New targets and challenges in the molecular therapeutics of cancer

The past 20 years have seen an explosion of information on the molecular changes that lead to cancer. The pathways that have been uncovered include many targets for the development of novel therapeutics. Several such drugs have been approved for clinical use and many additional drugs and targets are now being evaluated in preclinical studies. These new drugs may exhibit impressive therapeutic activity, but this is often restricted to a subpopulation of cancers with a particular molecular change. Moreover, toxicity or even antagonism may result from off-target effects of the drugs. Accordingly, it will be critical to stratify patients for treatment based on the propensity of their tumours to respond. In addition, defining the appropriate dose of targeted agents to administer is challenging; early clinical trial designs must include assays to define the effective biological dose, in addition to more traditional end-points such as the maximum tolerable dose. These and many other challenges exist in the preclinical and clinical development of these drugs.     

Optimal Two-Stage Design for the Phase II Cancer Clinical Trials With Responses and Early Progression as Co-primary Endpoints

In phase II cancer clinical trials of newly developed cytostatic or molecularly targeted agents, it is proposed to use both response and early progression rate as co-primary endpoints of the trials. An agent is considered promising if either its response rate is high or its early progression rate is low. In this article, we present some strategies for the search of optimal two-stage designs, which minimizes the expected total sample size under null hypothesis and has its Type I and II errors bounded above by prespecified values. Examples are given for several scenarios appearing in clinical practice.     

Development of Target-Based Antineoplastic Agents

The elucidation of multiple potential targets in cancer cells andthe development of multiple target-based antineoplastic agentsprovide unique challenges in clinical trial design. Many of theseagents are predicted to have cytostatic as opposed to cytotoxiceffects and thus the traditional surrogate endpoint of radiologictumor shrinkage may be inadequate. The ethical and safety issuesof obtaining multiple tumor biopsies further complicate theassessment of appropriate target inhibition in patients. Wediscuss specific issues that need to be addressed duringpreclinical, phase I, II, and III testing of these agents. Wepropose clinical trial designs, including a randomizeddiscontinuation design during phase II evaluation, that may beparticularly useful for cytostatic antineoplastic agents.     

Adaptive Penalized D-Optimal Designs for Dose Finding Based on Continuous Efficacy and Toxicity

When a new drug is under development, a conventional dose-finding study involves learning about the dose–response curve in order to bring forward right doses of the drug to late-stage development. We propose an adaptive procedure for dose-finding in clinical trials in the presence of both efficacy and toxicity endpoints. We use the principles of optimal experimental designs for bivariate continuous endpoints.

However, instead of using the traditional D-optimal design, which favors collective ethics but neglects the individual ethics, we consider the penalized D-optimal design that achieves an appropriate balance between the efficient treatment of patients in the trial (by penalizing allocation of patients to ineffective or toxic doses) and the precise estimation of the model parameters to be used in the identification of the target dose. This is compared with the traditional fixed allocation design in terms of allocation of subjects and precision of the identified dose–response curve and selection of the target dose.     

Developing new agents for the treatment of childhood cancer

The development of new drugs for the treatment of childhood cancer presents novel challenges, and pediatric clinical trials of a new agent are often initiated many years after testing in adults. It is estimated that there are over 400 new entities being developed as cancer treatments, although few of these have been developed specifically for the treatment of childhood malignancies. This raises the question of how agents can be prioritized for pediatric clinical testing. In this review, the molecular characteristics of childhood cancers that may be valuable in steering choices for rational or molecularly targeted treatments are described, and the Pediatric Preclinical Testing Program, a National Cancer Institute initiative to identify agents that should be prioritized for clinical evaluation against childhood cancer, is presented.     

Statistical challenges in a regulatory review of cardiovascular and CNS clinical trials

Abstract

There are several challenging statistical problems identified in the regulatory review of large cardiovascular (CV) clinical outcome trials and central nervous system (CNS) trials. The problems can be common or distinct due to disease characteristics and the differences in trial design elements such as endpoints, trial duration, and trial size. In schizophrenia trials, heavy missing data is a big problem. In Alzheimer trials, the endpoints for assessing symptoms and the endpoints for assessing disease progression are essentially the same; it is difficult to construct a good trial design to evaluate a test drug for its ability to slow the disease progression. In CV trials, reliance on a composite endpoint with low event rate makes the trial size so large that it is infeasible to study multiple doses necessary to find the right dose for study patients. These are just a few typical problems. In the past decade, adaptive designs were increasingly used in these disease areas and some challenges occur with respect to that use. Based on our review experiences, group sequential designs (GSDs) have borne many successful stories in CV trials and are also increasingly used for developing treatments targeting CNS diseases. There is also a growing trend of using more advanced unblinded adaptive designs for producing efficacy evidence. Many statistical challenges with these kinds of adaptive designs have been identified through our experiences with the review of regulatory applications and are shared in this article.     

Advances in the approach to novel drug clinical development for breast cancer

Introduction: In the post-genomic era clinical development of new agents to treat breast cancer (BC) can be a real challenge. Different from chemotherapy agents, with a broad but not specific spectrum of activity, novel drugs are being developed as ‘targeted’ agents, potentially benefiting a subgroup of patients. In BC, different clinically identifiable subtypes are now separately addressed in specific clinical trials.

Areas covered: In this review, the authors discuss the clinical development of targeted drugs that have become part of the current treatment of BC. They also highlight the challenges that in other cases determined the failure of promising compounds. Furthermore, the article reports on how combinations of targeted agents have emerged as valid strategies to overcome acquired resistance. It also provides discussion of how ‘old’ therapies can be retargeted to certain patient populations or ‘reinvented’ as safer and more effective with the creation of drug conjugates. They also discuss how novel clinical trial designs are emerging to accelerate the successful matching of targeted drugs to the right patient population.

Expert opinion: It is important not to forget that the development of BC therapeutics is a ‘moving target’, as its biology evolves in time under the pressure of ongoing treatments. There are currently a finite number of resources available for the development of new therapeutics, which means that resources need to be carefully allocated. There is also a need to prioritize clinical trials that can reduce the number of patients who are candidates for expensive treatments.     

Some Challenges With Statistical Inference in Adaptive Designs

Adaptive designs have generated a great deal of attention to clinical trial communities. The literature contains many statistical methods to deal with added statistical uncertainties concerning the adaptations. Increasingly encountered in regulatory applications are adaptive statistical information designs that allow modification of sample size or related statistical information and adaptive selection designs that allow selection of doses or patient populations during the course of a clinical trial. For adaptive statistical information designs, a few statistical testing methods are mathematically equivalent, as a number of articles have stipulated, but arguably there are large differences in their practical ramifications. We pinpoint some undesirable features of these methods in this work. For adaptive selection designs, the selection based on biomarker data for testing the correlated clinical endpoints may increase statistical uncertainty in terms of type I error probability, and most importantly the increased statistical uncertainty may be impossible to assess.     

Predicting the outcome of phase III trials using phase II data: a case study of clinical trial simulation in late stage drug development

Abstract: Maximizing the likelihood of success in Phase III is the ultimate goal of the use of modelling and simulation in the drug development process. The success in Phase III depends primarily on two questions: 1) Is the drug regimen actually efficacious and safe in the targeted patient population?, and 2) Will the planned Phase III clinical trial(s) be successful in demonstrating this? Traditionally, the first question is addressed in a qualitative, overall interpretation of available study results. Integrating this information into a formal statistical model of the action of the drug, allows running simulations to investigate the impact of uncertainties and imprecision in this knowledge. The second question is related to having an adequately designed clinical trial. Clinical trial simulation, using a drug action model, supplemented with appropriate models for disease progression and trial execution, allows assessing the impact of typical design features such as doses, sample size, in‐/exclusion criteria, drop‐out and trial duration on the trial outcome and thus optimising trial design. In this contribution, the use of modelling and simulation in the Phase II to Phase III transition is illustrated using real data of a drug for symptom relief in a chronic condition. A dose‐response model of the clinical response was developed using data from Phase II. Simulations were performed to 1) generate the range of possible outcomes of ongoing Phase III trials and compare these to the blinded data being generated from these trials; 2) assess the robustness of the ongoing Phase III trials with respect to uncertainty of the true dose‐response, patient variability in baseline severity and drug‐response, and 3) assess the likelihood of achieving a clinically relevant response with a dose lower than those included in the trials.     

Strategies for designing clinical trials for oligonucleotide therapeutics

Recent Phase III clinical trials for oligonucleotide therapeutics have yielded disappointing results. There is growing evidence that trial designs that consider the specific mode of action of these compounds are of crucial importance for their clinical testing. Early trials for oligonucleotide therapeutics should consider additional endpoints for the definition of a biologically active dose rather than focusing on the traditional concept of maximal tolerated dose. In later phases, alternative clinical endpoints and enriching sensitive study populations through innovative trial designs could improve the efficiency of clinical trials for oligonucleotide therapeutics.     

Feasibility of Exposure-Response Analyses for Clinical Dose-Ranging Studies of Drug Combinations

The exposure-response relationship of combinatory drug effects can be quantitatively described using pharmacodynamic interaction models, which can be used for the selection of optimal dose combinations. The aim of this simulation study was to evaluate the reliability of parameter estimates and the probability for accurate dose identification for various underlying exposure-response profiles, under a number of different phase II designs. An efficacy variable driven by the combined exposure of two theoretical compounds was simulated and model parameters were estimated using two different models, one estimating all parameters and one assuming that adequate previous knowledge for one drug is readily available. Estimation of all pharmacodynamic parameters under a realistic, in terms of sample size and study design, phase II trial, proved to be challenging. Inaccurate estimates were found in all exposure-response scenarios, except for situations where no pharmacodynamic interaction was present, with the drug potency and interaction parameters being the hardest to estimate. When previous knowledge of the exposure-response relationship of one of the monocomponents is available, such information should be utilized, as it enabled relevant improvements in parameter estimation and in correct dose identification. No general trends for classification of the performance of the tested study designs across different scenarios could be identified. This study shows that pharmacodynamic interactions models can be used for the exposure-response analysis of clinical endpoints especially when accompanied by appropriate dose selection in regard to the expected drug potencies and appropriate trial size and if information regarding the exposure-response profile of one monocomponent is available.     

Targeted ultrasound imaging of cancer: an emerging technology on its way to clinics

Ultrasound is one of the workhorses in clinical cancer diagnosis. In particular, it is routinely used to characterize lesions in liver, urogenital tract, head and neck and soft tissues. During the last years image quality steadily improved, which, among others, can be attributed to the development of harmonic image analysis. Microbubbles were introduced as intravascular contrast agents and can be detected with superb sensitivity and specificity using contrast specific imaging modes. By aid of these unspecific contrast agents tissues can be characterised regarding their vascularity. Antibodies, peptides and other targeting moieties were bound to microbubbles to target sites of angiogenesis and inflammation intending to get more disease-specific information. Indeed, many preclinical studies proved the high potential of targeted ultrasound imaging to better characterize tumors and to more sensitively monitor therapy response. Recently, first targeted microbubbles had been developed that meet the pharmacological demands of a clinical contrast agent. This review articles gives an overview on the history and current status of targeted ultrasound imaging of cancer. Different imaging concepts and contrast agent designs are introduced ranging from the use of experimental nanodroplets to agents undergoing clinical evaluation. Although it is clear that targeted ultrasound imaging works reliably, its broad acceptance is hindered by the user dependency of ultrasound imaging in general. Automated 3D-scanning techniques-like being used for breast diagnosis - and novel 3D transducers will help to make this fascinating method clinical reality.     

Multiple Testing in Group Sequential Trials Using Graphical Approaches

In 1997, Robert T. O’Neill introduced the framework of structuring the experimental questions to best reflect the clinical study’s objectives. This task comprises the identification of the study’s primary, secondary, and exploratory objectives and the requirements as to when the corresponding statistical tests are considered meaningful. A topic that has been considered much less in the literature until very recently is the application of group sequential trial designs to multiple endpoints. In 2007, Hung, Wang, and O’Neill showed that borrowing testing strategies naively from trial designs without interim analyses may not maintain the familywise Type I error rate at level α. The authors gave examples in the context of testing two hierarchically ordered endpoints in two-armed group sequential trials with one interim analysis. We consider the general situation of testing multiple hypotheses repeatedly in time using recently developed graphical approaches. We focus on closed testing procedures using weighted group sequential Bonferroni tests for the intersection hypotheses. Under mild monotonicity conditions on the error spending functions, this allows the use of sequentially rejective graphical procedures in group sequential trials. The methodology is illustrated with a numerical example for a three-armed trial comparing two doses against control for two hierarchically ordered endpoints.     

Promise and Progress for Functional and Molecular Imaging of Response to Targeted Therapies

Biomarkers to predict or monitor therapy response are becoming essential components of drug developer's armamentaria. Molecular and functional imaging has particular promise as a biomarker for anticancer therapies because it is non-invasive, can be used longitudinally and provides information on the whole patient or tumor. Despite this promise, molecular or functional imaging endpoints are not routinely incorporated into clinical trial design. As the costs of clinical trials and drug development become prohibitively more expensive, the need for improved biomarkers has become imperative and thus, the relatively high cost of imaging is justified. Imaging endpoints, such as Diffusion-Weighted MRI, DCE-MRI and FDG-PET have the potential to make drug development more efficient at all phases, from discovery screening with in vivo pharmacodynamics in animal models through the phase III enrichment of the patient population for potential responders. This review focuses on the progress of imaging responses to new classes of anti-cancer therapies targeted against PI3 kinase/AKT, HIF-1alpha and VEGF. The ultimate promise of molecular and functional imaging is to theragnostically predict response prior to commencement of targeted therapy.     

Emerging drugs in multiple myeloma

The treatment of multiple myeloma has seen significant changes from the time of the initial use of cytotoxic agents such as melphalan, to the introduction of high-dose chemotherapy and stem cell transplantation, and most recently the era of novel targeted agents. These new drugs have rapidly become the mainstay of therapy of this disease and transformed the treatment paradigm, leading to improvements in survival and quality of life. Existing therapeutic options include agents such as thalidomide, bortezomib and lenalidomide, either used alone or in combination with standard agents, including glucocorticoids, and in conjunction with high-dose chemotherapy supported with stem cell transplantation. Several other targeted agents have demonstrated exciting preclinical activity, and are presently being tested in early Phase I and II clinical trials. This review summarizes the role of novel therapeutic agents in multiple myeloma, and the promising effect of multiple new agents in development.     

Emerging drugs in multiple myeloma

The treatment of multiple myeloma has seen significant changes from the time of the initial use of cytotoxic agents such as melphalan, to the introduction of high-dose chemotherapy and stem cell transplantation, and most recently the era of novel targeted agents. These new drugs have rapidly become the mainstay of therapy of this disease and transformed the treatment paradigm, leading to improvements in survival and quality of life. Existing therapeutic options include agents such as thalidomide, bortezomib and lenalidomide, either used alone or in combination with standard agents, including glucocorticoids, and in conjunction with high-dose chemotherapy supported with stem cell transplantation. Several other targeted agents have demonstrated exciting preclinical activity, and are presently being tested in early Phase I and II clinical trials. This review summarizes the role of novel therapeutic agents in multiple myeloma, and the promising effect of multiple new agents in development.     

The pursuit of optimal outcomes in cancer therapy in a new age of rationally designed target-based anticancer agents

There have been extraordinary advances in anticancer therapy over the last few decades, particularly for patients with relatively uncommon malignancies, largely because of the advent of nonspecific cytotoxic chemotherapeutics. Although these agents have also brought improved outcomes for patients with many of the more common solid cancers, it is clear that the point of 'diminishing return' has been reached. The recent development of a plethora of rationally designed target-based anticancer agents has opened up new opportunities and extraordinary therapeutic challenges. Since these agents appear primarily to target malignant cells, they can be expected to be less toxic at clinically effective doses than the cytotoxic agents. Among the various types of rationally designed target-based agents are those that target strategic facets of cell growth signal transduction, angiogenesis, metastasis and cell cycle regulation. While the primary therapeutic benefit of these agents is expected to be decreased tumour growth, evidence suggests that objective tumour responses may also be achieved. However, because of their potentially cytostatic properties, the clinical efficacy of such biologically based agents may not be readily demonstrable with traditional phase I and II study methodologies. Additionally, their dose-toxicity relationships are likely to be less steep than those of the nonspecific cytotoxic agents, thereby rendering such concepts as the maximum tolerated dose less meaningful than alternatives such as the optimal biological dose or the biologically effective dose. Those end-points generally considered, both from a regulatory and clinical viewpoint, to be of secondary importance in trials of cytotoxic agents, such as time to disease progression, disease-related symptoms and quality of life, may evolve into primary end-points. Present findings from preclinical studies suggest that the development, evaluation and general clinical use of rationally designed target-based anticancer agents will require a radical departure from the traditional paradigms if the full potential of these new therapies is to be exploited.     

Selenium and inhibition of disease progression in men diagnosed with prostate carcinoma: study design and baseline characteristics of the 'Watchful Waiting' Study

Impediment of the promotion and progression stages of carcinogenesis of the prostate could have a profound impact on treatment choice and prognosis for prostate cancer. Efficacious chemopreventive agents that elicit their activity by slowing the processes of progression could make watchful waiting a viable alternative for a large population of men or could delay the necessity for surgery, radiation or other more invasive treatment modalities associated with frequent side effects. Reports from the Nutritional Prevention of Cancer (NPC) study reported that dietary supplementation with selenium significantly reduced the risk of developing prostate cancer. These data led to initiation of the Watchful Waiting Study, a phase II, multi-center, randomized, double-blind, placebo-controlled clinical intervention study testing the effects of two doses of selenized yeast on progression of prostate cancer. Participants are men with biopsy-proven prostate cancer who have elected to forgo therapy and be closely followed by 'watchful waiting' that includes quarterly prostate-specific antigen (PSA) screening. Subjects are randomized to receive 200 or 800 microg of selenized yeast or matched placebo daily. Endpoints include time to disease progression and PSA velocity. Secondary endpoints include time to initiation of therapy as well as biochemical markers of disease progression including chromagranin A and alkaline phosphatase. Immunohistochemical analyses for indicators of apoptosis, proliferation and differentiation will be performed on baseline and subsequent prostate biopsy specimens. This report summarizes the primary objectives, research methods and the randomized subjects in this important clinical trial.     

Penalty-based approaches to evaluating multiplicity adjustments in clinical trials: Advanced multiplicity problems

ABSTRACT

Given the importance of addressing multiplicity issues in confirmatory clinical trials, several recent publications focused on the general goal of identifying most appropriate methods for multiplicity adjustment in each individual setting. This goal can be accomplished using the Clinical Scenario Evaluation approach. This approach encourages trial sponsors to perform comprehensive assessments of applicable analysis strategies such as multiplicity adjustments under all plausible sets of statistical assumptions using relevant evaluation criteria. This two-part paper applies a novel class of criteria, known as criteria based on multiplicity penalties, to the problem of evaluating the performance of several candidate multiplicity adjustments. The ultimate goal of this evaluation is to identify efficient and robust adjustments for each individual trial and optimally select parameters of these adjustments. Part II focuses on advanced settings with several sources of multiplicity, for example, clinical trials with several endpoints evaluated at two or more doses of an experimental treatment. A case study is given to illustrate a penalty-based approach to evaluating candidate multiple testing procedures in advanced multiplicity problems.