaborated to explore whether statistical methods developed by Dr Hampson (published in " Hampson LV et al. (2014) Bayesian methods for the design and interpretation of clinical trials in very rare diseases; Statistics in Medicine 33;4186-4201") could be extended for application to a soon-to-start Phase II paediatric clinical trial in a rare cancer.
Collaborator Contribution Collaborators provided intellectual input into statistical methodology research and computer software development.
Impact Since October 2014, I am co-supervisor (along with Dr Marie-Cecile Le Deley) of a PhD student with the project Novel Bayesian methods for clinical trials in rare cancers. The PhD student is funded by the French Ministry of Higher Education and Research and will be based mainly at the Institute Gustave Roussy (Paris), with visits to Lancaster University planned. I was also invited to the Institute Gustave Roussy to present the following talk to an audience of statisticians, epidemiologists and clinicians: Hampson LV, Whitehead J, Eleftheriou D, Brogan P. Bayesian methods for the design of clinical trials in very rare diseases: application to the MYPAN trial in childhood polyarteritis nodosa.
Start Year 2014
 
Description EMA collaborative agreement 
Organisation European Medicines Agency
Department Paediatric Medicines
Country United Kingdom 
Sector Private 
PI Contribution Collaboration enabled me to undertake a review of strategies used to support dosing recommendations for paediatric medicines.
Collaborator Contribution During visits to the Agency, collaborator provided me with access to information and opportunities for discussions with scientific administrators on topics relevant to MRC Career Development Award. I was also invited to observe one meeting of the Paediatric Committee.
Impact Results of collaborative project were reported at a meeting of the EMA Paediatric Committee (London, December 2012) with a presentation entitled: Hampson LV, Herold R, Posch M, Saperia J, Whitehead A. Review of dose-finding strategies in paediatric investigation plans. A jointly authored manuscript reporting this research has been submitted for publication.
Start Year 2012
 
Description MYPAN trial 
Organisation University College London
Department Institute of Child Health
Country United Kingdom 
Sector Academic/University 
PI Contribution Contributed to the development of the statistical methodology underpinning the design of the MYPAN trial (Bayesian multicentre randomized controlled trial of mycophenolate mofetil versus cyclophosphamide for the induction of remission of polyarteritis nodosa) and wrote computer software to implement this novel methodology, specifically to elicit prior distributions for the treatments to be compared by the trial. I currently provide methodological support for the MYPAN clinical trial by sitting on the Trial Management Group.
Collaborator Contribution Collaborators are Principal Investigator and Co-Investigator of the MYPAN trial. Collaborators provided intellectual input into statistical methodology research and computer software.
Impact I have presented several invited talks on the statistical methodology research stemming from this collaboration: Hampson LV, Whitehead J. Combining opinion with clinical data. Barcelona BioMed Conference on Bayesian methods in Biostatistics and Bioinformatics (Barcelona, December 2012) Hampson LV, Whitehead J, Eleftheriou D, Brogan P. Bayesian methods for the design of clinical trials in rare diseases: application to the MYPAN trial in childhood polyarteritis nodosa. Institut Gustave-Roussy (Paris, March 2014) Hampson LV, Whitehead J, Eleftheriou D, Brogan P. Bayesian methods for the design of clinical trials in rare diseases: application to the MYPAN trial in childhood polyarteritis nodosa. Joint Meeting of Danish Society for Biopharmaceutical Statistics/Swedish Society for Medical Statistics (Copenhagen, October 2014)
Start Year 2012
 
Description PhD studentship related to design of Phase I clinical trials 
Organisation AstraZeneca
Country United Kingdom 
Sector Private 
PI Contribution I lead the supervision of an early stage researcher (ESR) who is funded through a Marie-Curie funded European international training network. The ESR's project will develop statistical methods for incorporating pre-clinical information into the design and interpretation of Phase I first-in-man studies.
Collaborator Contribution AstraZeneca will contribute to the supervision of the ESR through monthly meetings. The company will also host the ESR for a three month secondment during the project.
Impact No outputs yet.
Start Year 2016
 
Description Co-chaired expert group meeting for CRMO clinical trial 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Elicited the opinions of a group of 15 expert rheumatologists on the relative merits of two treatments for the treatment of children and adolescents with chronic recurrent multi-focal osteomylitis. Experts were drawn from across the UK, Europe and North America. Based on the meeting, we established consensus Bayesian prior distributions which can be taken forwards to a future planned Phase II trial. A novel methodological approach to Bayesian prior elicitation (and accompanying software) was developed for the meeting, which is currently being prepared for publication.
Year(s) Of Engagement Activity 2016
 
Description Engagement with Pharmaceutical Industry (DSBS/FMS meeting 2014) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presented research on Bayesian methods for clinical trials in very rare diseases to joint meeting of Danish and Swedish societies for biopharmaceutical/medical statistics. Talk sparked questions and discussion afterwards.

No tangible impacts yet.
Year(s) Of Engagement Activity 2014
URL http://www.dsbs.dk/moder.html
 
Description Engagement with Pharmaceutical Industry (Novartis, Switzerland 2012) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation Keynote/Invited Speaker
Geographic Reach International
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Invited speaker at Novartis Annual Biostatistics Conference (Switzerland, 17-18 October 2012) attended by over 50 biostatisticians. Two presentations were given which sparked discussions and interesting questions about my research. These presentations were:

Hampson LV, Whitehead J. "Bayesian approach for the design and interpretation of rare disease trials"

Hampson LV, Jennison C. "Optimal data combination rules for seamless Phase II/III clinical trials".


Continued contact with the Expert Statistical Methodology Group at Novartis in the form of intellectual input into research conducted as part of MRC Career Development Award.
Year(s) Of Engagement Activity 2012
 
Description Engagement with Pharmaceutical Industry (SMi Conference 2014) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Disseminated work on adaptive designs for multi-arm dose-finding trials to an audience including statisticians from the pharmaceutical industry and public sector clinical trials units. Talk sparked questions and discussion.

No tangible impact as yet.
Year(s) Of Engagement Activity 2014
 
Description Epilepsy Experts Group Meeting on Extrapolation 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Health professionals
Results and Impact Elicited the opinions of a panel of epileptologists on the role of extrapolation in the development of new medicines for children with epilepsy. The findings of this focus group will inform future methodological research on this topic. Discussions will be summarised in an opinion piece currently in preparation with the intention of submitting this for publication in a peer-reviewed journal.

No tangible impacts yet.
Year(s) Of Engagement Activity 2014
 
Description Presentation to the European Medicines Agency's Paediatric Committee 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Type Of Presentation Keynote/Invited Speaker
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact Presented the following talk at a meeting of the EMA's Paediatric Committee (London, December 2012), which sparked questions and discussion afterwards:

LV Hampson, R Herold, M Posch, J Saperia, A Whitehead: "Review of Dose-Finding Strategies in Paediatric Investigation Plans"


No direct impacts so far
Year(s) Of Engagement Activity 2012
URL http://www.ema.europa.eu/docs/en_GB/document_library/Minutes/2013/01/WC500137361.pdf
 
Description Two-day workshop on clinical trials in small populations 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact This was a two-day training and dissemination workshop on the theme "Clinical Trials in Small Populations: Methodological Challenges and Solutions". The meeting brought together 60 participants comprising methodologists, applied statisticians from the public and private sectors, a patient representative, and regulators to disseminate state-of-the-art methods. Participants were drawn from the UK, Europe and North America. Day 1 of the meeting comprised a mixture of tutorials and discussions centered around case-studies. Day 2 comprised a series of invited presentations from leading researchers and a patient representative. Feedback immediately after the even indicated that many attendees planned to use the methods covered in their future work.
Year(s) Of Engagement Activity 2015
URL http://www.lancaster.ac.uk/maths/small-trials/