The need for reporting guidelines for early phase dose-finding trials: Dose-Finding CONSORT Extension

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.

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Early-Phase Platform Trials: A New Paradigm for Dose Finding and Treatment Screening in the Era of Precision Oncology

JCO Precision Oncology ◽

10.1200/po.19.00057 ◽

2019 ◽

pp. 1-8

Author(s):

Mei-Yin C. Polley ◽

Ying Kuen Cheung

Keyword(s):

Early Phase ◽

Cytotoxic Agents ◽

Dose Finding ◽

Stopping Rules ◽

Precision Oncology ◽

Cancer Therapies ◽

New Paradigm ◽

Cancer Trial ◽

Targeted Cancer Therapies ◽

Statistical Designs

Applications in early-phase cancer trials have motivated the development of many statistical designs since the late 1980s, including dose-finding methods, futility screening, treatment selection, and early stopping rules. These methods are often proposed to address the conventional cytotoxic therapeutics for neoplastic diseases and cancer. Recent advances in precision medicine have motivated novel trial designs, most notably the idea of master protocol (eg, platform trial, basket trial, umbrella trial, N-of-1 trial), for the evaluation of molecularly targeted cancer therapies. In this article, we review the concepts and methodology of early-phase cancer trial designs with a focus on dose finding and treatment screening and put these methods in the context of platform trials of molecularly targeted cancer therapies. Because most cancer trial designs have been developed for cytotoxic agents, we will discuss how these time-tested design principles hold relevance for targeted cancer therapies, and we will delineate how a master protocol may serve as an efficient platform for safety and efficacy evaluations of novel targeted therapies.

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Supplemental Material for Adapting Pharmacological Dose-Finding Designs for Early Phase Behavioral Intervention Development Research

Health Psychology ◽

10.1037/hea0001024.supp ◽

2020 ◽

Keyword(s):

Behavioral Intervention ◽

Early Phase ◽

Intervention Development ◽

Dose Finding ◽

Development Research

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Implementation of adaptive dose-finding designs in two early phase haematological trials: clinical, operational, and methodological challenges

Trials ◽

10.1186/1745-6215-14-s1-o75 ◽

2013 ◽

Vol 14 (S1) ◽

Cited By ~ 2

Author(s):

Christina Yap ◽

Charlie Craddock ◽

Graham Collins ◽

Josephine Khan ◽

Shamyla Siddique ◽

...

Keyword(s):

Early Phase ◽

Dose Finding ◽

Methodological Challenges

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Adaptive dose-finding based on safety and feasibility in early-phase clinical trials of adoptive cell immunotherapy

Clinical Trials ◽

10.1177/1740774519890145 ◽

2019 ◽

Vol 17 (2) ◽

pp. 157-165

Author(s):

Nolan A Wages ◽

Camilo E Fadul

Keyword(s):

Clinical Trials ◽

Early Phase ◽

Safety Data ◽

Maximum Tolerated Dose ◽

Dose Finding ◽

Cell Immunotherapy ◽

Adoptive Cell Immunotherapy ◽

Early Phase Clinical Trials ◽

Finding Method ◽

Number Of Cells

Background/aims: Dose feasibility is a challenge that may arise in the development of adoptive T cell therapies for cancer. In early-phase clinical trials, dose is quantified either by a fixed or per unit body weight number of cells infused. It may not be feasible, however, to administer a patient’s assigned dose due to an insufficient number of cells harvested or functional heterogeneity of the product. The study objective becomes to identify the maximum tolerated dose with high feasibility of being administered. This article describes a new dose-finding method that adaptively accounts for safety and feasibility endpoints in guiding dose allocation. Methods: We propose an adaptive dose-finding method that integrates accumulating feasibility and safety data to select doses for participant cohorts in early-phase trials examining adoptive cell immunotherapy. We sequentially model the probability of dose-limiting toxicity and the probability of feasibility using independent beta-binomial models. The probability model for toxicity borrows information across all dose levels using isotonic regression, allowing participants infused at a lower dose than his or her planned dose to contribute safety data to the dose-finding algorithm. We applied the proposed methodology in a single simulated trial and evaluated its operating characteristics through extensive simulation studies. Results: In simulations conducted for a phase I study of adoptive immunotherapy for newly diagnosed glioblastoma, the proposed method demonstrates the ability to identify accurately the feasible maximum tolerated doses and to treat participants at and around these doses. Over 10 hypothesized scenarios studied, the percentage of correctly selecting the true feasible and maximum tolerated dose ranged from 50% to 90% with sample sizes averaging between 21 and 24 participants. A comparison to the only known existing method accounting for safety and feasibility yields competitive performance. Conclusion: We have developed a new practical adaptive dose-finding method to assess feasibility in early-phase adoptive cell therapy trials. A design that incorporates feasibility, as a function of the quantity and quality of the product manufactured, in addition to safety will have an impact on the recommended phase II doses in studies that evaluate patient outcomes.

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Dose Titration Algorithm Tuning (DTAT) should supersede ‘the’ Maximum Tolerated Dose (MTD) in oncology dose-finding trials

F1000Research ◽

10.12688/f1000research.10624.2 ◽

2017 ◽

Vol 6 ◽

pp. 112 ◽

Cited By ~ 2

Author(s):

David C. Norris

Keyword(s):

Phase I ◽

Early Phase ◽

Maximum Tolerated Dose ◽

Cytotoxic Chemotherapy ◽

Dose Finding ◽

Phase Iii ◽

Dose Titration ◽

Parameter Estimates ◽

Optimal Dosing ◽

Titration Algorithm

Background. Absent adaptive, individualized dose-finding in early-phase oncology trials, subsequent ‘confirmatory’ Phase III trials risk suboptimal dosing, with resulting loss of statistical power and reduced probability of technical success for the investigational therapy. While progress has been made toward explicitly adaptive dose-finding and quantitative modeling of dose-response relationships, most such work continues to be organized around a concept of ‘the’ maximum tolerated dose (MTD). The purpose of this paper is to demonstrate concretely how the aim of early-phase trials might be conceived, not as ‘dose-finding’, but as dose titration algorithm (DTA)-finding. Methods. A Phase I dosing study is simulated, for a notional cytotoxic chemotherapy drug, with neutropenia constituting the critical dose-limiting toxicity. The drug’s population pharmacokinetics and myelosuppression dynamics are simulated using published parameter estimates for docetaxel. The amenability of this model to linearization is explored empirically. The properties of a simple DTA targeting neutrophil nadir of 500 cells/mm 3 using a Newton-Raphson heuristic are explored through simulation in 25 simulated study subjects. Results. Individual-level myelosuppression dynamics in the simulation model approximately linearize under simple transformations of neutrophil concentration and drug dose. The simulated dose titration exhibits largely satisfactory convergence, with great variance in individualized optimal dosing. Some titration courses exhibit overshooting. Conclusions. The large inter-individual variability in simulated optimal dosing underscores the need to replace ‘the’ MTD with an individualized concept of MTDi . To illustrate this principle, the simplest possible DTA capable of realizing such a concept is demonstrated. Qualitative phenomena observed in this demonstration support discussion of the notion of tuning such algorithms. Although here illustrated specifically in relation to cytotoxic chemotherapy, the DTAT principle appears similarly applicable to Phase I studies of cancer immunotherapy and molecularly targeted agents.

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Dose Titration Algorithm Tuning (DTAT) should supersede the Maximum Tolerated Dose (MTD) concept in oncology dose-finding trials

F1000Research ◽

10.12688/f1000research.10624.1 ◽

2017 ◽

Vol 6 ◽

pp. 112

Author(s):

David C. Norris

Keyword(s):

Simulation Model ◽

Early Phase ◽

Maximum Tolerated Dose ◽

Dose Finding ◽

Phase Iii ◽

Dose Titration ◽

Individual Level ◽

General Terms ◽

Optimal Dosing ◽

Titration Algorithm

Background. Absent adaptive, individualized dose-finding in early-phase oncology trials, subsequent ‘confirmatory’ Phase III trials risk suboptimal dosing, with resulting loss of statistical power and reduced probability of technical success for the investigational drug. While progress has been made toward explicitly adaptive dose-finding and quantitative modeling of dose-response relationships, most such work continues to be organized around a concept of ‘the’ maximum tolerated dose (MTD). The purpose of this paper is to demonstrate concretely how the aim of early-phase trials might be conceived of, not as ‘dose-finding’, but as dosing algorithm-finding. Methods. A Phase I dosing study is simulated, for a notional cytotoxic chemotherapy drug, with neutropenia constituting the critical dose-limiting toxicity. The drug’s population pharmacokinetics and myelosuppression dynamics are simulated using published parameter estimates for docetaxel. The amenability of this model to linearization is explored empirically. The properties of a simple dose titration algorithm targeting neutrophil nadir of 500 cells/mm3 using a Newton-Raphson heuristic are explored through simulation in 25 simulated study subjects. Results. Individual-level myelosuppression dynamics in the simulation model approximately linearize under simple transformations of neutrophil concentration and drug dose. The simulated dose titration exhibits largely satisfactory convergence, with great variance in individualized optimal dosing. Some titration courses exhibit overshooting. Conclusions. The large inter-individual variability in simulated optimal dosing underscores the need to replace ‘the’ MTD with an individualized concept of MTDi . To illustrate this principle, the simplest possible dose titration algorithm capable of realizing such a concept is demonstrated. Qualitative phenomena observed in this demonstration support discussion of the notion of tuning such algorithms. The individual-level linearization of myelosuppression dynamics demonstrated for the simulation model used here suggest that a titration algorithm specified in the more general terms of the linear Kalman filter will be worth exploring.

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