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Murphy R, Halford S, Symeonides SN. Project Optimus, an FDA initiative: Considerations for cancer drug development internationally, from an academic perspective. Front Oncol 2023; 13:1144056. [PMID: 36937434 PMCID: PMC10020863 DOI: 10.3389/fonc.2023.1144056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Modern cancer therapeutics are increasingly targeted, bringing the promise of new and improved activity, alongside better tolerability. However, while many are indeed resulting in dramatic improvements in disease control and patient survival, short- and long-term tolerability has not always accompanied it. The choice of dose and schedule is often in the upper range of the therapeutic window, driven by the maximum tolerated dose (MTD) model of previous cytotoxic agents. There is increasing recognition that this needs to change, by taking a more holistic approach to determine the optimal dose for desired biological effects and tolerability early in clinical development. In the US, the FDA's Oncology Centre of Excellence is addressing this via the Project Optimus initiative: aiming to reform dose optimisation studies so that they can demonstrate the most appropriate dose selection. Early clinical development will need to demonstrate the dose-exposure, -pharmacodynamic, -toxicity and -activity relationships, including randomised evaluations for dose selection. Regulatory agencies outside the US are similarly exploring this. Along with Australia, Brazil, Canada, Israel, Singapore and Switzerland, the UK participates in Project Orbis, a collaborative program with the FDA to accelerate patient access to new cancer medicines through coordinated regulatory review. Close alignment with Project Optimus will be important internationally and will require changes across industry, including for academic units and small biotech. We discuss our perspective on the implications, and opportunities, for early phase oncology trials as a uniquely charity-funded drug development facility, the Centre for Drug Development within the Cancer Research UK charity.
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Affiliation(s)
- Ravindhi Murphy
- Centre for Drug Development, Cancer Research UK, London, United Kingdom
- *Correspondence: Ravindhi Murphy, ; Stefan Nicholas Symeonides,
| | - Sarah Halford
- Centre for Drug Development, Cancer Research UK, London, United Kingdom
| | - Stefan Nicholas Symeonides
- Centre for Drug Development, Cancer Research UK, London, United Kingdom
- Edinburgh Experimental Cancer Medicine Centre, University of Edinburgh, Edinburgh, United Kingdom
- *Correspondence: Ravindhi Murphy, ; Stefan Nicholas Symeonides,
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Walker K, Hinsley S, Phillip R, Oughton JB, Murden G, Chalmers AJ, Faivre-Finn C, Greystoke A, Brown SR. Implementation of the Time-to-Event Continuous Reassessment Method Design in a Phase I Platform Trial Testing Novel Radiotherapy-Drug Combinations-CONCORDE. JCO Precis Oncol 2022; 6:e2200133. [PMID: 36446040 PMCID: PMC9812638 DOI: 10.1200/po.22.00133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 09/23/2022] [Accepted: 10/04/2022] [Indexed: 11/30/2022] Open
Abstract
PURPOSE CONCORDE is the first phase I drug-radiotherapy (RT) combination platform in non-small-cell lung cancer, designed to assess multiple different DNA damage response inhibitors in combination with radical thoracic RT. Time-to-event continuous reassessment method (TiTE-CRM) methodology will inform dose escalation individually for each different DNA damage response inhibitor-RT combination and a randomized calibration arm will aid attribution of toxicities. We report in detail the novel statistical design and implementation of the TiTE-CRM in the CONCORDE trial. METHODS Statistical parameters were calibrated following recommendations by Lee and Cheung. Simulations were performed to assess the operating characteristics of the chosen models and were written using modified code from the R package dfcrm. RESULTS The results of the simulation work showed that the proposed statistical model setup can answer the research questions under a wide range of potential scenarios. The proposed models work well under varying levels of recruitment and with multiple adaptations to the original methodology. CONCLUSION The results demonstrate how TiTE-CRM methodology may be used in practice in a complex dose-finding platform study. We propose that this novel phase I design has potential to overcome some of the logistical barriers that for many years have prevented timely development of novel drug-RT combinations.
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Affiliation(s)
- Katrina Walker
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
| | - Samantha Hinsley
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
- Cancer Research UK Glasgow Clinical Trials Unit, Institute of Cancer Sciences, University of Glasgow, Scotland, United Kingdom
| | - Rachel Phillip
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
| | - Jamie B. Oughton
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
| | - Geraldine Murden
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
| | - Anthony J. Chalmers
- Institute of Cancer Sciences, University of Glasgow, Scotland, United Kingdom
| | - Corinne Faivre-Finn
- The Christie NHS Foundation Trust/University of Manchester, Manchester, United Kingdom
| | | | - Sarah R. Brown
- Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, England, United Kingdom
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Brown SR, Hinsley S, Hall E, Hurt C, Baird RD, Forster M, Scarsbrook AF, Adams RA. A Road Map for Designing Phase I Clinical Trials of Radiotherapy-Novel Agent Combinations. Clin Cancer Res 2022; 28:3639-3651. [PMID: 35552622 PMCID: PMC9433953 DOI: 10.1158/1078-0432.ccr-21-4087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/26/2022] [Accepted: 04/28/2022] [Indexed: 01/07/2023]
Abstract
Radiotherapy has proven efficacy in a wide range of cancers. There is growing interest in evaluating radiotherapy-novel agent combinations and a drive to initiate this earlier in the clinical development of the novel agent, where the scientific rationale and preclinical evidence for a radiotherapy combination approach are high. Optimal design, delivery, and interpretation of studies are essential. In particular, the design of phase I studies to determine safety and dosing is critical to an efficient development strategy. There is significant interest in early-phase research among scientific and clinical communities over recent years, at a time when the scrutiny of the trial methodology has significantly increased. To enhance trial design, optimize safety, and promote efficient trial conduct, this position paper reviews the current phase I trial design landscape. Key design characteristics extracted from 37 methodology papers were used to define a road map and a design selection process for phase I radiotherapy-novel agent trials. Design selection is based on single- or dual-therapy dose escalation, dose-limiting toxicity categorization, maximum tolerated dose determination, subgroup evaluation, software availability, and design performance. Fifteen of the 37 designs were identified as being immediately accessible and relevant to radiotherapy-novel agent phase I trials. Applied examples of using the road map are presented. Developing these studies is intensive, highlighting the need for funding and statistical input early in the trial development to ensure appropriate design and implementation from the outset. The application of this road map will improve the design of phase I radiotherapy-novel agent combination trials, enabling a more efficient development pathway.
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Affiliation(s)
- Sarah R. Brown
- Leeds Cancer Research UK Clinical Trials Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, United Kingdom
| | - Samantha Hinsley
- Clinical Trials Unit Glasgow, University of Glasgow, Glasgow, United Kingdom
| | - Emma Hall
- Clinical Trials and Statistics Unit, The Institute of Cancer Research, London, United Kingdom
| | - Chris Hurt
- Centre for Trials Research, Cardiff University, Cardiff, United Kingdom
| | | | | | - Andrew F. Scarsbrook
- Radiotherapy Research Group, Leeds Institute of Medical Research at St James's, Faculty of Medicine and Health, University of Leeds, Leeds, United Kingdom
| | - Richard A. Adams
- Centre for Trials Research, Cardiff University and Velindre Cancer Centre, Cardiff, United Kingdom
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Gourgou S, Azria D. [Clinical trials in Radiation Oncology: Methodologic approach]. Cancer Radiother 2022; 26:803-807. [PMID: 35953424 DOI: 10.1016/j.canrad.2022.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 06/01/2022] [Indexed: 11/29/2022]
Abstract
In the context of the clinical development of radiation oncology, the specificities of curative treatments and the necessary follow-ups for the acute and late tolerance evaluation require rigourous and up-dated methodological approaches given the limited feasibility of some studies to demonstrate their effectiveness. Indeed, the diversity of treatments in terms of delivery, type of radiation and multiple technologies render difficult the medical assessment. Although the randomized controlled trial is the gold standard for demonstrating the causal link of the treatment effect size, a state of the art of current limits is presented and proposals for new methodological approaches are discussed as alternative or complementary possibilities. Co-primary endpoints or pragmatic composite endpoints are to be used with adequate statistical analyses, the use of Bayesian methods, the re-use of observational data for the external control arms identification and the development of Real World Data registers is to be preferred to respond to this colossal challenge.
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Affiliation(s)
- S Gourgou
- Unité de biométrie, ICM, institut régional du cancer montpellier, université de Montpellier, avenue des Apothicaires, 34298 Montpellier cedex 05, France.
| | - D Azria
- Fédération universitaire d'oncologie radiothérapie d'occitanie méditerranée, ICM, Institut régional du cancer Montpellier, université de Montpellier, rue Croix-Verte, 34298 Montpellier cedex 05, France; IRCM, Institut de recherche en cancérologie de Montpellier, Inserm U1194, INCa_Inserm_DGOS_12553, université de Montpellier, avenue des Apothicaires, 34298 Montpellier cedex 05, France
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Wages NA, Braun TM, Normolle DP, Schipper MJ. Adaptive Phase 1 Design in Radiation Therapy Trials. Int J Radiat Oncol Biol Phys 2022; 113:493-499. [PMID: 35777394 DOI: 10.1016/j.ijrobp.2022.02.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 02/20/2022] [Indexed: 10/17/2022]
Affiliation(s)
- Nolan A Wages
- Division of Translational Research & Applied Statistics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia.
| | - Thomas M Braun
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Daniel P Normolle
- Department of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania
| | - Matthew J Schipper
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
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Exploring hypoxic biology to improve radiotherapy outcomes. Expert Rev Mol Med 2022; 24:e21. [DOI: 10.1017/erm.2022.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Ewings S, Saunders G, Jaki T, Mozgunov P. Practical recommendations for implementing a Bayesian adaptive phase I design during a pandemic. BMC Med Res Methodol 2022; 22:25. [PMID: 35057758 PMCID: PMC8771176 DOI: 10.1186/s12874-022-01512-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 01/06/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Modern designs for dose-finding studies (e.g., model-based designs such as continual reassessment method) have been shown to substantially improve the ability to determine a suitable dose for efficacy testing when compared to traditional designs such as the 3 + 3 design. However, implementing such designs requires time and specialist knowledge. METHODS We present a practical approach to developing a model-based design to help support uptake of these methods; in particular, we lay out how to derive the necessary parameters and who should input, and when, to these decisions. Designing a model-based, dose-finding trial is demonstrated using a treatment within the AGILE platform trial, a phase I/II adaptive design for novel COVID-19 treatments. RESULTS We present discussion of the practical delivery of AGILE, covering what information was found to support principled decision making by the Safety Review Committee, and what could be contained within a statistical analysis plan. We also discuss additional challenges we encountered in the study and discuss more generally what (unplanned) adaptations may be acceptable (or not) in studies using model-based designs. CONCLUSIONS This example demonstrates both how to design and deliver an adaptive dose-finding trial in order to support uptake of these methods.
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Affiliation(s)
- Sean Ewings
- Southampton Clinical Trials Unit, University of Southampton, Mailpoint 131, Southampton General Hospital, Tremona Road, Southampton, SO16, UK.
| | - Geoff Saunders
- Southampton Clinical Trials Unit, University of Southampton, Mailpoint 131, Southampton General Hospital, Tremona Road, Southampton, SO16, UK
| | - Thomas Jaki
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Mathematics and Statistics, Lancaster University, University of Lancaster, Lancaster, UK
| | - Pavel Mozgunov
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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