Model-informed evaluation of the benefit-risk balance of medicinal products in
paediatric rare diseases.
Background: The current pathway for development and approval of efficacious and
safe drugs for paediatric and rare disease is not optimal. In fact, despite the
trend towards rising drug research and development (R&D) expenditure, in Europe
only 14% of new medicines entering the market have a paediatric indication. One
of the reasons evoked by pharmaceutical companies for this issue is regulatory
overcautiousness, resulting in rising R&D costs and long drug development
timelines, causing delays in patient access to promising drugs. It is also
acknowledged that clinical trials have become increasingly complex,
larger-scale, and expensive. Whilst modelling and simulation (M&S) and
extrapolation has been proposed to address some of the current limitations by
complementing or replacing randomised controlled trials (RCT), model-informed
approaches are still used sub-optimally as part of an integrated drug
development strategy, and not always endorsed by regulators. There is currently
an unmet need for acceptability criteria related to the assessment of M&S
approaches when applied to drug development and assessment in paediatric and
rare diseases.
Within the scope of a broader European initiative, i.e., the ERAMET consortium,
drug-disease modelling and simulation will be used in conjunction with decision
analytical approaches, in particular, multicriteria decision analysis (MCDA) to
assess the operational efficacy and benefit-risk balance of pharmacological
interventions in paediatric rare diseases. The approach will also provide an
opportunity to establish the requirements for the generation of digital twins,
which reflect the key baseline characteristics of such patients in a real-life
setting. It is anticipated that this approach will reduce the gap in clinical
care, allowing paediatric patients to access the potential benefits of novel
therapies significantly earlier.
A post-doctoral research fellow position and a PhD research programme
(studentship) in clinical pharmacology have been created to support the
activities of the consortium including European academic groups and regulatory
agencies. The primary objective of the research programme will be to 1)
demonstrate the impact of a model-informed, question-centric approach for the
prediction of therapeutic response in paediatric rare diseases (e.g.,
transfusion-dependent haemoglobinopathies), 2) facilitate data re-use and
expedite the implementation of clinical trial simulations by the use of digital
twins and virtual cohort of paediatric patients and 3) evaluate alternative
trial designs for Phase II and III studies aimed at the assessment on of the
efficacy and safety of iron chelation in children.
Required skills: In addition to enthusiasm, motivation and independent
thinking, candidates must have working knowledge of
pharmacokinetic-pharmacodynamic modelling and simulation, including prior
experience with advanced statistical principles (nonlinear mixed effects
modelling, Bayesian statistics, clinical trial simulations). Programming skills
in R language, RStudio and NONMEM are essential. Understanding of clinical data
standards (CDISC, OMOP) would be desirable.
Willingness to learn and integrate knowledge from across different therapeutic
areas (i.e., haematology, biostatistics, decision analysis and clinical
pharmacology). Behavioural attributes such as teamwork, accurate listening,
strategic thinking, along with very good oral and written English language
skills will be critical for the successful implementation of the project.
Candidates for the post-doctoral research fellow position should have completed
a PhD in a relevant discipline (quantitative clinical pharmacology,
pharmacometrics, population pharmacokinetics, PKPD modelling, bioengineering),
and have published their research in a peer reviewed journal.
Candidates for the PhD studentship position should have at least six months
research experience in quantitative clinical pharmacology. Applications from
candidates with a degree in Medicine, Bioengineering, Clinical Drug
Development, Clinical Pharmacology, Biostatistics and Pharmaceutical Sciences
will be prioritised.
The successful candidates will be based at the Clinical Pharmacology &
Therapeutic Group at UCL in London.
Applicants for the PhD research programme should have an EU settled or
pre-settled status or be a UK national. Further details on the application
procedures can be obtained by email. Please contact Prof O. Della Pasqua
([email protected]<mailto:[email protected]>) including a short CV.
Deadline for applications: 15th May 2024.
Kind regards,
Salvatore D’Agate
Clinical Pharmacology & Therapeutics
School of Life and Medical Sciences
University College London
E-mail: s.d’[email protected]<mailto:s.d%e2%80%[email protected]>