Precision medicine needs randomized clinical trials

Early Efficacy End Points in Neoadjuvant Rectal Cancer Trials: Surrogacy Revisited

Trial-level surrogacy is critical before early response endpoints are used to approve new therapies.

Bayesian Sequential Design for Identifying and Ranking Effective Patient Subgroups in Precision Medicine in the Case of Counting Outcome Data with Inflated Zeros

Precision medicine is revolutionizing health care, particularly by addressing patient variability due to different biological profiles. As traditional treatments may not always be appropriate for certain patient subsets, the rise of biomarker-stratified clinical trials has driven the need for innovative methods. We introduced a Bayesian sequential scheme to evaluate therapeutic interventions in an intensive care unit setting, focusing on complex endpoints characterized by an excess of zeros and right truncation. By using a zero-inflated truncated Poisson model, we efficiently addressed this data complexity. The posterior distribution of rankings and the surface under the cumulative ranking curve (SUCRA) approach provided a comprehensive ranking of the subgroups studied. Different subsets of subgroups were evaluated depending on the availability of biomarker data. Interim analyses, accounting for early stopping for efficacy, were an integral aspect of our design. The simulation study demonstrated a high proportion of correct identification of the subgroup which is the most predictive of the treatment effect, as well as satisfactory false positive and true positive rates. As the role of personalized medicine grows, especially in the intensive care setting, it is critical to have designs that can manage complicated endpoints and that can control for decision error. Our method seems promising in this challenging context.

Estimation of treatment effects in early-phase randomized clinical trials involving external control data

There are good reasons to perform a randomized controlled trial (RCT) even in early phases of clinical development. However, the low sample sizes in those settings lead to high variability of the treatment effect estimate. The variability could be reduced by adding external control data if available. For the common setting of suitable subject-level control group data only available from one external (clinical trial or real-world) data source, we evaluate different analysis options for estimating the treatment effect via hazard ratios. The impact of the external control data is usually guided by the level of similarity with the current RCT data. Such level of similarity can be determined via outcome and/or baseline covariate data comparisons. We provide an overview over existing methods, propose a novel option for a combined assessment of outcome and baseline data, and compare a selected set of approaches in a simulation study under varying assumptions regarding observable and unobservable confounder distributions using a time-to-event model. Our various simulation scenarios also reflect the differences between external clinical trial and real-world data. Data combinations via simple outcome-based borrowing or simple propensity score weighting with baseline covariate data are not recommended. Analysis options which conflate outcome and baseline covariate data perform best in our simulation study.

Trial Design for Cancer Immunotherapy: A Methodological Toolkit

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

Pharmaco-proteogenomic characterization of liver cancer organoids for precision oncology

Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.

Bayesian modelling strategies for borrowing of information in randomised basket trials

Basket trials are an innovative precision medicine clinical trial design evaluating a single targeted therapy across multiple diseases that share a common characteristic. To date, most basket trials have been conducted in early-phase oncology settings, for which several Bayesian methods permitting information sharing across subtrials have been proposed. With the increasing interest of implementing randomised basket trials, information borrowing could be exploited in two ways; considering the commensurability of either the treatment effects or the outcomes specific to each of the treatment groups between the subtrials. In this article, we extend a previous analysis model based on distributional discrepancy for borrowing over the subtrial treatment effects ('treatment effect borrowing', TEB) to borrowing over the subtrial groupwise responses ('treatment response borrowing', TRB). Simulation results demonstrate that both modelling strategies provide substantial gains over an approach with no borrowing. TRB outperforms TEB especially when subtrial sample sizes are small on all operational characteristics, while the latter has considerable gains in performance over TRB when subtrial sample sizes are large, or the treatment effects and groupwise mean responses are noticeably heterogeneous across subtrials. Further, we notice that TRB, and TEB can potentially lead to different conclusions in the analysis of real data.

Challenges and the Evolving Landscape of Assessing Blood-Based PD-L1 Expression as a Biomarker for Anti-PD-(L)1 Immunotherapy

While promising, PD-L1 expression on tumor tissues as assessed by immunohistochemistry has been shown to be an imperfect biomarker that only applies to a limited number of cancers, whereas many patients with PD-L1-negative tumors still respond to anti-PD-(L)1 immunotherapy. Recent studies using patient blood samples to assess immunotherapeutic responsiveness suggests a promising approach to the identification of novel and/or improved biomarkers for anti-PD-(L)1 immunotherapy. In this review, we discuss the advances in our evolving understanding of the regulation and function of PD-L1 expression, which is the foundation for developing blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy. We further discuss current knowledge and clinical study results for biomarker identification using PD-L1 expression on tumor and immune cells, exosomes, and soluble forms of PD-L1 in the peripheral blood. Finally, we discuss key challenges for the successful development of the potential use of blood-based PD-L1 as a biomarker for anti-PD-(L)1 immunotherapy.

International consensus recommendations on key outcome measures for organ preservation after (chemo)radiotherapy in patients with rectal cancer

Multimodal treatment strategies for patients with rectal cancer are increasingly including the possibility of organ preservation, through nonoperative management or local excision. Organ preservation strategies can enable patients with a complete response or near-complete clinical responses after radiotherapy with or without concomitant chemotherapy to safely avoid the morbidities associated with radical surgery, and thus to maintain anorectal function and quality of life. However, standardization of the key outcome measures of organ preservation strategies is currently lacking; this includes a lack of consensus of the optimal definitions and selection of primary end points according to the trial phase and design; the optimal time points for response assessment; response-based decision-making; follow-up schedules; use of specific anorectal function tests; and quality of life and patient-reported outcomes. Thus, a consensus statement on outcome measures is necessary to ensure consistency and facilitate more accurate comparisons of data from ongoing and future trials. Here, we have convened an international group of experts with extensive experience in the management of patients with rectal cancer, including organ preservation approaches, and used a Delphi process to establish the first international consensus recommendations for key outcome measures of organ preservation, in an attempt to standardize the reporting of data from both trials and routine practice in this emerging area.

Of some innovations in clinical trial design in hematology and oncology

The design of clinical trials, formalized in the immediate post-war period, has undergone major changes due to therapeutic innovations, particularly the arrival of targeted therapies in onco-hematology. The traditional phase I-II-III regimen is regularly questioned and multiple adaptations are proposed. This article proposes to expose some of these modifications and the issues they lead to.

Using numerical modeling and simulation to assess the ethical burden in clinical trials and how it relates to the proportion of responders in a trial sample

In order to propose a more precise definition and explore how to reduce ethical losses in randomized controlled clinical trials (RCTs), we set out to identify trial participants who do not contribute to demonstrating that the treatment in the experimental arm is superior to that in the control arm. RCTs emerged mid-last century as the gold standard for assessing efficacy, becoming the cornerstone of the value of new therapies, yet their ethical grounds are a matter of debate. We introduce the concept of unnecessary participants in RCTs, the sum of non-informative participants and non-responders. The non-informative participants are considered not informative with respect to the efficacy measured in the trial in contrast to responders who carry all the information required to conclude on the treatment's efficacy. The non-responders present the event whether or not they are treated with the experimental treatment. The unnecessary participants carry the burden of having to participate in a clinical trial without benefiting from it, which might include experiencing side effects. Thus, these unnecessary participants carry the ethical loss that is inherent to the RCT methodology. On the contrary, responders to the experimental treatment bear its entire efficacy in the RCT. Starting from the proportions observed in a real placebo-controlled trial from the literature, we carried out simulations of RCTs progressively increasing the proportion of responders up to 100%. We show that the number of unnecessary participants decreases steadily until the RCT's ethical loss reaches a minimum. In parallel, the trial sample size decreases (presumably its cost as well), although the trial's statistical power increases as shown by the increase of the chi-square comparing the event rates between the two arms. Thus, we expect that increasing the proportion of responders in RCTs would contribute to making them more ethically acceptable, with less false negative outcomes.

Basket clinical trial design for targeted therapies for cancer: a French National Authority for Health statement for health technology assessment

During the past decade, health technology assessment bodies have faced new challenges in establishing the benefits of new drugs for individuals and health-care systems. A topic of increasing importance to the field of oncology is the so-called agnostic regulatory approval of targeted therapies for cancer (independent of tumour location and histology) granted on the basis of basket trials. Basket trials in oncology offer the advantage of simultaneously evaluating treatments for multiple tumours, even rare cancers, in a single clinical trial. To address the novel challenges introduced by these trials, an interdisciplinary panel was convened on behalf of the Transparency Committee of the French National Authority for Health to clarify an approach designed to guarantee a transparent, reproducible, and fair assessment of histology-agnostic treatments for reimbursement by the French National Health Insurance Fund. The requirements of this approach include the need for randomisation, clinically relevant endpoints, appropriate correction for multiple significance testing, characterisation of subgroup heterogeneity, and validation of underlying biomarker assays. A prospectively designated external control is encouraged when the implementation of a direct comparison is deemed infeasible. We also underline the importance of recording outcomes from basket trials in a registry for use as future external controls.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

The evidence landscape in precision medicine

Precision medicine is beginning to make an impact on the treatment of different diseases, but there are still challenges that must be overcome, such as the complexity of interventions, the need for marker validation, and the level of evidence necessary to demonstrate effectiveness. In this Perspective, we describe how evidence landscapes can help to address these challenges.

Patient Participation in Clinical Trials of Oncology Drugs and Biologics Preceding Approval by the US Food and Drug Administration

IMPORTANCE

Several studies have estimated the financial inputs for successful drug development. Such analyses do not capture the large investment that patient study participants commit to drug development.

OBJECTIVE

To estimate the volume of patients required to achieve a first US Food and Drug Administration (FDA) approval for a new anticancer drug or biologic therapy.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included a random sample of prelicense oncology drugs and biologics with a trial site in the United States that were launched into clinical efficacy testing between January 1, 2006, and December 31, 2010. Drugs and biologics were identified using ClinicalTrials.gov registration records. Total patient enrollment was captured over an 8-year span, and each intervention was classified based on whether it received FDA approval and was deemed as having intermediate or substantial value according to the American Society of Clinical Oncology Value Framework (ASCO-VF) score. Secondarily, the association between patient numbers and intervention characteristics was tested. Data were analyzed in February 2020.

MAIN OUTCOMES AND MEASURE

The prespecified primary outcome was the number of patients enrolled in prelicense trials per FDA approval.

RESULTS

A total of 120 drugs and biologics were included in our study, with 84 (70.0%) targeted agents, 20 (16.7%) immunotherapies, and 71 (59.2%) novel agents. A total of 13 drugs and biologics (10.8%; 95% CI, 5.3%-16.8%) in our sample gained FDA approval within 8 years, of which 1 (7.7%) was deemed of intermediate value and 3 (23.1%) were deemed of substantial value using ASCO-VF scoring. Overall, 158 810 patients were enrolled in 1335 trials testing these drugs and biologics, 47 913 (30.2%) in trials that led to FDA approval and 110 897 (69.8%) in trials that did not. An estimated 12 217 (95% CI, 7970-22 215) patient study participants contributed to prelicense trials per FDA approval. The estimated number of patients needed to produce a single FDA-approved drug or biologic of intermediate or substantial ASCO-VF clinical value was 39 703 (95% CI, 19 391-177 991).

CONCLUSIONS AND RELEVANCE

The results of this cohort study make visible the substantial patient investment required for prelicense oncology drug development. Such analyses can be used to devise policies that maximize the clinical impact of research on a per-patient basis.

The next horizon in precision oncology: Proteogenomics to inform cancer diagnosis and treatment

When it comes to precision oncology, proteogenomics may provide better prospects to the clinical characterization of tumors, help make a more accurate diagnosis of cancer, and improve treatment for patients with cancer. This perspective describes the significant contributions of The Cancer Genome Atlas and the Clinical Proteomic Tumor Analysis Consortium to precision oncology and makes the case that proteogenomics needs to be fully integrated into clinical trials and patient care in order for precision oncology to deliver the right cancer treatment to the right patient at the right dose and at the right time.

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.

Precision Oncology, Signaling and Anticancer Agents in Cancer Therapeutics

BACKGROUND

The global alliance for genomics and healthcare facilities provides innovational solutions to expedite research and clinical practices for complex and incurable health conditions. Precision oncology is an emerging field explicitly tailored to facilitate cancer diagnosis, prevention and treatment based on patients' genetic profile. Advancements in "omics" techniques, next-generation sequencing, artificial intelligence and clinical trial designs provide a platform for assessing the efficacy and safety of combination therapies and diagnostic procedures.

METHOD

Data were collected from Pubmed and Google scholar using keywords: "Precision medicine", "precision medicine and cancer", "anticancer agents in precision medicine" and reviewed comprehensively.

RESULTS

Personalized therapeutics including immunotherapy, cancer vaccines, serve as a groundbreaking solution for cancer treatment. Herein, we take a measurable view of precision therapies and novel diagnostic approaches targeting cancer treatment. The contemporary applications of precision medicine have also been described along with various hurdles identified in the successful establishment of precision therapeutics.

CONCLUSION

This review highlights the key breakthroughs related to immunotherapies, targeted anticancer agents, and target interventions related to cancer signaling mechanisms. The success story of this field in context to drug resistance, safety, patient survival and in improving quality of life is yet to be elucidated. We conclude that, in the near future, the field of individualized treatments may truly revolutionize the nature of cancer patient care.

Molecular Profiling-Based Assignment of Cancer Therapy (NCI-MPACT): A Randomized Multicenter Phase II Trial

This trial assessed the utility of applying tumor DNA sequencing to treatment selection for patients with advanced, refractory cancer and somatic mutations in one of four signaling pathways by comparing the efficacy of four study regimens that were either matched to the patient's aberrant pathway (experimental arm) or not matched to that pathway (control arm).

MATERIALS AND METHODS

Adult patients with an actionable mutation of interest were randomly assigned 2:1 to receive either (1) a study regimen identified to target the aberrant pathway found in their tumor (veliparib with temozolomide or adavosertib with carboplatin [DNA repair pathway], everolimus [PI3K pathway], or trametinib [RAS/RAF/MEK pathway]), or (2) one of the same four regimens, but chosen from among those not targeting that pathway.

RESULTS

Among 49 patients treated in the experimental arm, the objective response rate was 2% (95% CI, 0% to 10.9%). One of 20 patients (5%) in the experimental trametinib cohort had a partial response. There were no responses in the other cohorts. Although patients and physicians were blinded to the sequencing and random assignment results, a higher pretreatment dropout rate was observed in the control arm (22%) compared with the experimental arm (6%; P = .038), suggesting that some patients may have had prior tumor mutation profiling performed that led to a lack of participation in the control arm.

CONCLUSION

Further investigation, better annotation of predictive biomarkers, and the development of more effective agents are necessary to inform treatment decisions in an era of precision cancer medicine. Increasing prevalence of tumor mutation profiling and preference for targeted therapy make it difficult to use a randomized phase II design to evaluate targeted therapy efficacy in an advanced disease setting.

Statistical Considerations for Trials in Adjuvant Treatment of Colorectal Cancer

The design of the best possible clinical trials of adjuvant interventions in colorectal cancer will entail the use of both time-tested and novel methods that allow efficient, reliable and patient-relevant therapeutic development. The ultimate goal of this endeavor is to safely and expeditiously bring to clinical practice novel interventions that impact patient lives. In this paper, we discuss statistical aspects and provide suggestions to optimize trial design, data collection, study implementation, and the use of predictive biomarkers and endpoints in phase 3 trials of systemic adjuvant therapy. We also discuss the issues of collaboration and patient centricity, expecting that several novel agents with activity in the (neo)adjuvant therapy of colon and rectal cancers will become available in the near future.

Molecular Profiling-Based Precision Medicine in Cancer: A Review of Current Evidence and Challenges

Matched therapy based on next-generation sequencing is now a part of routine care to guide the treatment of patients with advanced solid tumors. However, whether and to what extent patients can benefit from this strategy on a large scale remains uncertain. In the past decade, several clinical studies were performed in this field, among which only one was a randomized trial. We reviewed the literature on this topic and summarize the existing data about the efficacy of this treatment strategy. Currently, the evidence is promising but not solid. Multiple ongoing trials are also summarized. We also discuss the limitations of this treatment strategy and certain unsolved important problems, including how to select the sample and target level, how to interpret the results, and the problem of drug accessibility. All these issues should receive more attention in future clinical trial design and the application of target therapy in cancer treatment.

A Review of Perspectives on the Use of Randomization in Phase II Oncology Trials

Historically, phase II oncology trials assessed a treatment's efficacy by examining its tumor response rate in a single-arm trial. Then, approximately 25 years ago, certain statistical and pharmacological considerations ignited a debate around whether randomized designs should be used instead. Here, based on an extensive literature review, we review the arguments on either side of this debate. In particular, we describe the numerous factors that relate to the reliance of single-arm trials on historical control data and detail the trial scenarios in which there was general agreement on preferential utilization of single-arm or randomized design frameworks, such as the use of single-arm designs when investigating treatments for rare cancers. We then summarize the latest figures on phase II oncology trial design, contrasting current design choices against historical recommendations on best practice. Ultimately, we find several ways in which the design of recently completed phase II trials does not appear to align with said recommendations. For example, despite advice to the contrary, only 66.2% of the assessed trials that employed progression-free survival as a primary or coprimary outcome used a randomized comparative design. In addition, we identify that just 28.2% of the considered randomized comparative trials came to a positive conclusion as opposed to 72.7% of the single-arm trials. We conclude by describing a selection of important issues influencing contemporary design, framing this discourse in light of current trends in phase II, such as the increased use of biomarkers and recent interest in novel adaptive designs.

Neoadjuvant rectal score as individual-level surrogate for disease-free survival in rectal cancer in the CAO/ARO/AIO-04 randomized phase III trial

Background

Surrogate end points in rectal cancer after preoperative chemoradiation are lacking as their statistical validation poses major challenges, including confirmation based on large phase III trials. We examined the prognostic role and individual-level surrogacy of neoadjuvant rectal (NAR) score that incorporates weighted cT, ypT and ypN categories for disease-free survival (DFS) in 1191 patients with rectal carcinoma treated within the CAO/ARO/AIO-04 phase III trial.

Patients and methods

Cox regression models adjusted for treatment arm, resection status, and NAR score were used in multivariable analysis. The four Prentice criteria (PC1-4) were used to assess individual-level surrogacy of NAR for DFS.

Results

After a median follow-up of 50 months, the addition of oxaliplatin to fluorouracil-based chemoradiotherapy (CRT) significantly improved 3-year DFS [75.9% (95% confidence interval [CI] 72.30% to 79.50%) versus 71.3% (95% CI 67.60% to 74.90%); P = 0.034; PC 1) and resulted in a shift toward lower NAR groups (P = 0.034, PC 2) compared with fluorouracil-only CRT. The 3-year DFS was 91.7% (95% CI 88.2% to 95.2%), 81.8% (95% CI 78.4% to 85.1%), and 58.1% (95% CI 52.4% to 63.9%) for low, intermediate, and high NAR score, respectively (P < 0.001; PC 3). NAR score remained an independent prognostic factor for DFS [low versus high NAR: hazard ratio (HR) 4.670; 95% CI 3.106-7.020; P < 0.001; low versus intermediate NAR: HR 1.971; 95% CI 1.303-2.98; P = 0.001] in multivariable analysis. Notwithstanding the inherent methodological difficulty in interpretation of PC 4 to establish surrogacy, the treatment effect on DFS was captured by NAR, supporting satisfaction of individual-level PC 4.

Conclusion

Our study validates the prognostic role and individual-level surrogacy of NAR score for DFS within a large randomized phase III trial. NAR score could help oncologists to speed up response-adapted therapeutic decision, and further large phase III trial data sets should aim to confirm trial-level surrogacy.

Future Perspectives for Patient-Centric Pharmaceutical Drug Product Design with Regard to Solid Oral Dosage Forms

Purpose

Additional costs for healthcare provision are expected for cases where the level of care provided is not according to the patient’s needs and demands. To address these issues and reduce costs, fundamental changes need to be made on how healthcare provision is administered to patients, which raises the opportunity for the implementation of patient-centric systems.

Methods

This review addresses the importance of implementing a patient-centric approach in current healthcare provision and emphasizes the need to adjust current development and business models for a successful application of patient-centric care.

Results

To increase awareness and avoid confusion, the purpose of patient-centric pharmaceutical drug product design is reviewed in detail and future market opportunities for patient-centric drug products are discussed.

Conclusions

With regard to solid oral dosage forms, the subject of patient-centric pharmaceutical drug product design will focus more on the customization of existing technologies (e.g., dosage form size reduction) to address the needs of specific patient populations such as pediatrics, geriatrics, dysphagia patients, or the cognitively impaired.

Harnessing innate immunity in cancer therapy

New therapies that promote antitumour immunity have been recently developed. Most of these immunomodulatory approaches have focused on enhancing T-cell responses, either by targeting inhibitory pathways with immune checkpoint inhibitors, or by targeting activating pathways, as with chimeric antigen receptor T cells or bispecific antibodies. Although these therapies have led to unprecedented successes, only a minority of patients with cancer benefit from these treatments, highlighting the need to identify new cells and molecules that could be exploited in the next generation of immunotherapy. Given the crucial role of innate immune responses in immunity, harnessing these responses opens up new possibilities for long-lasting, multilayered tumour control.

Phase I trials as valid therapeutic options for patients with cancer

For many years, oncology phase I trials have been referred to as 'toxicity trials' and have been believed to have low clinical utility other than that of establishing the adverse event profile of novel therapeutic agents. The traditional distinction of clinical trials into three phases has been challenged in the past few years by the introduction of targeted therapies and immunotherapies into the routine management of patients with cancer. This transformation has especially affected early phase trials, leading to the current situation in which response rates are increasingly reported from phase I trials. In this Perspectives, we highlight key elements of phase I trials and discuss how each one of them contributes to a new paradigm whereby preliminary measurements of the clinical benefit from a novel treatment can be obtained in current phase I trials, which can therefore be considered to have a therapeutic intent.

Keeping phase III tuberculosis trials relevant: Adapting to a rapidly changing landscape

In a Collection Review, Patrick Phillips and colleagues discuss developments in clinical trial design for the evaluation of TB therapeutics.

Inability of positive phase II clinical trials of investigational treatments to subsequently predict positive phase III clinical trials in glioblastoma

Background

Glioblastoma is the most common primary malignant brain tumor in adults, but effective therapies are lacking. With the scarcity of positive phase III trials, which are increasing in cost, we examined the ability of positive phase II trials to predict statistically significant improvement in clinical outcomes of phase III trials.

Methods

A PubMed search was conducted to identify phase III clinical trials performed in the past 25 years for patients with newly diagnosed or recurrent glioblastoma. Trials were excluded if they did not examine an investigational chemotherapy or agent, if they were stopped early owing to toxicity, if they lacked prior phase II studies, or if a prior phase II study was negative.

Results

Seven phase III clinical trials in newly diagnosed glioblastoma and 4 phase III clinical trials in recurrent glioblastoma met the inclusion criteria. Only 1 (9%) phase III study documented an improvement in overall survival and changed the standard of care.

Conclusion

The high failure rate of phase III trials demonstrates the urgent need to increase the reliability of phase II trials of treatments for glioblastoma. Strategies such as the use of adaptive trial designs, Bayesian statistics, biomarkers, volumetric imaging, and mathematical modeling warrant testing. Additionally, it is critical to increase our expectations of phase II trials so that positive findings increase the probability that a phase III trial will be successful.

The future of myeloma precision medicine: integrating the compendium of known drug resistance mechanisms with emerging tumor profiling technologies

Multiple myeloma (MM) is a hematologic malignancy that is considered mostly incurable in large part due to the inability of standard of care therapies to overcome refractory disease and inevitable drug-resistant relapse. The post-genomic era has been a productive period of discovery where modern sequencing methods have been applied to large MM patient cohorts to modernize our current perception of myeloma pathobiology and establish an appreciation for the vast heterogeneity that exists between and within MM patients. Numerous pre-clinical studies conducted in the last two decades have unveiled a compendium of mechanisms by which malignant plasma cells can escape standard therapies, many of which have potentially quantifiable biomarkers. Exhaustive pre-clinical efforts have evaluated countless putative anti-MM therapeutic agents and many of these have begun to enter clinical trial evaluation. While the palette of available anti-MM therapies is continuing to expand it is also clear that malignant plasma cells still have mechanistic avenues by which they can evade even the most promising new therapies. It is therefore becoming increasingly clear that there is an outstanding need to develop and employ precision medicine strategies in MM management that harness emerging tumor profiling technologies to identify biomarkers that predict efficacy or resistance within an individual's sub-clonally heterogeneous tumor. In this review we present an updated overview of broad classes of therapeutic resistance mechanisms and describe selected examples of putative biomarkers. We also outline several emerging tumor profiling technologies that have the potential to accurately quantify biomarkers for therapeutic sensitivity and resistance at genomic, transcriptomic and proteomic levels. Finally, we comment on the future of implementation for precision medicine strategies in MM and the clear need for a paradigm shift in clinical trial design and disease management.

Economic Evaluations of Next-Generation Precision Oncology: A Critical Review

Purpose

Precision oncology has the potential to improve patient health and reduce treatment costs. Yet the up-front cost of genomic testing with next-generation sequencing (NGS) technologies can be prohibitive. Our study is a structured review of economic evaluations of precision oncology informed by NGS. The aim is to characterize the availability and scope of economic evidence.

Materials and Methods

We searched Medline (PubMed), Embase (Ovid), and Web of Science databases for English-language full-text peer-reviewed articles published between 2000 and 2016. We focused our search on articles that estimated the benefit of precision oncology in relation to its costs. We excluded studies that did not undertake full economic evaluations or did not focus on NGS technologies. We reviewed all included studies and summarized key methodological and empirical study characteristics.

Results

Fifty-five economic evaluations met our inclusion criteria. The number of published studies increased steadily, from three studies between 2005 and 2007 to 26 between 2014 and 2016. Most studies evaluated multiplex panels (86%). We found testing was frequently used to predict prognosis (67%), to diagnose patients (24%), or to identify targeted therapeutic options (7%). Methods and cost effectiveness differed according to NGS technology, test strategy, and cancer type. Deterministic and probabilistic analyses were typically used to characterize parameter and decision uncertainty (91% and 75%).

Conclusion

Although the availability of economic evidence examining precision oncology increased over time, methods used often did not align with current guidelines. Future evaluations should undertake extensive sensitivity analysis to address all sources of uncertainty associated with rapidly changing NGS technologies. Furthermore, additional research is needed evaluating the cost effectiveness of more comprehensive next-generation technologies before implementing these on a wider scale.

Randomized dose-escalation designs for drug combination cancer trials with immunotherapy

This work considers Phase I cancer dual-agent dose-escalation clinical trials in which one of the compounds is an immunotherapy. The distinguishing feature of trials considered is that the dose of one agent, referred to as a standard of care, is fixed and another agent is dose-escalated. Conventionally, the goal of a Phase I trial is to find the maximum tolerated combination (MTC). However, in trials involving an immunotherapy, it is also essential to test whether a difference in toxicities associated with the MTC and the standard of care alone is present. This information can give useful insights about the interaction of the compounds and can provide a quantification of the additional toxicity burden and therapeutic index. We show that both, testing for difference between toxicity risks and selecting MTC can be achieved using a Bayesian model-based dose-escalation design with two modifications. Firstly, the standard of care administrated alone is included in the trial as a control arm and each patient is randomized between the control arm and one of the combinations selected by a model-based design. Secondly, a flexible model is used to allow for toxicities at the MTC and the control arm to be modeled directly. We compare the performance of two-parameter and four-parameter logistic models with and without randomization to a current standard of such trials: a one-parameter model. It is found that at the cost of a small reduction in the proportion of correct selections in some scenarios, randomization provides a significant improvement in the ability to test for a difference in the toxicity risks. It also allows a better fitting of the combination-toxicity curve that leads to more reliable recommendations of the combination(s) to be studied in subsequent phases.

Path toward Precision Oncology: Review of Targeted Therapy Studies and Tools to Aid in Defining "Actionability" of a Molecular Lesion and Patient Management Support

Precision medicine trials and targeted therapies have shifted to the forefront of oncology. Although targeted therapies have shown initial promise, implementation across the broad landscape of oncology has many challenges. These limitations include an incomplete understanding of the functional significance of variant alleles as well as the need for clinical research and practice models that are more patient-centered and account for the complexity of individual patient tumors. Furthermore, successful implementation of targeted therapies will also be predicated on efforts to standardize the framework for patient management support. Here, we review current implementations of targeted therapies in precision oncology and discuss how "actionability" is defined for molecular targets in cancer therapeutics. We also comment on the growing need for bioinformatics tools and data platforms to complement advances in precision oncology. Finally, we discuss current frameworks for integrating precision oncology into patient management and propose an integrated model that combines features of molecular tumor boards and decision support systems. Mol Cancer Ther; 16(12); 2645-55. ©2017 AACRSee related article by Pilié et al., p. 2641.

Re-inventing the randomized controlled trial in medical oncology: The registry-based trial

Substantial progress has recently been made in optimizing the management of cancer patients, resulting in major gains in survival and quality of life. Much of this progress has resulted from the serial testing of promising treatment strategies, typically using prospective randomized controlled trials to compare outcomes achieved with the new approach versus the current standard(s) of care. However, there is an ever-expanding list of important questions that are difficult to investigate, particularly with respect to determining the optimal sequencing and combination of proven active agents. With the rapidly growing list of clinical, pathologic and molecular characteristics that promise to predict treatment benefit and/or risk for defined patient subsets, many new questions regarding how best to personalize our approach to treatment selection are emerging. These questions can be investigated in the context of registry-based randomized clinical trials. Recently, the potential of registry-based randomized clinical trials was demonstrated in cardiology, highlighting the ability to rapidly recruit large numbers of patients to a trial addressing an important clinical question, with minimal cost and high external validity. In this review, we discuss the challenges and limitations of conventional clinical trials in multidisciplinary cancer care, describe the potential advantages of registry-based randomized trials, and highlight several registry-based oncology studies that are already underway to demonstrate the feasibility of this approach.

Genomics and emerging biomarkers for immunotherapy of colorectal cancer

Colorectal cancer (CRC) is a common and lethal disease with a high therapeutic need. For most patients with metastatic CRC, chemotherapy is the only viable option. Currently, immunotherapy is restricted to the particular genetic subgroup of mismatch-repair deficient (MMRd)/microsatellite instable (MSI) CRC. Anti-PD1 therapy was recently FDA-approved as a second-line treatment in this subgroup. However, in a metastatic setting, these MMRd/MSI tumors are vastly outnumbered by mismatch-repair proficient (MMRp)/microsatellite stable (MSS) tumors. These MMRp/MSS tumors do not meaningfully respond to any traditional immunotherapy approach including checkpoint blockade, adoptive cell transfer and vaccination. This resistance to immunotherapy is due to a complex tumor microenvironment that counteracts antitumor immunity through a combination of poorly antigenic tumor cells and an immunosuppressive tumor microenvironment. To find ways of overcoming immunotherapy resistance in the majority of CRC patients, it is necessary to analyze the immunological makeup in an in-depth and personalized way and in the context of their tumor genetic makeup. Flexible, biomarker-guided early-phase immunotherapy trials are needed to optimize this workflow. In this review, we detail key mechanisms for immune evasion and emerging immune biomarkers for personalized immunotherapy in CRC. Also, we present a template for biomarker-guided clinical trials that are needed to move new immunotherapy approaches closer to clinical application.

Accelerating Therapeutic Development through Innovative Trial Design in Colorectal Cancer

OPINION STATEMENT

Current trial design is challenged by the advancement of technologies that have enabled deeper understanding of the molecular drivers of colorectal cancer (CRC). The speed of trial testing and the ability to test larger volumes of promising novel agents in the face of smaller populations identified by molecular profiling are challenges posed to clinical studies. Master protocols that utilize umbrella designs are equipped to deal with potential biomarker and matched treatments simultaneously. Although complex in nature, they increase trial efficiency by utilizing shared screening platforms, test multiple treatments together, and simplify regulatory submission and reporting under a common protocol. Emerging technologies such as circulating tumor DNA (ctDNA) may help speed up adjuvant trials. These studies have been traditionally slow to complete due to low event rates and the high numbers needed to recruit. ctDNA used as a surrogate for minimal residual disease (MRD) and as an early marker of relapse may help counter some of these factors that deter innovation in this setting. Finally, in the era of precision medicine, surgery should not be forgotten as the only potentially curative option to date in metastatic disease. Five-year overall survival following resection of liver metastasis exceeds what can be achieved with chemotherapy alone in selected cases. Surgical advances have lowered morbidity and allow for greater resection volumes and repeated interventions. Although historically challenging, a well-designed randomized surgical intervention trial would greatly facilitate moving single-institution guidelines reported by case series into wider clinical practice.

Evidence-Based Precision Oncology with the Cancer Targetome

A core tenet of precision oncology is the rational choice of drugs to interact with patient-specific biological targets of interest, but it is currently difficult for researchers to obtain consistent and well-supported target information for pharmaceutical drugs. We review current drug-target interaction resources and critically assess how supporting evidence is handled. We introduce the concept of a unified Cancer Targetome to aggregate drug-target interactions in an evidence-based framework. We discuss current unmet needs and the implications for evidence-based clinical omics. The focus of this review is precision oncology but the discussion is highly relevant to targeted therapies in any area.

Personalised Interventions-A Precision Approach for the Next Generation of Dietary Intervention Studies

Diet is a key modifiable risk factor for non-communicable diseases. However, we currently are not benefitting from the full potential of its protective effects. This is due to a number of reasons, including high individual variability in response to certain diets. It is now well acknowledged that in order to gain the full benefit of dietary regimes it is essential to take into account individual responses. With this in mind, the present review examines the concept of precision nutrition and the performance of n-of-1 studies, and discusses the development of certain approaches that will be critical for development of the concepts.

Early phase clinical trials of anticancer agents in children and adolescents - an ITCC perspective

In the past decade, the landscape of drug development in oncology has evolved dramatically; however, this paradigm shift remains to be adopted in early phase clinical trial designs for studies of molecularly targeted agents and immunotherapeutic agents in paediatric malignancies. In drug development, prioritization of drugs on the basis of knowledge of tumour biology, molecular 'drivers' of disease and a drug's mechanism of action, and therapeutic unmet needs are key elements; these aspects are relevant to early phase paediatric trials, in which molecular profiling is strongly encouraged. Herein, we describe the strategy of the Innovative Therapies for Children with Cancer (ITCC) Consortium, which advocates for the adoption of trial designs that enable uninterrupted patient recruitment, the extrapolation from studies in adults when possible, and the inclusion of expansion cohorts. If a drug has neither serious dose-related toxicities nor a narrow therapeutic index, then studies should generally be started at the adult recommended phase II dose corrected for body surface area, and act as dose-confirmation studies. The use of adaptive trial designs will enable drugs with promising activity to progress rapidly to randomized studies and, therefore, will substantially accelerate drug development for children and adolescents with cancer.

Evidence for Treatment-by-Biomarker interaction for FDA-approved Oncology Drugs with Required Pharmacogenomic Biomarker Testing

For oncology drugs that were approved by the US Food and Drug Administration (FDA) and required pharmacogenomic biomarker testing, we describe 1) the use of enrichment (biomarker-positive patients) and a randomized controlled design by pre-approval trials and 2) the treatment-by-biomarker interaction. From the 137 drugs included in the FDA table, we selected the 22 oncology drugs with required genetic testing in their labels. These drugs corresponded to 35 approvals supported by 80 clinical studies included in the FDA medical officer reviews of efficacy. For two thirds of approvals (24/35, 69%), all clinical studies were restricted to biomarker-positive patients (enriched). Among the 11 remaining approvals with at least one non-enriched trial, for five approvals, the non-enriched studies were non-randomized. The treatment-by-biomarker interaction was statistically significant for three approvals and missing for two. Among the six approvals with a non-enriched randomized controlled trial, three featured a statistically significant treatment-by-biomarker interaction (p < 0.10), for an enhanced treatment effect in the biomarker-positive subgroup. For two thirds of FDA approvals of anticancer agents, the requirement for predictive biomarker testing was based on clinical development restricted to biomarker-positive patients. We found only few cases with clinical evidence that biomarker-negative patients would not benefit from treatment.

Precision Medicine in Myeloma: Challenges in Defining an Actionable Approach

Recently, large sequencing studies have provided insights into the mutational landscape of multiple myeloma (MM), identifying actionable mutations and giving a precious opportunity for exploring new targeted therapies. The main goal of precision medicine, matching patients with the right drug, seems to be closer than ever. However, no targeted therapies in MM are approved yet. Several clinical trials testing targeted drugs and enrolling patients with MM are currently ongoing and will provide predictive biomarkers that might support clinical decision making. In this review, we evaluate the evidence supporting the implementation of precision medicine in MM and we discuss the challenges that should be dealt with in this imminent and promising new era.

Spotlight on landmark oncology trials: the latest evidence and novel trial designs

The era of precision oncology is marked with prominent successes in the therapy of advanced soft tissue sarcomas, breast cancer, ovarian cancer and haematological neoplasms, among others. Moreover, recent trials of immune checkpoint inhibitors in melanoma, non-small cell lung carcinoma, and head and neck cancers have significantly influenced the therapeutic landscape by providing promising evidence for immunotherapy efficacy in the adjuvant setting in high-risk locoregional disease. To speed up the introduction of targeted therapy for cancer patients, novel phase II trials are being designed, and may likely form the basis for the 'landmark trials' of the future. A special article collection in BMC Medicine, "Spotlight on landmark oncology trials", features articles from invited experts on recent clinical practice-changing trials.

Towards personalized tumor markers

The cancer biomarker discovery pipeline is progressing slowly. The difficulties of finding novel and effective biomarkers for diagnosis and management of cancer patients are well-known. We speculate that it is unlikely to discover new serological biomarkers characterized by high sensitivity and specificity. This projection is supported by recent findings that cancers are genetically highly heterogeneous. Here, we propose a new way of improving the landscape of cancer biomarker research. There are currently hundreds, if not thousands, of described biomarkers which perform at high specificity (> 90%), but at relatively low sensitivity (< 30%). We call these “rare tumor markers.” Borrowing from the principles of precision medicine, we advocate that among these low sensitivity markers, some may be useful to specific patients. We suggest screening new patients for hundreds to thousands of cancer biomarkers to identify a few that are informative, and then use them clinically. This is similar to what we currently do with genomics to identify personalized therapies. We further suggest that this approach may explain as to why some biomarkers are elevated in only a small group of patients. It is likely that these differences in expression are linked to specific genomic alterations, which could then be found with genomic sequencing.

Evaluating tumor response with FDG PET: updates on PERCIST, comparison with EORTC criteria and clues to future developments

Eighteen years ago, the EORTC PET criteria standardized for the first time response assessment by FDG PET. Response assessment by FDG PET has been further developed and refined by PERCIST (PET response criteria in solid tumors). This review describes the data underlying these two systems for assessing tumor response on FDG PET/CT. It also summarizes recent clinical studies that have compared EORTC criteria and PERCIST with each other as well as with the anatomically based "response criteria in solid tumors" (RECIST). These studies have shown that response assessment by EORTC criteria and PERCIST leads to very similar response classifications. In contrast, there are significant differences between response assessment by PERCIST and RECIST. Preliminary data also suggest that response assessment by PERCIST is better correlated with patient outcome and may be a better predictor for the effectiveness of new anti-cancer therapies than RECIST. If correct, this could have a significant impact on oncologic drug development. However, confirmation of the better predictive value of response assessment by PERCIST by data from randomized trials is still lacking.