Innovative Clinical Trials: The LUNG-MAP Study

Precision Oncology Clinical Trials: A Systematic Review of Phase II Clinical Trials with Biomarker-Driven, Adaptive Design

Novel clinical trial designs are conducted in the precision medicine era. This study aimed to evaluate biomarker-driven, adaptive phase II trials in precision oncology, focusing on infrastructure, efficacy, and safety. We systematically reviewed and analyzed the target studies. EMBASE and PubMed searches from 2015 to 2023 generated 29 eligible trials. Data extraction included infrastructure, biomarker screening methodologies, efficacy, and safety profiles. Government agencies, cancer hospitals, and academic societies with accumulated experiences led investigator-initiated precision oncology clinical trials (IIPOCTs), which later guided sponsor-initiated precision oncology clinical trials (SIPOCTs). Most SIPOCTs were international studies with basket design. IIPOCTs primarily used the central laboratory for biomarker screening, but SIPOCTs used both central and local laboratories. Most of the studies adapted next-generation sequencing and/or immunohistochemistry for biomarker screening. Fifteen studies included an independent central review committee for outcome investigation. Efficacy assessments predominantly featured objective response rate as the primary endpoint, with varying results. Nine eligible studies contributed to the United States Food and Drug Administration's marketing authorization. Safety monitoring was rigorous, but reporting formats lacked uniformity. Health-related quality of life and patient-reported outcomes were described in some protocols but rarely reported. Our results reveal that precision oncology trials with adaptive design rapidly and efficiently evaluate anticancer drugs' efficacy and safety, particularly in specified biomarker-driven cohorts. The evolution from IIPOCT to SIPOCT has facilitated fast regulatory approval, providing valuable insights into the precision oncology landscape.

Implementation of an ISO 15189 accredited next generation sequencing service for cell-free total nucleic acid (cfTNA) analysis to facilitate driver mutation reporting in blood: the experience of a clinical diagnostic laboratory

AIMS

Next generation sequencing (NGS) on tumour tissue is integral to the delivery of personalised medicine and targeted therapy. NGS on liquid biopsy, a much less invasive technology, is an emerging clinical tool that has rapidly expanded clinical utility. Gene mutations in cell-free total nucleic acids (cfTNA) circulating in the blood are representative of whole tumour biology and can reveal different mutations from different tumour sites, thus addressing tumour heterogeneity challenges.

METHODS

The novel Ion Torrent Genexus NGS system with automated sample preparation, onboard library preparation, templating, sequencing, data analysis and Oncomine Reporter software was used. cfTNA extracted from plasma was verified with the targeted pan-cancer (~50 genes) Oncomine Precision Assay (OPA). Assessment criteria included analytical sensitivity, specificity, limits of detection (LOD), accuracy, repeatability, reproducibility and the establishment of performance metrics.

RESULTS

An ISO 15189 accredited, minimally invasive cfTNA NGS diagnostic service has been implemented. High sensitivity (>83%) and specificity between plasma and tissue were observed. A sequencing LOD of 1.2% was achieved when the depth of coverage was >22 000×. A reduction (>68%) in turnaround time (TAT) of liquid biopsy results was achieved: 5 days TAT for in-house analysis from sample receipt to a final report issued to oncologists as compared with >15 days from reference laboratories.

CONCLUSION

Tumour-derived somatic variants can now be reliably assessed from plasma to provide minimally invasive tumour profiling. Successful implementation of this accredited service resulted in:Appropriate molecular profiling of patients where tumour tissue is unavailable or inaccessible.Rapid TAT of plasma NGS results.

Unlocking the Potential: A Systematic Review of Master Protocol in Pediatrics

The use of master protocols allows for innovative approaches to clinical trial designs, potentially enabling new approaches to operations and analytics and creating value for patients and drug developers. Pediatric research has been conducted for many decades, but the use of novel designs such as master protocols in pediatric research is not well understood. This study aims to provide a systematic review on the utilization of master protocols in pediatric drug development. A search was performed in September 2022 using two data sources (PubMed and ClinicalTrials.gov) and included studies conducted in the past10 years. General study information was extracted such as study type, study status, therapeutic area, and clinical trial phase. Study characteristics that are specific to pediatric studies (such as age of the participants and pediatric drug dosing) and important study design elements (such as number of test drug arms and whether randomization and/or concurrent control was used) were also collected. Our results suggest that master protocol studies are being used in pediatrics, with platform and basket trials more common than umbrella trials. Most of this experience is in oncology and early phase studies. There is a rise in the use starting in 2020, largely in oncology and COVID-19 trials. However, adoption of master protocols in pediatric clinical research is still on a small scale and could be substantially expanded. Work is required to further understand the barriers in implementing pediatric master protocols, from setting up infrastructure to interpreting study findings.

Implementation of an ISO15189 accredited next-generation sequencing service with the fully automated Ion Torrent Genexus: the experience of a clinical diagnostic laboratory

AIMS

Next-generation sequencing (NGS) is integral to the delivery of personalised medicine for targeted cancer therapy. Average turnaround times (TAT) from reference laboratories with advanced expertise in sequencing are typically 2-3 weeks. Prolonged TAT for biomarker analysis can adversely affect patient outcomes. The project aim was to establish an accredited NGS service integrated within a routine clinical diagnostic laboratory, in a designated tertiary cancer centre with no previous experience in NGS or bioinformatics.

METHODS

Platform selected was the novel Ion Torrent Genexus Sequencer with automated onboard library preparation, templating, sequencing and data analysis, with subsequent reporting using Oncomine Reporter software.Entire workflow validation was performed with a targeted panel, the Oncomine Precision Assay, on formalin-fixed paraffin embedded clinical tumour samples. Oncomine Reporter software was used to report on variants including mutations, copy number variations and fusions across 50 key genes.Samples included surgical resections, biopsies, cytology and commercial reference material. Assessment of criteria included analytical sensitivity, specificity, limit of detection, accuracy, repeatability and reproducibility, with the establishment of performance metrics and quality parameters.

RESULTS

High sensitivity, specificity and reproducibility were achieved. DNA/RNA input requirements optimised to >10 ng, and sequencing performance established with a limit of detection of 5% when depth of coverage of 2500X was reached. This NGS service attained ISO15189 accreditation with no non-conformances and >56% reduction in TAT.

CONCLUSION

Successful implementation, clinical validation and accreditation of a novel NGS technology was achieved in this institution, with a significantly improved TAT of results to oncologists.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Precision oncology with selective RET inhibitor selpercatinib in RET-rearranged cancers

Rearranged during transfection (RET) is a protooncogene that encodes for receptor tyrosine kinase with downstream effects on multiple cellular pathways. Activating RET alterations can occur and lead to uncontrolled cellular proliferation as a hallmark of cancer development. Oncogenic RET fusions are present in nearly 2% of patients with non-small cell lung cancer (NSCLC), 10-20% of patients with thyroid cancer, and <1% across the pan-cancer spectrum. In addition, RET mutations are drivers in 60% of sporadic medullary thyroid cancers and 99% of hereditary thyroid cancers. The discovery, rapid clinical translation, and trials leading to FDA approvals of selective RET inhibitors, selpercatinib and pralsetinib, have revolutionized the field of RET precision therapy. In this article, we review the current status on the use of the selective RET inhibitor, selpercatinib, in RET fusion-positive tumors: NSCLC, thyroid cancers, and the more recent tissue-agnostic activity leading to FDA approval.

Validation of Predictive Analyses for Interim Decisions in Clinical Trials

PURPOSE

Adaptive clinical trials use algorithms to predict, during the study, patient outcomes and final study results. These predictions trigger interim decisions, such as early discontinuation of the trial, and can change the course of the study. Poor selection of the Prediction Analyses and Interim Decisions (PAID) plan in an adaptive clinical trial can have negative consequences, including the risk of exposing patients to ineffective or toxic treatments.

METHODS

We present an approach that leverages data sets from completed trials to evaluate and compare candidate PAIDs using interpretable validation metrics. The goal is to determine whether and how to incorporate predictions into major interim decisions in a clinical trial. Candidate PAIDs can differ in several aspects, such as the prediction models used, timing of interim analyses, and potential use of external data sets. To illustrate our approach, we considered a randomized clinical trial in glioblastoma. The study design includes interim futility analyses on the basis of the predictive probability that the final analysis, at the completion of the study, will provide significant evidence of treatment effects. We examined various PAIDs with different levels of complexity to investigate if the use of biomarkers, external data, or novel algorithms improved interim decisions in the glioblastoma clinical trial.

RESULTS

Validation analyses on the basis of completed trials and electronic health records support the selection of algorithms, predictive models, and other aspects of PAIDs for use in adaptive clinical trials. By contrast, PAID evaluations on the basis of arbitrarily defined ad hoc simulation scenarios, which are not tailored to previous clinical data and experience, tend to overvalue complex prediction procedures and produce poor estimates of trial operating characteristics such as power and the number of enrolled patients.

CONCLUSION

Validation analyses on the basis of completed trials and real world data support the selection of predictive models, interim analysis rules, and other aspects of PAIDs in future clinical trials.

A bayesian platform trial design to simultaneously evaluate multiple drugs in multiple indications with mixed endpoints

In the era of targeted therapies and immunotherapies, the traditional drug development paradigm of testing one drug at a time in one indication has become increasingly inefficient. Motivated by a real-world application, we propose a master-protocol-based Bayesian platform trial design with mixed endpoints (PDME) to simultaneously evaluate multiple drugs in multiple indications, where different subsets of efficacy measures (e.g., objective response and landmark progression-free survival) may be used by different indications as single or multiple endpoints. We propose a Bayesian hierarchical model to accommodate mixed endpoints and reflect the trial structure of indications that are nested within treatments. We develop a two-stage approach that first clusters the indications into homogeneous subgroups and then applies the Bayesian hierarchical model to each subgroup to achieve precision information borrowing. Patients are enrolled in a group-sequential way and adaptively assigned to treatments according to their efficacy estimates. At each interim analysis, the posterior probabilities that the treatment effect exceeds prespecified clinically relevant thresholds are used to drop ineffective treatments and "graduate" effective treatments. Simulations show that the PDME design has desirable operating characteristics compared to existing method. This article is protected by copyright. All rights reserved.

Targeted Therapies for Lung Cancer Patients With Oncogenic Driver Molecular Alterations

Lung cancer has traditionally been classified by histology. However, a greater understanding of disease biology and the identification of oncogenic driver alterations has dramatically altered the therapeutic landscape. Consequently, the new classification paradigm of non-small-cell lung cancer is further characterized by molecularly defined subsets actionable with targeted therapies and the treatment landscape is becoming increasingly complex. This review encompasses the current standards of care for targeted therapies in lung cancer with driver molecular alterations. Targeted therapies for EGFR exon 19 deletion and L858R mutations, and ALK and ROS1 rearrangements are well established. However, there is an expanding list of approved targeted therapies including for BRAF V600E, EGFR exon 20 insertion, and KRAS G12C mutations, MET exon 14 alterations, and NTRK and RET rearrangements. In addition, there are numerous other oncogenic drivers, such as HER2 exon 20 insertion mutations, for which there are emerging efficacy data for targeted therapies. The importance of diagnostic molecular testing, intracranial efficacy of novel therapies, the optimal sequencing of therapies, role for targeted therapies in early-stage disease, and future directions for precision oncology approaches to understand tumor evolution and therapeutic resistance are also discussed.

Bayesian basket trial design with false-discovery rate control

BACKGROUND

Recent advances in developing "tumor agnostic" oncology therapies have identified molecular targets that define patient subpopulations in a manner that supersedes conventional criteria for cancer classification. These successes have produced effective targeted therapies that are administered to patients regardless of their tumor histology. Trials have evolved as well with master protocol designs. By blending translational and clinical science, basket trials in particular are well-suited to investigate and develop targeted therapies among multiple cancer histologies. However, basket trials intrinsically involve more complex design decisions, including issues of multiple testing across baskets, and guidance for investigators is needed.

METHODS

The sensitivity of the multisource exchangeability model to prior specification under differing degrees of response heterogeneity is explored through simulation. Then, a multisource exchangeability model design that incorporates control of the false-discovery rate is presented and a simulation study compares the operating characteristics to a design where the family-wise error rate is controlled and to the frequentist approach of treating the baskets as independent. Simulations are based on the original design of a real-world clinical trial, the SUMMIT trial, which investigated Neratinib treatment for a variety of solid tumors. The methods studied here are specific to single-arm phase II trials with binary outcomes.

RESULTS

Values of prior probability of exchangeability in the multisource exchangeability model between 0.1 and 0.3 provide the best trade-offs between gain in precision and bias, especially when per-basket sample size is below 30. Application of these calibration results to a re-analysis of the SUMMIT trial showed that the breast basket exceeded the null response rate with posterior probability of 0.999 while having low posterior probability of exchangeability with all other baskets. Simulations based on the design of the SUMMIT trial revealed that there is meaningful improvement in power even in baskets with small sample size when the false-discovery rate is controlled as opposed to the family-wise error rate. For example, when only the breast basket was active, with a sample size of 25, the power was 0.76 when the false-discovery rate was controlled at 0.05 but only 0.56 when the family-wise error rate was controlled at 0.05, indicating that impractical sample sizes for the phase II setting would be needed to achieve acceptable power while controlling the family-wise error rate in this setting of a trial with 10 baskets.

CONCLUSION

Selection of the prior exchangeability probability based on calibration and incorporation of false-discovery rate control result in multisource exchangeability model designs with high power to detect promising treatments in the context of phase II basket trials.

Patient Knowledge and Expectations About Return of Genomic Results in a Biomarker-Driven Master Protocol Trial (SWOG S1400GEN)

PURPOSE

Biomarker-driven master protocols represent a new paradigm in oncology clinical trials, but their complex designs and wide-ranging genomic results returned can be difficult to communicate to participants. The objective of this pilot study was to evaluate patient knowledge and expectations related to return of genomic results in the Lung Cancer Master Protocol (Lung-MAP).

METHODS

Eligible participants with previously treated advanced non-small-cell lung cancer were recruited from patients enrolled in Lung-MAP. Participants completed a 38-item telephone survey ≤ 30 days from Lung-MAP consent. The survey assessed understanding about the benefits and risks of Lung-MAP participation and knowledge of the potential uses of somatic testing results returned. Descriptive statistics and odds ratios for associations between demographic factors and correct responses to survey items were assessed.

RESULTS

From August 1, 2017, to June 30, 2019, we recruited 207 participants with a median age of 67, 57.3% male, and 94.2% White. Most participants "strongly/somewhat agreed" with statements that they "received enough information to understand" Lung-MAP benefits (82.6%) and risks (69.5%). In items asking about potential uses of Lung-MAP genomic results, 87.0% correctly indicated that the results help to select cancer treatment, but < 20% correctly indicated that the results are not used to confirm cancer diagnosis, would not reveal risk of developing diseases besides cancer, and would not indicate if family members had increased cancer risk. There were no associations between sociodemographic factors and proportions providing correct responses.

CONCLUSION

In a large National Clinical Trials Network biomarker-driven master protocol, most participants demonstrated incorrect knowledge and expectations about the uses of genomic results provided in the study despite most indicating that they had enough information to understand benefits and risks.

Streamlined Operational Approaches and Use of e-Technologies in Clinical Trials: Beat Acute Myeloid Leukemia Master Trial

Advances in genomic technologies and an increased understanding of the molecular pathogenesis of cancer have resulted in development of new effective, mutation-targeted therapies. In turn, these informed the development of Master Trial designs to test these therapies. The Beat Acute Myeloid Leukemia (BAML) Master Trial (Sponsor: The Leukemia & Lymphoma Society) tests several targeted therapies in patients aged ≥ 60 years with AML based on genomic profiling obtained within 7 days of study enrollment. We hypothesized that integrating operational strategies with new electronic technologies (e-technologies) might streamline the conduct and management of this Master Trial. BAML's 5 core operational strategies revolve around the guiding principle of "patients first." The e-technology platforms employed in BAML include: Clinical Oversight Platform: a central collaborative tool; e-Protocol/e-Source Upload/Electronic Data Capture Platform: digitizes the protocol, allows remote data monitoring, and collects/exports data in Study Data Tabulation Model format; and Data Review Platform: ingests data from different sources for clinical response and safety data reviews. The operational approaches, e-technologies and sponsor/contract research organization's (CRO) expertise together allow: the complexity and size of the BAML Master Trial to be better managed; near real-time study data oversight; better collaboration, communication and training; improved data collection, enhanced transmission and accessibility; data integration, review and generation of reports; while maintaining data privacy, and compliance. Initial e-technology challenges were overcome through training, learning, discipline and adjustment. In conclusion, to successfully manage Master Trials, significant time should be spent re-evaluating, improving and developing new operational approaches.Clinical Trial Registration: Clinical Trials.gov Identifier: NCT03013998. https://clinicaltrials.gov/ct2/show/NCT03013998 .

Novel Study Designs in Precision Medicine - Basket, Umbrella and Platform Trials

The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict, more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypothesis within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.

Statistical design considerations for trials that study multiple indications

Breakthroughs in cancer biology have defined new research programs emphasizing the development of therapies that target specific pathways in tumor cells. Innovations in clinical trial design have followed with master protocols defined by inclusive eligibility criteria and evaluations of multiple therapies and/or histologies. Consequently, characterization of subpopulation heterogeneity has become central to the formulation and selection of a study design. However, this transition to master protocols has led to challenges in identifying the optimal trial design and proper calibration of hyperparameters. We often evaluate a range of null and alternative scenarios; however, there has been little guidance on how to synthesize the potentially disparate recommendations for what may be optimal. This may lead to the selection of suboptimal designs and statistical methods that do not fully accommodate the subpopulation heterogeneity. This article proposes novel optimization criteria for calibrating and evaluating candidate statistical designs of master protocols in the presence of the potential for treatment effect heterogeneity among enrolled patient subpopulations. The framework is applied to demonstrate the statistical properties of conventional study designs when treatments offer heterogeneous benefit as well as identify optimal designs devised to monitor the potential for heterogeneity among patients with differing clinical indications using Bayesian modeling.

Recent advances in understanding amyotrophic lateral sclerosis and emerging therapies

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that is characterized by degeneration of both upper and lower motor neurons and subsequent progressive loss of muscle function. Within the last decade, significant progress has been made in the understanding of the etiology and pathobiology of the disease; however, treatment options remain limited and only two drugs, which exert a modest effect on survival, are approved for ALS treatment in the US. Therefore, the search for effective ALS therapies continues, and over 60 clinical trials are in progress for patients with ALS and other therapeutics are at the pre-clinical stage of development. Recent advances in understanding the genetics, pathology, and molecular mechanisms of ALS have led to the identification of novel targets and strategies that are being used in emerging ALS therapeutic interventions. Here, we review the current status and mechanisms of action of a selection of emerging ALS therapies in pre-clinical or early clinical development, including gene therapy, immunotherapy, and strategies that target neuroinflammation, phase separation, and protein clearance.

Master Protocol Trial Design for Efficient and Rational Evaluation of Novel Therapeutic Oncology Devices

Historically, the gold standard for evaluation of cancer therapeutics, including medical devices, has been the randomized clinical trial. Although high-quality clinical data are essential for safe and judicious use of therapeutic oncology devices, class II devices require only preclinical data for US Food and Drug Administration approval and are often not rigorously evaluated prior to widespread uptake. Herein, we review master protocol design in medical oncology and its application to therapeutic oncology devices, using examples from radiation oncology. Unique challenges of clinical testing of radiation oncology devices (RODs) include patient and treatment heterogeneity, lack of funding for trials by industry and health-care payers, and operator dependence. To address these challenges, we propose the use of master protocols to optimize regulatory, financial, administrative, quality assurance, and statistical efficiency of trials evaluating RODs. These device-specific master protocols can be extrapolated to other devices and encompass multiple substudies with the same design, statistical considerations, logistics, and infrastructure. As a practical example, we outline our phase I and II master protocol trial of stereotactic magnetic resonance imaging–guided adaptive radiotherapy, which to the best of our knowledge is the first master protocol trial to test a ROD. Development of more efficient clinical trials is needed to promote thorough evaluation of therapeutic oncology devices, including RODs, in a resource-limited environment, allowing more practical and rapid identification of the most valuable advances in our field.

Challenges and approaches to implementing master/basket trials in oncology

The appetite for cutting-edge cancer research, across medical institutions, scientific researchers, and health care providers, is increasing based on the promise of true breakthroughs and cures with new therapeutics available for investigation. At the same time, the barriers for advancing clinical research are impacting how quickly drug development efforts are conducted. For example, we know now that under a microscope, patients with the same type of cancer and histology might look the same; however, the reality is that most cancers are driven by genomic, transcriptional, and epigenetic changes that make each patient unique. Additionally, the immunologic reaction to different tumor types is distinct among patients. The challenge for researchers developing new therapies today is vastly different than it was in the era of cytotoxics. Today, we must identify a sufficient number of patients harboring a rare mutation or other characteristic and match this to the right therapeutic option. This summary provides a guide to help inform the scientific cancer community about the benefits and challenges of conducting umbrella or basket trials (master trials), and to create a roadmap to help make this new and evolving form of clinical trial design as effective as possible.

Systematic Review and Meta-Analysis of the Magnitude of Structural, Clinical, and Physician and Patient Barriers to Cancer Clinical Trial Participation

BACKGROUND

Barriers to cancer clinical trial participation have been the subject of frequent study, but the rate of trial participation has not changed substantially over time. Studies often emphasize patient-related barriers, but other types of barriers may have greater impact on trial participation. Our goal was to examine the magnitude of different domains of trial barriers by synthesizing prior research.

METHODS

We conducted a systematic review and meta-analysis of studies that examined the trial decision-making pathway using a uniform framework to characterize and quantify structural (trial availability), clinical (eligibility), and patient/physician barrier domains. The systematic review utilized the PubMed, Google Scholar, Web of Science, and Ovid Medline search engines. We used random effects to estimate rates of different domains across studies, adjusting for academic vs community care settings.

RESULTS

We identified 13 studies (nine in academic and four in community settings) with 8883 patients. A trial was unavailable for patients at their institution 55.6% of the time (95% confidence interval [CI] = 43.7% to 67.3%). Further, 21.5% (95% CI = 10.9% to 34.6%) of patients were ineligible for an available trial, 14.8% (95% CI = 9.0% to 21.7%) did not enroll, and 8.1% (95% CI = 6.3% to 10.0%) enrolled. Rates of trial enrollment in academic (15.9% [95% CI = 13.8% to 18.2%]) vs community (7.0% [95% CI = 5.1% to 9.1%]) settings differed, but not rates of trial unavailability, ineligibility, or non-enrollment.

CONCLUSIONS

These findings emphasize the enormous need to address structural and clinical barriers to trial participation, which combined make trial participation unachievable for more than three of four cancer patients.

Basket Designs: Statistical Considerations for Oncology Trials

Progress in the areas of genomics, disease pathways, and drug discovery has advanced into clinical and translational cancer research. The latest innovations in clinical trials have followed with master protocols, which are defined by inclusive eligibility criteria and devised to interrogate multiple therapies for a given tumor histology and/or multiple histologies for a given therapy under one protocol. The use of master protocols for oncology has become more common with the desire to improve the efficiency of clinical research and accelerate overall drug development. Basket trials have been devised to ascertain the extent to which a treatment strategy offers benefit to various patient subpopulations defined by a common molecular target. Conventionally conducted within the phase II setting, basket designs have become popular as drug developers seek to effectively evaluate and identify preliminary efficacy signals among clinical indications identified as promising in preclinical study. This article reviews basket trial designs in oncology settings and discusses several issues that arise with their design and analysis.

Light and shadow on innovative clinical trial designs: reflections from the EORTC-PAMM course on 'preclinical and early-phase clinical pharmacology'

Introduction: In the era of 'precision' oncology, novel clinical trial designs have emerged, in order to better address the final goal of translating the above-mentioned preclinical discoveries into the clinic. Nonetheless, in aiming to achieve the greatest clinical benefit to patients, some limitations of these novel approaches from the statistical, methodological and practical point of view need to be overcome.Areas covered: In the present review, a short overview of basket trials, umbrella trials and platform trials are discussed, in particular advantages and disadvantages of such experimental approaches.Expert opinion: Master protocols represent the future of clinical oncology research. The possibility of investigating multiple biomarkers and therapeutic regimens under one study is a strong advantage over traditional trials, and it can lead to quick implementation of new, promising treatments or biomarkers into the clinic.

Reporting of master protocols towards a standardized approach: A systematic review

BACKGROUND

In September 2018 the FDA provided a draft guidance on master protocols reflecting an increased interest in these designs by industry. Master protocols refer to a single overarching protocol developed to evaluate multiple hypotheses and may be further categorized as basket, umbrella, and platform trials. However, inconsistencies in reporting persist in the literature. We conducted a systematic review to describe master protocol reporting with the goal of facilitating the further development and spread of these innovative trial designs.

METHODS

We searched MEDLINE, EMBASE, and CENTRAL from inception to April 25, 2019 for English articles on master protocols. This was supplemented by hand searches of trial registries and of the bibliographies of published reviews. We used the FDA's definitions of master protocols as references and compared them to self-reported master protocols.

RESULTS

We identified 278 master protocol publications, consisting of 228 protocols and 50 reviews. Sixty-six records provided unique definitions of master protocol types. We observed considerable heterogeneity in definitions of master protocols, and over half (54%) used oncology-specific language. The majority of self-classified master protocols (57%) were consistent with the FDA's definitions of master protocols.

CONCLUSION

The terms 'master protocol', 'basket trial', 'umbrella trial', and 'platform trial' are inconsistently described. Careful treatment of these terms and adherence to the definitions set forth by the FDA will facilitate better understanding of these trial designs and allow them to be used broadly and to their full potential in clinical research. We encourage trial methodologists to use these trial designations when applicable.

Umbrella and basket trials in oncology: ethical challenges

BACKGROUND

Novel precision oncology trial designs, such as basket and umbrella trials, are designed to test new anticancer agents in more effective and affordable ways. However, they present some ethical concerns referred to scientific validity, risk-benefit balance and informed consent. Our aim is to discuss these issues in basket and umbrella trials, giving examples of two ongoing cancer trials: NCI-MATCH (National Cancer Institute - Molecular Analysis for Therapy Choice) and Lung-MAP (Lung Cancer Master Protocol) study.

MAIN BODY

We discuss three ethical requirements for clinical trials which may be challenged in basket and umbrella trial designs. Firstly, we consider scientific validity. Thanks to the new trial designs, patients with rare malignancies have the opportunity to be enrolled and benefit from the trial, but due to insufficient accrual, the trial may generate clinically insignificant findings. Inadequate sample size in study arms and the use of surrogate endpoints may result in a drug approval without confirmed efficacy. Moreover, complexity, limited quality and availability of tumor samples may not only introduce bias and result in unreliable and unrepresentative findings, but also can potentially harm patients and assign them to an inappropriate therapy arm. Secondly, we refer to benefits and risks. Novel clinical trials can gain important knowledge on the variety of tumors, which can be used in future trials to develop effective therapies. However, they offer limited direct benefits to patients. All potential participants must wait about 2 weeks for the results of the genetic screening, which may be stressful and produce anxiety. The enrollment of patients whose tumors harbor multiple mutations in treatments matching a single mutation may be controversial. As to informed consent - the third requirement we discuss, the excessive use of phrases like "personalized medicine", "tailored therapy" or "precision oncology" might be misleading and cause personal convictions that the study protocol is designed to fulfill the individual health-related needs of participants.

CONCLUSIONS

We suggest that further approaches should be implemented to enhance scientific validity, reduce misunderstandings and risks, thus maximizing the benefits to society and to trial participants.

Adaptive and platform trials in remote damage control resuscitation

The traditional approach to clinical trial design requires assuming precise values for multiple unknown parameters, resulting in a trial design that is unlikely to perform well if one or more of those assumptions turn out to be incorrect. During conduct of the trial, trial characteristics are often held fixed, even if incoming data suggest that one or more design assumptions were incorrect. This leads to an increased risk of a failed trial. In contrast, an adaptive clinical trial is designed to take advantage of partial, incoming data during the conduct of the trial, modifying key clinical trial characteristics according to prespecified rules, in order to avoid a failed or inconclusive trial, improve statistical efficacy, better treat patients within the trial, or achieve other scientific or ethical goals. The concept of an adaptive trial can be expanded to a platform trial, a clinical trial that is intended to evaluate multiple treatments or combinations of treatments, often for patients with any of a group of related diseases, and to continue beyond the evaluation of any particular treatment. Platform trial design strategies can be applied to the problem of finding the best treatment strategy for patients suffering from posttraumatic hemorrhagic shock. We present the rationale and considerations surrounding adaptive and platform trial design and apply these concepts to the problem of investigating strategies for remote damage control resuscitation.

Challenges with Novel Clinical Trial Designs: Master Protocols

The 2018 Accelerating Anticancer Agent Development (AAADV) Workshop assembled a panel of experts for an in-depth discussion session to present "Challenges with Novel Clinical Trial Designs." This panel offered assessments of the challenges faced by industry, the FDA, investigators, institutional review boards, and patients. The panel focused on master protocols, which include umbrella trials, platform trials, and basket trials. Umbrella trials and platform trials share many commonalities, whereas basket trials are more distinct. Umbrella and platform trials are generally designed with multiple arms where patients of the same histology or other unifying characteristics are enrolled into different arms and multiple investigational agents are evaluated in a single protocol. In contrast, basket studies generally enroll patients with different tumor types based on the presence of a specific mutation or biomarker regardless of histology; these trials may include expansion cohorts. These novel designs offer the promise of expedited drug assessment and approval, but they also place new challenges on all the stakeholders involved in the drug development process. Only by identifying the challenges of these complex, innovative clinical trial designs and highlighting challenges from each perspective can we begin to address these challenges. The 2018 AAADV Workshop convened a panel of experts from relevant disciplines to highlight the challenges that are created by master protocols, and, where appropriate, offer strategies to address these challenges.

CDK 4/6 Inhibitors as Single Agent in Advanced Solid Tumors

Cyclin-dependent kinases (CDK) 4/6 inhibitors, namely abemaciclib, palbociclib, and ribociclib, interfere with cell cycle progression, induce cell senescence and might promote cancer cell disruption by a cytotoxic T cells-mediated effect. Phase III randomized clinical trials have proven that CDK4/6 inhibitors (CDK4/6i) in combination with several endocrine agents improve treatment efficacy over endocrine agents alone for hormone receptor positive (HR+) HER2 negative (HER2-) metastatic breast cancer (MBC). Based on such results, these combinations have been approved for clinical use. Preclinical studies in cell cultures and mouse models proved that CDK4/6i are active against a broad spectrum of solid tumors other than breast cancer, including liposarcoma, rhabdomyosarcoma, non-small cell lung cancer, glioblastoma multiforme, esophageal cancer, and melanoma. The role of CDK4/6i in monotherapy in several solid tumors is currently under evaluation in phase I, II, and III trials. Nowadays, abemaciclib is the only of the three inhibitors that has received approval as single agent therapy for pretreated HR+ HER2- MBC. Here we review biological, preclinical and clinical data on the role of CDK4/6 inhibitors as single agents in advanced solid tumors.

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Biomarker Clinical Trials in Lung Cancer: Design, Logistics, Challenges, and Practical Considerations

Treatment for lung cancer has evolved in the past 3 decades starting with platinum-based chemotherapy as the standard of care, regardless of histology, in the early 1990s to the current age of biomarker-driven therapy. Consequently, clinical trials in lung cancer have evolved in response to this new shift of paradigm, leading to novel approaches that simultaneously shorten the development process and allow evaluation of multiple patient cohorts. Herein, we provide an overview of the landscape of lung cancer clinical trials in the era of targeted therapies, precision medicine, and biomarkers. Specific trials are given as examples to illustrate the design paradigms. The paper is organized by drug development phases starting with early-phase biomarker discovery to proof-of-concept trials to definitive trials. We also present some thoughts on future directions.

Current landscape and future of dual anti-CTLA4 and PD-1/PD-L1 blockade immunotherapy in cancer; lessons learned from clinical trials with melanoma and non-small cell lung cancer (NSCLC)

Immunotherapy is among the most rapidly evolving treatment strategies in oncology. The therapeutic potential of immune-checkpoint inhibitors is exemplified by the recent hail of Food and Drug Administration (FDA) approvals for their use in various malignancies. Continued efforts to enhance outcomes with immunotherapy agents have led to the formulation of advanced treatment strategies. Recent evidence from pre-clinical studies evaluating immune-checkpoint inhibitors in various cancer cell-lines has suggested that combinatorial approaches may have superior survival outcomes compared to single-agent immunotherapy regimens. Preliminary trials assessing combination therapy with anti-PD-1/PD-L1 plus anti-CTLA-4 immune-checkpoint inhibitors have documented considerable advantages in survival indices over single-agent immunotherapy. The therapeutic potential of combinatorial approaches is highlighted by the recent FDA approval of nivolumab plus ipilimumab for patients with advanced melanoma. Presently, dual-immune checkpoint inhibition with anti-programmed death receptor-1/programmed cell death receptor- ligand-1 (anti-PD-1/PD-L1) plus anti-cytotoxic T lymphocyte associated antigen-4 (anti-CTLA-4) monoclonal antibodies (MoAbs) is being evaluated for a wide range of tumor histologies. Furthermore, several ongoing clinical trials are investigating combination checkpoint inhibition in association with traditional treatment modalities such as chemotherapy, surgery, and radiation. In this review, we summarize the current landscape of combination therapy with anti-PD-1/PD-L1 plus anti-CTLA-4 MoAbs for patients with melanoma and non-small cell lung cancer (NSCLC). We present a synopsis of the prospects for expanding the indications of dual immune-checkpoint inhibition therapy to a more diverse set of tumor histologies.

Controlled multi-arm platform design using predictive probability

The process of screening agents one-at-a-time under the current clinical trials system suffers from several deficiencies that could be addressed in order to extend financial and patient resources. In this article, we introduce a statistical framework for designing and conducting randomized multi-arm screening platforms with binary endpoints using Bayesian modeling. In essence, the proposed platform design consolidates inter-study control arms, enables investigators to assign more new patients to novel therapies, and accommodates mid-trial modifications to the study arms that allow both dropping poorly performing agents as well as incorporating new candidate agents. When compared to sequentially conducted randomized two-arm trials, screening platform designs have the potential to yield considerable reductions in cost, alleviate the bottleneck between phase I and II, eliminate bias stemming from inter-trial heterogeneity, and control for multiplicity over a sequence of a priori planned studies. When screening five experimental agents, our results suggest that platform designs have the potential to reduce the mean total sample size by as much as 40% and boost the mean overall response rate by as much as 15%. We explain how to design and conduct platform designs to achieve the aforementioned aims and preserve desirable frequentist properties for the treatment comparisons. In addition, we demonstrate how to conduct a platform design using look-up tables that can be generated in advance of the study. The gains in efficiency facilitated by platform design could prove to be consequential in oncologic settings, wherein trials often lack a proper control, and drug development suffers from low enrollment, long inter-trial latency periods, and an unacceptably high rate of failure in phase III.

Precision oncology: neither a silver bullet nor a dream

Precision oncology is not an illusion, nor is it the magic bullet that will eradicate all cancers. Precision oncology is simply another weapon in our growing armament against cancer. Rather than honing in on the failures of a relatively young field, one should advocate for integrating its successes into widespread clinical practice, especially for indications, such as: ABL, ALK, BRAF, BRCA1, BRCA2, EGFR, KIT, KRAS, PDGFRA, PDGFRB, ROS1, BCR-ABL, FLT3 and ROS1, where aberrations have been shown to alter responses to US FDA approved drugs - that is, level 1 data. Moreover, to truly assess the promise of precision oncology, we must first begin by defining our expectations for this field. Importantly, we must recognize that the conception of precision oncology arose as an antithesis of the 'one-size fits all' cancer therapeutics approach. Consequently, tools used for evaluating these conventional, large-scale trials, are not directly transferable for assessing nonconventional, smaller-scale trials needed for evaluating precision oncology. Hence, a thorough vetting of precision oncology as another tool of the trade, must first begin by reassessing our expectations for this field, as well as current clinical trial designs and end point measurements. Importantly, we must recognize that most targeted therapy approaches are in their infancy, with only monotherapy approaches being assessed and combination therapies likely being necessary to fulfill the promise of precision oncology.

Imprecision in the Era of Precision Medicine in Non-Small Cell Lung Cancer

Over the past decade, major advances have been made in the management of advanced non-small cell lung cancer (NSCLC). There has been a particular focus on the identification and targeting of putative driver aberrations, which has propelled NSCLC to the forefront of precision medicine. Several novel molecularly targeted agents have now achieved regulatory approval, while many others are currently in late-phase clinical trial testing. These antitumor therapies have significantly impacted the clinical outcomes of advanced NSCLC and provided patients with much hope for the future. Despite this, multiple deficiencies still exist in our knowledge of this complex disease, and further research is urgently required to overcome these critical issues. This review traces the path undertaken by the different therapeutics assessed in NSCLC and the impact of precision medicine in this disease. We also discuss the areas of "imprecision" that still exist in NSCLC and the modern hypothesis-testing studies being conducted to address these key challenges.

Second-Line Treatment of NSCLC-The Pan-ErbB Inhibitor Afatinib in Times of Shifting Paradigms

In contrast to the established role of epidermal growth factor receptor (EGFR) inhibitors for the first-line treatment of patients with non-small cell lung cancer (NSCLC) harboring activating EGFR mutations, the role of EGFR blockade and of EGFR molecular testing in the second-line treatment remains less clear. The irreversible pan-ErbB family inhibitor afatinib (Gi(l)otrif^®) was recently FDA- and EMA-approved for the second-line treatment of NSCLC with squamous cell histology irrespective of the EGFR mutational status (LUX-Lung 8). Contrariwise, results from the TAILOR and DELTA trials among retrospective biomarker analyses show the predictive value of the EGFR mutational status for efficacy of reversible EGFR inhibitors also as a second-line therapy. This mini review critically summarizes the current role of EGFR-targeting strategies in the second-line treatment of NSCLC with special respect to afatinib in light of emerging T790M-specific EGFR and immune check point inhibitors. The review also emphasizes the urgent need for reliable biomarkers to guide therapeutic decision-making and outlines prospective changes to the second-line landscape with some of the current second-line treatment concepts likely to be moved to the first-line.

Challenges and methodology in the incorporation of biomarkers in cancer clinical trials

Biomarkers can be used to establish more homogeneous groups using the genetic makeup of the tumour to inform the selection of treatment for each individual patient. However, proper preclinical work and stringent validation are needed before taking forward biomarkers into confirmatory studies. Despite the challenges, incorporation of biomarkers into clinical trials could better target appropriate patients, and potentially be lifesaving. The authors conducted a systematic review to describe marker-based and adaptive design methodology for their integration in clinical trials, and to further describe the associated practical challenges. Studies published between 1990 to November 2015 were searched on PubMed. Titles, abstracts and full text articles were reviewed to identify relevant studies. Of the 4438 studies examined, 57 studies were included. The authors conclude that the proposed approaches may readily help researchers to design biomarker trials, but novel approaches are still needed.

Comparing a stratified treatment strategy with the standard treatment in randomized clinical trials

The increasing emergence of predictive markers for different treatments in the same patient population allows us to define stratified treatment strategies. We consider randomized clinical trials that compare a standard treatment with a new stratified treatment strategy that divides the study population into subgroups receiving different treatments. Because the new strategy may not be beneficial in all subgroups, we consider in this paper an intermediate approach that establishes a treatment effect in a subset of patients built by joining several subgroups. The approach is based on the simple idea of selecting the subset with minimal p-value when testing the subset-specific treatment effects. We present a framework to compare this approach with other approaches to select subsets by introducing three performance measures. The results of a comprehensive simulation study are presented, and the relative merits of the various approaches are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

Managing Innovation to Maximize Value Along the Discovery-Translation-Application Continuum

Success in pharmaceutical development led to a record 51 drugs approved in the past year, surpassing every previous year since 1950. Technology innovation enabled identification and exploitation of increasingly precise disease targets ensuring next generation diagnostic and therapeutic products for patient management. The expanding biopharmaceutical portfolio stands, however, in contradistinction to the unsustainable costs that reflect remarkable challenges of clinical development programs. This annual Therapeutic Innovations issue juxtaposes advances in translating molecular breakthroughs into transformative therapies with essential considerations for lowering attrition and improving the cost-effectiveness of the drug-development paradigm. Realizing the discovery-translation-application continuum mandates a congruent approval, adoption, and access triad.

Next-Generation Sequencing to Guide Clinical Trials

Rapidly accruing knowledge of the mutational landscape of malignant neoplasms, the increasing facility of massively parallel genomic sequencing, and the availability of drugs targeting many "driver" molecular abnormalities have spurred the oncologic community to consider how to use these new tools to improve cancer treatment. In order to assure that assignment of patients to a particular targeted treatment is likely to be beneficial to the patient, it will be necessary to conduct appropriate clinical research. It is clear that clinical (histology and stage) eligibility criteria are not sufficient for most clinical trials using agents that target mutations that are present in only a minority of patients. Recently, several clinical trial designs have been suggested to test the benefit of targeted treatment in molecular and/or clinical subgroups of patients. However, challenges remain in the implementation of such trials, including choice of assay, levels of evidence regarding gene variants, tumor heterogeneity, identifying resistance mechanisms, the necessity of screening large numbers of patients, infrastructure needs, and collaboration of investigators and industry. This article reviews current trial designs and discusses some of the considerations, advantages, and drawbacks of designing clinical trials that depend on particular molecular variants as eligibility criteria.

Efficiencies of platform clinical trials: A vision of the future

BACKGROUND

A "platform trial" is a clinical trial with a single master protocol in which multiple treatments are evaluated simultaneously. Adaptive platform designs offer flexible features such as dropping treatments for futility, declaring one or more treatments superior, or adding new treatments to be tested during the course of a trial.

METHODS

A simulation study explores the efficiencies of various platform trial designs relative to a traditional two-arm strategy.

RESULTS

Platform trials can find beneficial treatments with fewer patients, fewer patient failures, less time, and with greater probability of success than a traditional two-arm strategy.

CONCLUSION

In an era of personalized medicine, platform trials provide the innovation needed to efficiently evaluate modern treatments.

The Master Protocol Concept

During the past decade, biomedical technologies have undergone an explosive evolution-from the publication of the first complete human genome in 2003, after more than a decade of effort and at a cost of hundreds of millions of dollars-to the present time, where a complete genomic sequence can be available in less than a day and at a small fraction of the cost of the original sequence. The widespread availability of next-generation genomic sequencing has opened the door to the development of precision oncology. The need to test multiple new targeted agents both alone and in combination with other targeted therapies, as well as classic cytotoxic agents, demands the development of novel therapeutic platforms (particularly Master Protocols) capable of efficiently and effectively testing multiple targeted agents or targeted therapeutic strategies in relatively small patient subpopulations. Here, we describe the Master Protocol concept, with a focus on the expected gains and complexities of the use of this design. An overview of Master Protocols currently active or in development is provided along with a more extensive discussion of the Lung Master Protocol (Lung-MAP study).