The aim of phase I clinical trials is to obtain reliable information on safety, tolerability, pharmacokinetics (PK), and mechanism of action of drugs with the objective of determining the maximum tolerated dose (MTD). In most phase I studies, dose‐finding and PK analysis are done separately and no attempt is made to combine them during dose allocation. In cases such as rare diseases, paediatrics, and studies in a biomarker‐defined subgroup of a defined population, the available population size will limit the number of possible clinical trials that can be conducted. Combining dose‐finding and PK analyses to allow better estimation of the dose‐toxicity curve should then be considered. In this work, we propose, study, and compare methods to incorporate PK measures in the dose allocation process during a phase I clinical trial. These methods do this in different ways, including using PK observations as a covariate, as the dependent variable or in a hierarchical model. We conducted a large simulation study that showed that adding PK measurements as a covariate only does not improve the efficiency of dose‐finding trials either in terms of the number of observed dose limiting toxicities or the probability of correct dose selection. However, incorporating PK measures does allow better estimation of the dose‐toxicity curve while maintaining the performance in terms of MTD selection compared to dose‐finding designs that do not incorporate PK information. In conclusion, using PK information in the dose allocation process enriches the knowledge of the dose‐toxicity relationship, facilitating better dose recommendation for subsequent trials.

The CONSORT (CONsolidated Standards Of Reporting Trials) 2010 statement is the standard guideline for reporting completed randomised trials. The CONSORT Dose-finding Extension (DEFINE) extends the guidance (with 21 new items and 19 modified items) to early phase dose-finding trials with interim dose escalation or de-escalation strategies. Such trials generally focus on safety, tolerability, activity, and recommending dosing and scheduling regimens for further clinical development. These trials are often inadequately reported, hampering their informativeness and making evidence informed decisions difficult. The CONSORT-DEFINE guidance aims to develop an international, consensus driven guideline for reporting early phase dose-finding trials to promote transparency, completeness, reproducibility, and facilitate the interpretation of the results. The CONSORT-DEFINE guidance provides recommendations for essential items that should be reported in early phase dose-finding trials to promote greater clarity, reproducibility, informativeness, and usefulness of results.

Where there are a limited number of patients, such as in a rare disease, clinical trials in these small populations present several challenges, including statistical issues. This led to an EU FP7 call for proposals in 2013. One of the three projects funded was the Innovative Methodology for Small Populations Research (InSPiRe) project. This paper summarizes the main results of the project, which was completed in 2017. The InSPiRe project has led to development of novel statistical methodology for clinical trials in small populations in four areas. We have explored new decision-making methods for small population clinical trials using a Bayesian decision-theoretic framework to compare costs with potential benefits, developed approaches for targeted treatment trials, enabling simultaneous identification of subgroups and confirmation of treatment effect for these patients, worked on early phase clinical trial design and on extrapolation from adult to pediatric studies, developing methods to enable use of pharmacokinetics and pharmacodynamics data, and also developed improved robust meta-analysis methods for a small number of trials to support the planning, analysis and interpretation of a trial as well as enabling extrapolation between patient groups. In addition to scientific publications, we have contributed to regulatory guidance and produced free software in order to facilitate implementation of the novel methods.

During drug evaluation trials, information from clinical trials previously conducted on another population, indications or schedules may be available. In these cases, it might be desirable to share information by efficiently using the available resources. In this work, we developed an adaptive power prior with a commensurability parameter for using historical or external information. It allows, at each stage, full borrowing when the data are not in conflict, no borrowing when the data are in conflict or “tuned” borrowing when the data are in between. We propose to apply our adaptive power prior method to bridging studies between Caucasians and Asians, and we focus on the sequential adaptive allocation design, although other design settings can be used. We weight the prior information in two steps: the effective sample size approach is used to set the maximum desirable amount of information to be shared from historical data at each step of the trial; then, in a sort of Empirical Bayes approach, a commensurability parameter is chosen using a measure of distribution distance. This approach avoids elicitation and computational issues regarding the usual Empirical Bayes approach. We propose several versions of our method, and we conducted an extensive simulation study evaluating the robustness and sensitivity to prior choices.

The number of trials conducted and the number of patients per trial are typically small in paediatric clinical studies. This is due to ethical constraints and the complexity of the medical process for treating children. While incorporating prior knowledge from adults may be extremely valuable, this must be done carefully. In this paper, we propose a unified method for designing and analysing dose-finding trials in paediatrics, while bridging information from adults. The dose-range is calculated under three extrapolation options, linear, allometry and maturation adjustment, using adult pharmacokinetic data. To do this, it is assumed that target exposures are the same in both populations. The working model and prior distribution parameters of the dose–toxicity and dose–efficacy relationships are obtained using early-phase adult toxicity and efficacy data at several dose levels. Priors are integrated into the dose-finding process through Bayesian model selection or adaptive priors. This calibrates the model to adjust for misspecification, if the adult and pediatric data are very different. We performed a simulation study which indicates that incorporating prior adult information in this way may improve dose selection in children.

SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) 2013 provides guidance for clinical trial protocol writing. However, neither the original guidance nor its extensions adequately cover the features of early phase dose-finding trials. The SPIRIT Dose-finding Extension (DEFINE) statement is a new guideline that provides recommendations for essential items that should be provided in the protocols of these trials. It details extensions to the SPIRIT 2013 guidance, incorporating 17 new items and modifying 15 existing items. The purpose of this guideline is to promote transparency, completeness, reproducibility of methods, and interpretation of early phase dose-finding trial protocols. It is envisioned that the resulting improvements in the design and conduct of early phase clinical trials will ultimately reduce research inefficiencies and inconsistencies, driving transformational advances in clinical care.