Biomarker-based adaptive trials for patients with glioblastoma--lessons from I-SPY 2

Inaugural Results of the Individualized Screening Trial of Innovative Glioblastoma Therapy: A Phase II Platform Trial for Newly Diagnosed Glioblastoma Using Bayesian Adaptive Randomization

PURPOSE

The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid-dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design.

PATIENTS AND METHODS

Patients with newly diagnosed O6-methylguanine-DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780).

RESULTS

Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit (P > .05).

CONCLUSION

The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.

Novel Clinical Trial Designs in Neuro-Oncology

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

High-grade glioma therapy: adding flexibility in trial design to improve patient outcomes

INTRODUCTION

Outcomes for patients with high grade gliomas have changed little over the past thirty years. This realization prompted renewed efforts to increase flexibility in the design and conduct of clinical brain tumor trials.

AREAS COVERED

This manuscript reviews the development of clinical trial methods, challenges and considerations of flexible clinical trial designs, approaches to improve identification and testing of active agents for high grade gliomas, and evaluation of their delivery to the central nervous system.

EXPERT OPINION

Flexibility can be introduced in clinical trials in several ways. Flexible designs tout smaller sample sizes, adaptive modifications, fewer control arms, and inclusion of multiple arms in one study. Unfortunately, modifications in study designs cannot address two challenges that are largely responsible for the lack of progress in treating high grade gliomas: 1) the identification of active pharmaceutical agents and 2) the delivery of these agents to brain tumor tissue in therapeutic concentrations. To improve the outcomes of patients with high grade gliomas efforts must be focused on the pre-clinical screening of drugs for activity, the ability of these agents to achieve therapeutic concentrations in non-enhancing tumors, and a willingness to introduce novel compounds in minimally pre-treated patient populations.

The current landscape of systemic therapy for recurrent glioblastoma: A systematic review of randomized-controlled trials

AIM

Conduct a systematic review of the effectiveness of systemic therapies for adult recurrent glioblastoma (rGBM).

METHODS

We electronically searched for randomized controlled trials from three major databases and four conferences from 2009-Dec 2020. Two independent reviewers conducted screening, data extraction, and quality assessment.

RESULTS

48 randomized trials were identified. Outcome reporting was inconsistent: overall survival (OS) in 46 studies, progression free survival in 37 studies, 6-month PFS in 30 studies, objective response rate in 28 studies, and 6-month OS in 7 studies. Network meta-analysis was not feasible due to heterogeneity in outcome reporting and single-study linkages. Most studies compared lomustine (8 studies), bevacizumab (18), or temozolomide (8) with other treatments. The median OS across all studies ranged from 3 to 17.6 months.

CONCLUSIONS

Based on level one evidence, there is no superior systemic regimen for rGBM. rGBM is a heterogeneous population with no single regimen demonstrating OS benefit. Registration number: CRD42020148512.

Prerequisites to support high-quality clinical trials in children and young people

Children have the right to treatment based on the same quality of information that guides treatment in adults. Without the proper evaluation of medicinal products and devices in paediatric clinical trials that are designed to meet the rigorous standards of the competent authorities, children are discriminated from advances in medicine. There are regulatory, scientific and ethical incentives to address the knowledge gap regarding efficacy and safety of medicines in the paediatric population. High-quality clinical trials involving children of all ages can generate data that will ultimately close the knowledge gaps and support decision making.For clinical trials that enrol children, the needs are specialised and often resource intensive. Prerequisites for successful paediatric clinical trials are personnel with training in both paediatrics and neonatology and expertise in clinical trials in these populations. Moreover, national and international networks for efficient collaboration, dissemination of information, and sharing of resources and expertise are also needed, together with competent, efficient and high-quality local infrastructure with effective processes. Monitoring and oversight bodies with the relevant competence, including expertise in paediatrics, is also an important prerequisite for paediatric clinical trials. Compromise in any of these components will compromise the downstream results.This paper discusses the structures and competences needed in order to perform effective, high-quality paediatric clinical trials with the ultimate goal of better medicines and treatments for children. We propose a model of examining the process as a series of components that each has to be optimised, then all the components are actively optimised to function together as an ecosystem, and the resulting ecosystem functions well with the general research system and the healthcare delivery system.

Challenges in clinical trials for children and young people

There is a well-known knowledge gap regarding the efficacy and safety of medicines in children of all ages and children are often treated with medicines off-label. Children are thus deprived of treatment based on the same quality of information that guides treatment in adults. The knowledge gap regarding efficacy and safety of medicines in children has been acknowledged by authorities and is reflected in legislation both in North America and in the European Union. Recent reports on the effects of legislation indicates that paediatric clinical trials remain a challenge.Paediatric clinical trials are needed in the entire developmental age spectrum and are especially needed in certain therapy areas. Paediatric clinical trials have special features compared with trials in adults, and these need to be taken into account. These special features include scientific issues related to small samples and heterogeneity, the consent/assent procedure, the need for age-appropriate study information, specific outcomes and safety issues related to development and maturation. Competence in paediatric clinical trials is required in both designing, planning, co-ordinating and organising paediatric clinical trials, as well as research infrastructure and networks to increase power and disseminate information and expert advice. Strengthening of paediatric clinical research is essential to facilitate generating the data that will let children enjoy new medical advances in a similar manner as adults.

I-SPY 2: a Neoadjuvant Adaptive Clinical Trial Designed to Improve Outcomes in High-Risk Breast Cancer

Purpose of Review

The I-SPY 2 trial is an adaptive clinical trial platform designed to improve outcomes in high-risk breast cancer patients by testing new drugs in the neoadjuvant setting. The intent of this review is to discuss background, study structure, innovation, and outcomes of the I-SPY 2 trial.

Recent Findings

I-SPY 2 evaluates new agents combined with standard therapy with pathologic complete response (pCR) as the primary endpoint. I-SPY-2 uses clinical biomarkers to classify breast cancer into 10 subtypes, with Bayesian adaptive randomization to allow individualized patient assignment to therapy arms to maximize treatment effects. A total of 7 drugs have graduated from I-SPY 2. Multiple new agents are currently in active enrollment in I-SPY 2.

Summary

I-SPY 2 uses an individualized approach in clinical trial design to improve high-risk breast cancer outcomes. The purpose of this review is to encourage further research and innovation in this area and bring more precise treatment options to breast cancer patients.

The clinical trials landscape for glioblastoma: is it adequate to develop new treatments?

Background

There have been few treatment advances for patients with glioblastoma (GBM) despite increasing scientific understanding of the disease. While factors such as intrinsic tumor biology and drug delivery are challenges to developing efficacious therapies, it is unclear whether the current clinical trial landscape is optimally evaluating new therapies and biomarkers.

Methods

We queried ClinicalTrials.gov for interventional clinical trials for patients with GBM initiated between January 2005 and December 2016 and abstracted data regarding phase, status, start and end dates, testing locations, endpoints, experimental interventions, sample size, clinical presentation/indication, and design to better understand the clinical trials landscape.

Results

Only approximately 8%-11% of patients with newly diagnosed GBM enroll on clinical trials with a similar estimate for all patients with GBM. Trial duration was similar across phases with median time to completion between 3 and 4 years. While 93% of clinical trials were in phases I-II, 26% of the overall clinical trial patient population was enrolled on phase III studies. Of the 8 completed phase III trials, only 1 reported positive results. Although 58% of the phase III trials were supported by phase II data with a similar endpoint, only 25% of these phase II trials were randomized.

Conclusions

The clinical trials landscape for GBM is characterized by long development times, inadequate dissemination of information, suboptimal go/no-go decision making, and low patient participation.

Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT): A Bayesian Adaptive Platform Trial to Develop Precision Medicines for Patients With Glioblastoma

PURPOSE

Adequately prioritizing the numerous therapies and biomarkers available in late-stage testing for patients with glioblastoma (GBM) requires an efficient clinical testing platform. We developed and implemented INSIGhT (Individualized Screening Trial of Innovative Glioblastoma Therapy) as a novel adaptive platform trial (APT) to develop precision medicine approaches in GBM.

METHODS

INSIGhT compares experimental arms with a common control of standard concurrent temozolomide and radiation therapy followed by adjuvant temozolomide. The primary end point is overall survival. Patients with newly diagnosed unmethylated GBM who are IDH R132H mutation negative and with genomic data available for biomarker grouping are eligible. At the initiation of INSIGhT, three experimental arms (neratinib, abemaciclib, and CC-115), each with a proposed genomic biomarker, are tested simultaneously. Initial randomization is equal across arms. As the trial progresses, randomization probabilities adapt on the basis of accumulating results using Bayesian estimation of the biomarker-specific probability of treatment impact on progression-free survival. Treatment arms may drop because of low probability of treatment impact on overall survival, and new arms may be added. Detailed information on the statistical model and randomization algorithm is provided to stimulate discussion on trial design choices more generally and provide an example for other investigators developing APTs.

CONCLUSION

INSIGhT (NCT02977780) is an ongoing novel biomarker-based, Bayesian APT for patients with newly diagnosed unmethylated GBM. Our goal is to dramatically shorten trial execution timelines while increasing scientific power of results and biomarker discovery using adaptive randomization. We anticipate that trial execution efficiency will also be improved by using the APT format, which allows for the collaborative addition of new experimental arms while retaining the overall trial structure.

Therapy for glioblastoma: is it working?

Glioblastoma (GBM) remains one of the most intransigent of cancers, with a median overall survival of only 15 months after diagnosis. Drug treatments have largely proven ineffective; it is thought that this is related to the heterogeneous nature and plasticity of GBM-initiating stem cell lineages. Although many combination drug therapies are being positioned to address tumour heterogeneity, the most promising therapeutic approaches for GBM to date appear to be those targeting GBM by vaccination or antibody- and cell-based immunotherapy. We review the most recent clinical trials for GBM and discuss the role of adaptive clinical trials in developing personalised treatment strategies to address intra- and inter-tumoral heterogeneity.

Recommendations for the design of small population clinical trials

Background

Orphan drug development faces numerous challenges, including low disease prevalence, patient population heterogeneity, and strong presence of paediatric patient populations. Consequently, clinical trials for orphan drugs are often smaller than those of non-orphan drugs, and they require the development of efficient trial designs relevant to small populations to gain the most information from the available data. The International Rare Diseases Research Consortium (IRDiRC) is aimed at promoting international collaboration and advance rare diseases research worldwide, and has as one of its goals to contribute to 1000 new therapies for rare diseases. IRDiRC set up a Small Population Clinical Trials (SPCT) Task Force in order to address the shortcomings of our understanding in carrying out clinical trials in rare diseases.

Results

The IRDiRC SPCT Task Force met in March 2016 to discuss challenges faced in the design of small studies for rare diseases and present their recommendations, structured around six topics: different study methods/designs and their relation to different characteristics of medical conditions, adequate safety data, multi-arm trial designs, decision analytic approaches and rational approaches to adjusting levels of evidence, extrapolation, and patients’ engagement in study design.

Conclusions

Recommendations have been issued based on discussions of the Small Population Clinical Trials Task Force that aim to contribute towards successful therapy development and clinical use. While randomised clinical trials are still considered the gold standard, it is recommended to systematically take into consideration alternative trial design options when studying treatments for a rare disease. Combining different sources of safety data is important to give a fuller picture of a therapy’s safety profile. Multi-arm trials should be considered an opportunity for rare diseases therapy development, and funders are encouraged to support such trial design via international networks. Patient engagement is critical in trial design and therapy development, a process which sponsors are encouraged to incorporate when conducting trials and clinical studies. Input from multiple regulatory agencies is recommended early and throughout clinical development. Regulators are often supportive of new clinical trial designs, provided they are well thought through and justified, and they also welcome discussions and questions on this topic. Parallel advice for multiregional development programs should also be considered.

Highlighting the need for reliable clinical trials in glioblastoma

INTRODUCTION

Several recent phase III studies have attempted to improve the dismal survival seen in glioblastoma patients, with disappointing results despite prior promising phase II data. Areas covered: A literature review of prior phase II and phase III studied in glioblastoma was performed to help identify possible areas of concern. Numerous issues in previous phase II trials for glioblastoma were found that may have contributed to these discouraging outcomes and discordant results. Expert commentary: These concerns include the improper selection of therapeutics warranting investigation in a phase III trial, suboptimal design of phase II studies (often lacking a control arm), absence of molecular data, the use of imaging criteria as a surrogate endpoint, and a lack of pharmacodynamic testing. Hopefully, by recognizing prior phase II trial limitations that contributed to failed phase III trials, we can adapt quickly to improve our ability to accurately discover survival-prolonging treatments for glioblastoma patients.

Clinical trial endpoints for patients with gliomas

Malignant glioma represents a diverse set of molecularly heterogeneous diseases. Few therapeutic agents have been approved despite decades of clinical trials research and pre-clinical investigation. Attempts to refine neuroimaging criteria and recent discovery of the genomic profiles linking tumor subsets to survival outcomes have spurred discussion on a variety of new approaches in clinical trial design and relevant endpoints. Here we focus on those endpoints in clinical trial design for patients with primary glioma and related issues still to be resolved.

Unbiased estimation for response adaptive clinical trials

Bayesian adaptive trials have the defining feature that the probability of randomization to a particular treatment arm can change as information becomes available as to its true worth. However, there is still a general reluctance to implement such designs in many clinical settings. One area of concern is that their frequentist operating characteristics are poor or, at least, poorly understood. We investigate the bias induced in the maximum likelihood estimate of a response probability parameter, p, for binary outcome by the process of adaptive randomization. We discover that it is small in magnitude and, under mild assumptions, can only be negative - causing one's estimate to be closer to zero on average than the truth. A simple unbiased estimator for p is obtained, but it is shown to have a large mean squared error. Two approaches are therefore explored to improve its precision based on inverse probability weighting and Rao-Blackwellization. We illustrate these estimation strategies using two well-known designs from the literature.

Adult Glioblastoma

Glioblastoma (GBM) is a rare tumor and one of the most challenging malignancies to treat in all of oncology. Although advances have been made in the treatment of GBM, encouraging outcomes typically are not observed; patients diagnosed with these tumors generally have a dismal prognosis and poor quality of life as the disease progresses. This review summarizes the clinical presentation of GBM, diagnostic methods, evidentiary basis for the current standards of care, and investigational approaches to treat or manage GBM. Because the track record for developing effective therapies for GBM has been dismal, we also review the challenges to successful therapeutic and biomarker development.

PIPELINEs: Creating Comparable Clinical Knowledge Efficiently by Linking Trial Platforms

Adaptive, seamless, multisponsor, multitherapy clinical trial designs executed as large scale platforms, could create superior evidence more efficiently than single-sponsor, single-drug trials. These trial PIPELINEs also could diminish barriers to trial participation, increase the representation of real-world populations, and create systematic evidence development for learning throughout a therapeutic life cycle, to continually refine its use. Comparable evidence could arise from multiarm design, shared comparator arms, and standardized endpoints-aiding sponsors in demonstrating the distinct value of their innovative medicines; facilitating providers and patients in selecting the most appropriate treatments; assisting regulators in efficacy and safety determinations; helping payers make coverage and reimbursement decisions; and spurring scientists with translational insights. Reduced trial times and costs could enable more indications, reduced development cycle times, and improved system financial sustainability. Challenges to overcome range from statistical to operational to collaborative governance and data exchange.

A Bayesian response-adaptive trial in tuberculosis: The endTB trial

PURPOSE

To evaluate the use of Bayesian adaptive randomization for clinical trials of new treatments for multidrug-resistant tuberculosis.

METHODS

We built a response-adaptive randomization procedure, adapting on two preliminary outcomes for tuberculosis patients in a trial with five experimental regimens and a control arm. The primary study outcome is treatment success after 73 weeks from randomization; preliminary responses are culture conversion at 8 weeks and treatment success at 39 weeks. We compared the adaptive randomization design with balanced randomization using hypothetical scenarios.

RESULTS

When we compare the statistical power under adaptive randomization and non-adaptive designs, under several hypothetical scenarios we observe that adaptive randomization requires fewer patients than non-adaptive designs. Moreover, adaptive randomization consistently allocates more participants to effective arm(s). We also show that these advantages are limited to scenarios consistent with the assumptions used to develop the adaptive randomization algorithm.

CONCLUSION

Given the objective of evaluating several new therapeutic regimens in a timely fashion, Bayesian response-adaptive designs are attractive for tuberculosis trials. This approach tends to increase allocation to the effective regimens.

Re-Engineering Alzheimer Clinical Trials: Global Alzheimer's Platform Network

Alzheimer's disease (AD) drug development is costly, time-consuming, and inefficient. Trial site functions, trial design, and patient recruitment for trials all require improvement. The Global Alzheimer Platform (GAP) was initiated in response to these challenges. Four GAP work streams evolved in the US to address different trial challenges: 1) registry-to-cohort web-based recruitment; 2) clinical trial site activation and site network construction (GAP-NET); 3) adaptive proof-of-concept clinical trial design; and 4) finance and fund raising. GAP-NET proposes to establish a standardized network of continuously funded trial sites that are highly qualified to perform trials (with established clinical, biomarker, imaging capability; certified raters; sophisticated management system. GAP-NET will conduct trials for academic and biopharma industry partners using standardized instrument versions and administration. Collaboration with the Innovative Medicines Initiative (IMI) European Prevention of Alzheimer's Disease (EPAD) program, the Canadian Consortium on Neurodegeneration in Aging (CCNA) and other similar international initiatives will allow conduct of global trials. GAP-NET aims to increase trial efficiency and quality, decrease trial redundancy, accelerate cohort development and trial recruitment, and decrease trial costs. The value proposition for sites includes stable funding and uniform training and trial execution; the value to trial sponsors is decreased trial costs, reduced time to execute trials, and enhanced data quality. The value for patients and society is the more rapid availability of new treatments for AD.

Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

BACKGROUND

Personalized medicine is a growing area of research which aims to tailor the treatment given to a patient according to one or more personal characteristics. These characteristics can be demographic such as age or gender, or biological such as a genetic or other biomarker. Prior to utilizing a patient's biomarker information in clinical practice, robust testing in terms of analytical validity, clinical validity and clinical utility is necessary. A number of clinical trial designs have been proposed for testing a biomarker's clinical utility, including Phase II and Phase III clinical trials which aim to test the effectiveness of a biomarker-guided approach to treatment; these designs can be broadly classified into adaptive and non-adaptive. While adaptive designs allow planned modifications based on accumulating information during a trial, non-adaptive designs are typically simpler but less flexible.

METHODS AND FINDINGS

We have undertaken a comprehensive review of biomarker-guided adaptive trial designs proposed in the past decade. We have identified eight distinct biomarker-guided adaptive designs and nine variations from 107 studies. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. We have graphically displayed the current biomarker-guided adaptive trial designs and summarised the characteristics of each design.

CONCLUSIONS

Our in-depth overview provides future researchers with clarity in definition, methodology and terminology for biomarker-guided adaptive trial designs.

Molecular classification of gliomas

The identification of distinct genetic and epigenetic profiles in different types of gliomas has revealed novel diagnostic, prognostic, and predictive molecular biomarkers for refinement of glioma classification and improved prediction of therapy response and outcome. Therefore, the new (2016) World Health Organization (WHO) classification of tumors of the central nervous system breaks with the traditional principle of diagnosis based on histologic criteria only and incorporates molecular markers. This will involve a multilayered approach combining histologic features and molecular information in an "integrated diagnosis". We review the current state of diagnostic molecular markers for gliomas, focusing on isocitrate dehydrogenase 1 or 2 (IDH1/IDH2) gene mutation, α-thalassemia/mental retardation syndrome X-linked (ATRX) gene mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutation in adult tumors, as well as v-raf murine sarcoma viral oncogene homolog B1 (BRAF) and H3 histone family 3A (H3F3A) aberrations in pediatric gliomas. We also outline prognostic and predictive molecular markers, including O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, and discuss the potential clinical relevance of biologic glioblastoma subtypes defined by integration of multiomics data. Commonly used methods for individual marker detection as well as novel large-scale DNA methylation profiling and next-generation sequencing approaches are discussed. Finally, we illustrate how advances in molecular diagnostics affect novel strategies of targeted therapy, thereby raising new challenges and identifying new leads for personalized treatment of glioma patients.

Optimal Bayesian adaptive trials when treatment efficacy depends on biomarkers

Clinical biomarkers play an important role in precision medicine and are now extensively used in clinical trials, particularly in cancer. A response adaptive trial design enables researchers to use treatment results about earlier patients to aid in treatment decisions of later patients. Optimal adaptive trial designs have been developed without consideration of biomarkers. In this article, we describe the mathematical steps for computing optimal biomarker-integrated adaptive trial designs. These designs maximize the expected trial utility given any pre-specified utility function, though we focus here on maximizing patient responses within a given patient horizon. We describe the performance of the optimal design in different scenarios. We compare it to Bayesian Adaptive Randomization (BAR), which is emerging as a practical approach to develop adaptive trials. The difference in expected utility between BAR and optimal designs is smallest when the biomarker subgroups are highly imbalanced. We also compare BAR, a frequentist play-the-winner rule with integrated biomarkers and a marker-stratified balanced randomization design (BR). We show that, in contrasting two treatments, BR achieves a nearly optimal expected utility when the patient horizon is relatively large. Our work provides novel theoretical solution, as well as an absolute benchmark for the evaluation of trial designs in personalized medicine.

Limited advances in therapy of glioblastoma trigger re-consideration of research policy

Glioblastoma (GB - WHO grade IV) is the most frequent and lethal primary brain tumour with median overall survival of 7-15 months after diagnosis. As in other cancer research areas, an overwhelming amount of pre-clinical research acquisitions in the GB field have not been translated to patients' benefit, potentially due to inappropriate treatment schedules and/or trial designs in the clinical setting. The recent failure of promising anti-VEGF bevacizumab to improve GB patients' overall survival recapitulates this sense of frustration. The following measures are proposed.

Contemporary murine models in preclinical astrocytoma drug development

Despite 6 decades of research, only 3 drugs have been approved for astrocytomas, the most common malignant primary brain tumors. However, clinical drug development is accelerating with the transition from empirical, cytotoxic therapy to precision, targeted medicine. Preclinical animal model studies are critical for prioritizing drug candidates for clinical development and, ultimately, for their regulatory approval. For decades, only murine models with established tumor cell lines were available for such studies. However, these poorly represent the genomic and biological properties of human astrocytomas, and their preclinical use fails to accurately predict efficacy in clinical trials. Newer models developed over the last 2 decades, including patient-derived xenografts, genetically engineered mice, and genetically engineered cells purified from human brains, more faithfully phenocopy the genomics and biology of human astrocytomas. Harnessing the unique benefits of these models will be required to identify drug targets, define combination therapies that circumvent inherent and acquired resistance mechanisms, and develop molecular biomarkers predictive of drug response and resistance. With increasing recognition of the molecular heterogeneity of astrocytomas, employing multiple, contemporary models in preclinical drug studies promises to increase the efficiency of drug development for specific, molecularly defined subsets of tumors.

Brain Malignancy Steering Committee clinical trials planning workshop: report from the Targeted Therapies Working Group

Glioblastoma is the most common primary brain malignancy and is associated with poor prognosis despite aggressive local and systemic therapy, which is related to a paucity of viable treatment options in both the newly diagnosed and recurrent settings. Even so, the rapidly increasing number of targeted therapies being evaluated in oncology clinical trials offers hope for the future. Given the broad range of possibilities for future trials, the Brain Malignancy Steering Committee convened a clinical trials planning meeting that was held at the Udvar-Hazy Center in Chantilly, Virginia, on September 19 and 20, 2013. This manuscript reports the deliberations leading up to the event from the Targeted Therapies Working Group and the results of the meeting.

Current and investigational drug strategies for glioblastoma

Medical treatments for glioblastoma face several challenges. Lipophilic alkylators remain the mainstay of treatment, emphasising the primacy of good blood-brain barrier penetration. Temozolomide has emerged as a major contributor to improved patient survival. The roles of procarbazine and vincristine in the procarbazine, lomustine and vincristine (PCV) schedule have attracted scrutiny and several lines of evidence now support the use of lomustine as effective single-agent therapy. Bevacizumab has had a convoluted development history, but clearly now has no major role in first-line treatment, and may even be detrimental to quality of life in this setting. In later disease, clinically meaningful benefits are achievable in some patients, but more impressively the combination of bevacizumab and lomustine shows early promise. Over the last decade, investigational strategies in glioblastoma have largely subscribed to the targeted kinase inhibitor paradigm and have mostly failed. Low prevalence dominant driver lesions such as the FGFR-TACC fusion may represent a niche role for this agent class. Immunological, metabolic and radiosensitising approaches are being pursued and offer more generalised efficacy. Finally, trial design is a crucial consideration. Progress in clinical glioblastoma research would be greatly facilitated by improved methodologies incorporating: (i) routine pharmacokinetic and pharmacodynamic assessments by preoperative dosing; and (ii) multi-stage, multi-arm protocols incorporating new therapy approaches and high-resolution biology in order to guide necessary improvements in science.