Current challenges for the early clinical development of anticancer drugs in the era of molecularly targeted agents

A generalized Bayesian optimal interval design for dose optimization in immunotherapy

For novel immuno-oncology therapies, the primary purpose of a dose-finding trial is to identify an optimal dose (OD), defined as the tolerable dose having adequate efficacy and immune response under the unpredictable dose-outcome (toxicity, efficacy, and immune response) relationships. In addition, the multiple low or moderate-grade toxicities rather than dose-limiting toxicities (DLTs) and multiple levels of efficacy should be evaluated differently in dose-finding to determine true OD for developing novel immuno-oncology therapies. We proposed a generalized Bayesian optimal interval design for immunotherapy, simultaneously considering efficacy and toxicity grades and immune response outcomes. The proposed design, named gBOIN-ETI design, is model-assisted and easy to implement to develop immunotherapy efficiently. The operating characteristics of the gBOIN-ETI are compared with other dose-finding trial designs in oncology by simulation across various realistic settings. Our simulations show that the gBOIN-ETI design could outperform the other available approaches in terms of both the percentage of correct OD selection and the average number of patients allocated to the OD across various realistic trial settings.

Early clinical trial unit tumor board: a real-world experience in a national cancer network

PURPOSE

Early clinical trials are the first step into clinical therapies for new drugs. Within the six Bavarian university-based hospitals (Augsburg, Erlangen, Regensburg, Munich (LMU and TU), Würzburg) we have enrolled a virtual network platform for patient discussion.

METHODS

The virtual Early Clinical Trial Unit Tumor Board (ECTU Tumor Board) is a secured web-based meeting to evaluate early clinical trial options for patients, where representatives from local ECTUs participate. We retrospectively analyzed patient cases discussed between November 2021 and November 2022.

RESULTS

From November 2021 to November 2022, a total of 43 patients were discussed in the ECTU Tumor Board. Median age at diagnosis was 44.6 years (range 10-76 years). The median number of previous lines of therapies was 3.7 (range 1-9 therapies) including systemic treatment, surgery, and radiation therapy. A total of 27 different tumor entities were presented and 83.7% (36/43) patients received at least one trial recommendation. In total, 21 different active or shortly recruiting clinical trials were recommended: ten antibody trials, four BiTE (bispecific T cell engager) trials, six CAR (chimeric antigen receptor) T-cell trials, and one chemotherapy trial. Only six trials (28.6%) were recommended on the basis of the previously performed comprehensive genetic profiling (CGP).

CONCLUSION

The ECTU Tumor Board is a feasible and successful network, highlighting the force of virtual patient discussions for improving patient care as well as trial recruitment in advanced diseases. It can provide further treatment options after local MTB presentation, aiming to close the gap to access clinical trials.

Enriching single-arm clinical trials with external controls: possibilities and pitfalls

For the past decade, it has become commonplace to provide rapid answers and early patient access to innovative treatments in the absence of randomized clinical trials (RCT), with benefits estimated from single-arm trials. This trend is important in oncology, notably when assessing new targeted therapies. Some of those uncontrolled trials further include an external/synthetic control group as an innovative way to provide an indirect comparison with a pertinent control group. We aimed to provide some guidelines as a comprehensive tool for (1) the critical appraisal of those comparisons or (2) for performing a single-arm trial. We used the example of ciltacabtagene autoleucel for the treatment of adult patients with relapsed or refractory multiple myeloma after 3 or more treatment lines as an illustrative example. We propose a 3-step guidance. The first step includes the definition of an estimand, which encompasses the treatment effect and the targeted population (whole population or restricted to single-arm trial or external controls), reflecting a clinical question. The second step relies on the adequate selection of external controls from previous RCTs or real-world data from patient cohorts, registries, or electronic patient files. The third step consists of choosing the statistical approach targeting the treatment effect defined above and depends on the available data (individual-level data or aggregated external data). The validity of the treatment effect derived from indirect comparisons heavily depends on careful methodological considerations included in the proposed 3-step procedure. Because the level of evidence of a well-conducted RCT cannot be guaranteed, the evaluation is more important than in standard settings.

TITE-gBOIN-ET: Time-to-event generalized Bayesian optimal interval design to accelerate dose-finding accounting for ordinal graded efficacy and toxicity outcomes

One of the primary objectives of an oncology dose-finding trial for novel therapies, such as molecular-targeted agents and immune-oncology therapies, is to identify an optimal dose (OD) that is tolerable and therapeutically beneficial for subjects in subsequent clinical trials. These new therapeutic agents appear more likely to induce multiple low or moderate-grade toxicities than dose-limiting toxicities. Besides, for efficacy, evaluating the overall response and long-term stable disease in solid tumors and considering the difference between complete remission and partial remission in lymphoma are preferable. It is also essential to accelerate early-stage trials to shorten the entire period of drug development. However, it is often challenging to make real-time adaptive decisions due to late-onset outcomes, fast accrual rates, and differences in outcome evaluation periods for efficacy and toxicity. To solve the issues, we propose a time-to-event generalized Bayesian optimal interval design to accelerate dose finding, accounting for efficacy and toxicity grades. The new design named "TITE-gBOIN-ET" design is model-assisted and straightforward to implement in actual oncology dose-finding trials. Simulation studies show that the TITE-gBOIN-ET design significantly shortens the trial duration compared with the designs without sequential enrollment while having comparable or higher performance in the percentage of correct OD selection and the average number of patients allocated to the ODs across various realistic settings.

Quasi-partial order continual reassessment method: Applying toxicity scores to cancer dose-finding drug combination trials

The primary endpoint of most dose-finding cancer trials is patient toxicity, and the primary goal is to identify the maximum tolerated dose (MTD), that is, the highest dose that falls below or within a pre-specified toxicity tolerability threshold. Conventionally, dose-finding methods have utilized a binary toxicity endpoint based on whether or not a patient experiences a dose limiting-toxicity (DLT). Improving upon this, in recent years several methods have been developed for modeling toxicity scores, a novel continuous endpoint designed to more precisely estimate patient toxicity burden. Separately, drug-combination trials have become increasingly prevalent, and due to added complexities regarding estimating 'true' dose ordering and potential for more complex patient toxicity profiles, provide an ideal setting which may benefit from the improved precision of toxicity scores. In this paper, we merge two frameworks based on the Continual Reassessment Method (CRM) - the Quasi-CRM and the Partial Order CRM (POCRM) - to propose a novel approach for modeling toxicity scores in a combination-trial setting. We demonstrate that utilizing toxicity scores has the potential to greatly improve correct dose-selection over a variety of trial scenarios. We further present a simple adaptation to the toxicity-score model to control for potential over-dosing issues such that it adheres to the conventional DLT definition and will, at worst, perform equivalently to that of the traditional binary DLT framework. We demonstrate that extending toxicity scores to the combination-trial setting offers potential for improvement over the conventional binary endpoint models.

Natural product-based PROteolysis TArgeting Chimeras (PROTACs)

Covering: upto 2022Natural products have an embedded recognition of protein surfaces. They possess this property as they are produced by biosynthetic enzymes and are substrates for one or more enzymes in the biosynthetic pathway. The inherent advantages, compared to synthetic compound libraries, is this ligand-protein binding which is, in many cases, a function of the 3-dimensional properties. Protein degradation is a recent novel therapeutic approach with several compounds now in the clinic. This review highlights the potential of PROteolysis TArgeting Chimeras (PROTACs) in the area of natural products. The approach will complement existing approaches such as the direct use of a bioactive natural product or its analogues, pharmacophore development and drug-antibody conjugates. The chemical synthesis and challenges of using natural product-based PROTACs are summarised. The review also highlights methods to detect the ternary complexes necessary for PROTAC mechanism of action.

gBOIN-ET: The generalized Bayesian optimal interval design for optimal dose-finding accounting for ordinal graded efficacy and toxicity in early clinical trials

One of the primary objectives of an oncology dose-finding trial for novel therapies, such as molecular targeted agents and immune-oncology therapies, is to identify an optimal dose (OD) that is tolerable and therapeutically beneficial for subjects in subsequent clinical trials. These new therapeutic agents appear more likely to induce multiple low- or moderate-grade toxicities than dose-limiting toxicities. Besides, efficacy should be evaluated as an overall response and stable disease in solid tumors and the difference between complete remission and partial remission in lymphoma. This paper proposes the generalized Bayesian optimal interval design for dose-finding accounting for efficacy and toxicity grades. The new design, named "gBOIN-ET" design, is model-assisted, simple, and straightforward to implement in actual oncology dose-finding trials than model-based approaches. These characteristics are quite valuable in practice. A simulation study shows that the gBOIN-ET design has advantages compared with the other model-assisted designs in the percentage of correct OD selection and the average number of patients allocated to the ODs across various realistic settings.

Subgroup‐specific dose finding for phase I‐II trials using Bayesian clustering

In most models and algorithms for dose‐finding clinical trials, it is assumed that the trial participants are homogeneous—the optimal dose is the same for all those who qualify for the trial. However, if there are heterogeneous populations who may benefit from the same treatment, it is inefficient to conduct dose‐finding separately for each group, and assuming homogeneity across all subpopulations may lead to identification of the incorrect dose for some (or all) subgroups. To accommodate heterogeneity in dose‐finding trials when both efficacy and toxicity outcomes must be used to identify the optimal dose (as in immunotherapeutic oncology treatments), we utilize an adaptive Bayesian clustering method which borrows strength among similar subgroups and clusters truly homogeneous subgroups. Unlike methodology already described in the literature, our proposed methodology does not require the assumption of exchangeability between subgroups or a priori ordering of subgroups, but does allow for specification of different subgroup‐specific priors if prior information is available. We provide a comparison of operating characteristics between our method and Bayesian hierarchical models for subgroups in a variety of relevant scenarios. After simulation studies with four a priori subgroups, we observed that our method and the hierarchical models both outperform separate subgroup‐specific models when all subgroups have the same dose‐efficacy and dose‐toxicity curves. However, our method outperforms hierarchical models when one subgroup has a different dose‐efficacy or dose‐toxicity curve from the other three subgroups.

An adaptive gBOIN design with shrinkage boundaries for phase I dose-finding trials

Background

With the emergence of molecularly targeted agents and immunotherapies, the landscape of phase I trials in oncology has been changed. Though these new therapeutic agents are very likely induce multiple low- or moderate-grade toxicities instead of DLT, most of the existing phase I trial designs account for the binary toxicity outcomes. Motivated by a pediatric phase I trial of solid tumor with a continuous outcome, we propose an adaptive generalized Bayesian optimal interval design with shrinkage boundaries, gBOINS, which can account for continuous, toxicity grades endpoints and regard the conventional binary endpoint as a special case.

Result

The proposed gBOINS design enjoys convergence properties, e.g., the induced interval shrinks to the toxicity target and the recommended dose converges to the true maximum tolerated dose with increased sample size.

Conclusion

The proposed gBOINS design is transparent and simple to implement. We show that the gBOINS design has the desirable finite property of coherence and large-sample property of consistency. Numerical studies show that the proposed gBOINS design yields good performance and is comparable with or superior to the competing design.

TITE-gBOIN: Time-to-event Bayesian optimal interval design to accelerate dose-finding accounting for toxicity grades

The new therapeutic agents, such as molecular targeted agents and immuno-oncology therapies, appear more likely to induce multiple toxicities at different grades than dose-limiting toxicities defined in traditional dose-finding trials. In addition, it is often challenging to make adaptive decisions on dose escalation and de-escalation on time because of the fast accrual rate and/or the late-onset toxicity outcomes, causing the potential suspension of the enrollment and the delay of the trials. To address these issues, we propose a time-to-event Bayesian optimal interval design to accelerate the dose-finding process utilizing toxicity grades based on both cumulative and pending toxicity outcomes. The proposed design, named "TITE-gBOIN" design, is a nonparametric and model-assisted design and has the virtues of robustness, simplicity and straightforward to implement in actual oncology dose-finding trials. A simulation study shows that the TITE-gBOIN design has a higher probability of selecting the MTDs correctly and allocating more patients to the MTDs across various realistic settings while reducing the trial duration significantly, therefore can accelerate early-stage dose-finding trials.

Precision medicine in pediatric solid cancers

Despite huge advances in the diagnosis and treatment of pediatric cancers over the past several decades, it remains one of the leading causes of death during childhood in developed countries. The development of new targeted treatments for these diseases has been hampered by two major factors. First, the extremely heterogeneous nature of the types of tumors encountered in this age group, and their fundamental differences from common adult carcinomas, has made it hard to truly get a handle on the complexities of the underlying biology driving tumor growth. Second, a reluctance of the pharmaceutical industry to develop products or trials for this population due to the relatively small size of the 'market', and a too-easy mechanism of obtaining waivers for pediatric development of adult oncology drugs based on disease type rather than mechanism of action, led to significant difficulties in getting access to new drugs. Thankfully, the field has now started to change, both scientifically and from a regulatory perspective, in order to address some of these challenges. In this review, we will examine some of the recent insights into molecular features which make pediatric tumors so unique and how these might represent therapeutic targets; highlight ongoing international initiatives for providing comprehensive, personalized genomic profiling of childhood tumors in a clinically-relevant timeframe, and look briefly at where the field of pediatric precision oncology may be heading in future.

A simulation study of approaches for handling disease progression in dose-finding clinical trials

In traditional dose-finding studies, dose-limiting toxicity (DLT) is determined within a fixed time observation window where DLT is often defined as a binary outcome. In the setting of oncology dose-finding trials, often patients in advanced stage of diseases are enrolled. Therefore, disease progression may occur within the DLT observation window leading to treatment discontinuation and rendering the patient unevaluable for DLT assessment. As a result, additional patients have to be enrolled, increasing the sample size. We propose and compare several practical approaches for handling disease progression which occurs within the DLT observation window, while in the framework of the time-to-event continual reassessment method (TITE-CRM) which allows using partial observations. The approaches differ on the way they define an evaluable patient and in the way incomplete observations are included. The practical approaches, which we call strategies A, B and C, are illustrated and contrasted in the context of a single simulated trial, and compared via simulations under various scenarios of dose-progression relationship, in the setting of advanced soft-tissue sarcoma.

Change-point joint model for identification of plateau of activity in early phase trials

This article presents a phase I/II trial design for targeted therapies and immunotherapies, with the objective of identifying the optimal dose (OD). We employ a joint modeling technique for discrete time-to-event toxicity data and repeated and continuous biomarker measurements. For the biomarker measurements, we implement a change point linear mixed effects skeleton model. This model can accommodate both plateauing and nonplateauing dose-activity relationships. For each new cohort of patients, we estimate the maximum tolerated dose (MTD) taking toxicity as a cumulative endpoint, over six treatment cycles. Then, we select the OD using two different criteria. The OD is a dose that is equally active to the MTD or a dose located on the beginning of the plateau of the dose-activity relationship. Joint modeling allows us to take into account informative censoring due to toxicities or lack of activity and we also consider consent withdrawal and intermittent missing responses. Model estimation relies on likelihood inference.

Multiple roles of DNA2 nuclease/helicase in DNA metabolism, genome stability and human diseases

DNA2 nuclease/helicase is a structure-specific nuclease, 5'-to-3' helicase, and DNA-dependent ATPase. It is involved in multiple DNA metabolic pathways, including Okazaki fragment maturation, replication of 'difficult-to-replicate' DNA regions, end resection, stalled replication fork processing, and mitochondrial genome maintenance. The participation of DNA2 in these different pathways is regulated by its interactions with distinct groups of DNA replication and repair proteins and by post-translational modifications. These regulatory mechanisms induce its recruitment to specific DNA replication or repair complexes, such as DNA replication and end resection machinery, and stimulate its efficient cleavage of various structures, for example, to remove RNA primers or to produce 3' overhangs at telomeres or double-strand breaks. Through these versatile activities at replication forks and DNA damage sites, DNA2 functions as both a tumor suppressor and promoter. In normal cells, it suppresses tumorigenesis by maintaining the genomic integrity. Thus, DNA2 mutations or functional deficiency may lead to cancer initiation. However, DNA2 may also function as a tumor promoter, supporting cancer cell survival by counteracting replication stress. Therefore, it may serve as an ideal target to sensitize advanced DNA2-overexpressing cancers to current chemo- and radiotherapy regimens.

Pragmatic dose-escalation methods incorporating relative dose intensity assessment for molecularly targeted agents in phase I trials

The recommended phase 2 doses of molecularly targeted agents, determined by using an ordinal dose-finding method that only uses toxicity data at first cycle, may not be optimal. Some researchers have proposed the use of relative dose intensity that can account for late-onset, cumulative, and low-grade toxicities to determine the recommended phase 2 dose (RP2D). In this study, we proposed two dose escalation methods based on the observed relative dose intensities (RDIs) between the pre-specified intervals (cycles) for toxicity evaluation used in combination with DLT evaluation in the first cycle. First, we propose the modified 3 + 3 design that incorporates longitudinal RDI assessment. Second, we propose the sequential assessment method for longitudinal RDI (SARDI) to achieve faster dose escalation compared to that of the modified 3 + 3 design. Simulation studies demonstrated that the SARDI was, in many cases, superior to the ordinal and modified 3 + 3 designs in respect to the selection rate of true RP2D and study period. The two proposed methods could also in some cases decrease the average number of patients enrolled in the trial compared to that of the ordinary 3 + 3 design. Incorporation of the RDI assessment into the 3 + 3 design is not difficult and does not require the use of complex statistical techniques. Therefore, we believe that investigators who routinely use the 3 + 3 design in practice can easily use our proposed methods.

Cumulative Toxicity in Targeted Therapies: What to Expect at the Recommended Phase II Dose

BACKGROUND

In the era of molecularly targeted agents (MTAs), it is recommended to account for toxicity over several cycles to identify the recommended phase II dose (RP2D). We investigated the relationship between the risk of toxicity at cycle 1 and the cumulative incidence of toxicity over subsequent cycles in trials of single MTAs.

METHODS

On individual patient data from 26 phase I clinical trials of single MTAs provided by the National Cancer Institute, we estimated the probability of first-severe toxicity per treatment cycle as well as the cumulative incidence at, below, and above the maximum tolerated dose (MTD). Toxicity was further subclassified into nonhematologic and hematologic. A prediction table was developed to estimate the cumulative incidence up to six cycles based on the toxicity rate observed in the first cycle.

RESULTS

Overall, 942 patients were included. For patients treated at the MTD, the probability of first-severe toxicity decreased from 24.8% (95% prediction interval [PI] = 20.3% to 32.9%) to 2.2% (95% PI = 0.1% to 7.7%) from cycle 1 to 6, whereas the cumulative incidence of toxicity reached 51.7% (95% PI = 40.5% to 66.3%) after six cycles. Toxicity rates ranging from 20.0% to 30.0% in the first cycle were associated with 46.8% (95% PI = 39.5% to 54.2%) and 65.8% (95% PI = 57.7% to 73.1%) cumulative incidence after six cycles.

CONCLUSION

This study examined the risk of severe toxicity over time of single MTAs. The cumulative incidence of toxicity at the MTD was higher than the usually accepted toxicity targets, challenging the definition of the RP2D of MTAs. The prediction table may help calibrate the target rate at the RP2D.

GAPDH with NAD+-binding site mutation competitively inhibits the wild-type and affects glucose metabolism in cancer

BACKGROUND

Rapid utilization of glucose is a metabolic signature of majority of cancers, hence enzymes of the glycolytic pathway remain attractive therapeutic targets. Recent reports have shown that targeting the glycolytic enzyme, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), an abundant, ubiquitous multifunctional protein frequently upregulated in cancer, affects cancer progression. Here, we report that a catalytically-deficient mutant-GAPDH competitively inhibits the wild-type, and disrupts glucose metabolism in cancer cells.

METHODS

Using site-directed mutagenesis, the human GAPDH clone was mutated at one of the NAD⁺-binding sites, (i.e.) arginine (R13) and isoleucine (I14) to glutamine (Q13) and phenylalanine (F14), respectively. The inhibitory role of the mutant-GAPDH, and its effect on energy metabolism and cancer phenotype was determined using in vitro and in vivo models of cancer.

RESULTS

The enzymatically-dysfunctional mutant-GAPDH competitively inhibited the wild-type GAPDH in a cell-free system. In cancer cells, ectopic expression of the mutant-GAPDH, but not the wild-type, inhibited the glycolytic capacity of cellular-GAPDH, and led to the induction of metabolic stress accompanied by a sharp decline in glucose-uptake. Furthermore, expression of mutant-GAPDH affected cancer growth in vitro and in vivo. Mechanistically, structural analysis by bioinformatics revealed that the mutations at the NAD⁺-binding site altered the solvent-accessibility that perhaps affected the functionality of mutant-GAPDH.

CONCLUSION

Mutant-GAPDH affects the enzymatic function of cellular-GAPDH and disrupts energy metabolism.

GENERAL SIGNIFICANCE

Our findings demonstrate that a minimal mutation at the NAD⁺-binding site is sufficient to generate a competitive but dysfunctional GAPDH, and its ectopic expression inhibits the wild-type to disrupt glycolysis.

Treatment of advanced breast cancer with a metronomic schedule of oral vinorelbine: what is the opinion of Italian oncologists?

BACKGROUND

The aim of this study was to record the opinions of Italian oncologists about the use of oral vinorelbine administered metronomically in patients with advanced breast cancer.

METHODS

A series of meetings were held throughout Italy, and participants were asked how much they agreed with each of the several statements.

RESULTS

The majority of oncologists agreed that the concept of the minimum biologically effective dose should be used for drugs administered metronomically. Over 50% agreed that metronomic vinorelbine is an option in first-line chemotherapy for patients with advanced breast cancer, including those with a terminal illness and the elderly, as well as in young and fit patients. Just over one-third of experts agreed that a combination of two chemotherapy agents instead of one is not desirable in metastatic breast cancer because of increased toxicity. Most experts agreed that the main aim of a first-line therapy is to control the disease over time and to preserve quality of life.

CONCLUSION

Metronomically administered oral vinorelbine, either as monotherapy or in combination with other drugs, is effective in the long-term treatment of patients with advanced breast cancer. The clinical profiles of patients should be carefully considered to determine the appropriate treatment strategy.

Potential utility of a longitudinal relative dose intensity of molecularly targeted agents in phase 1 dose-finding trials

Phase 1 trials of molecularly targeted agents (MTA) often do not use toxicity data beyond the first cycle of treatment to determine a recommended phase 2 dose (RP2D). We investigated the potential utility of longitudinal relative dose intensity (RDI) that may be a better new way of determining a more accurate RP2D as a lower dose that is presumably more tolerable over the long term without compromising efficacy. All consecutive patients who were initially treated using a single MTA at the conventional RP2D or at one level lower dose (OLLD) of that RP2D in 9 phase 1 trials sponsored by the National Cancer Institute were included. The associations between longitudinal RDI, time to first progression, and response rate were analyzed. The RDI of the conventional RP2D group were maintained a rate of ≥70% throughout 10 cycles, and were higher than those of the OLLD group, although in both groups the RDI gradually decreased with additional treatment cycles. The RP2D group was similar to the OLLD group with respect to time to first progression and response rate. In both groups, however, the decreasing RDI over time was significantly associated with shorter time to first disease progression; therefore, the longitudinal RDI, which takes into account lower grade toxicity occurrences, may be useful in determining a more desirable dose to use in phase 2 and 3 studies.

How to emerge from the conservatism in clinical research methodology?

PURPOSE OF REVIEW

Despite recent changes in clinical research methodology, many challenges remain in drug development methodology.

RECENT FINDINGS

Advances in molecular biology and cancer treatments have changed the clinical research landscape. Thus, we moved from empirical clinical oncology to molecular and immunological therapeutic approaches. Along with this move, adapted dose-limiting toxicities definitions, endpoints, and dose escalation methods have been proposed. Moreover, the classical frontier between phase I, phase II, and phase III has become unclear in particular for immunological approaches. So, investigators are facing major challenges in drug development methodology.

SUMMARY

We propose to individualize clinical research using innovative approaches to significantly improve patient outcomes and targeting what is considered unmet need. Integrating high level of translational research and performing well designed biomarker studies with great potential for clinical practice are of utmost importance. This could be performed within new models of clinical research networks and by building a strong collaboration between academic, cooperative groups, on-site investigators, and pharma.

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.

Metronomic chemotherapy for advanced breast cancer patients

Metronomic chemotherapy refers to the minimum biologically effective dose of a chemotherapy agent given as a continuous dosing regimen with no prolonged drug-free breaks that leads to antitumor activity. This schedule seems to have not only a direct cytotoxicity on cancer cells but also an effect on the tumor microenvironment by inhibiting tumor angiogenesis and modulating immune response. Metronomic chemotherapy was widely investigated in patients with breast cancer. The results of these studies showed that this strategy is not only effective but has a low toxicity profile too, proposing as a promising strategy for breast cancer patients. In this review we summarize the results of Phase II and III studies evaluating metronomic therapy in metastatic breast cancer.

A Bayesian dose-finding design incorporating toxicity data from multiple treatment cycles

Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle, although patients continue to receive treatment for multiple cycles. In addition, the toxicity data from multiple types and grades are typically summarized into a single binary outcome of dose-limiting toxicity. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades. In this work, we propose to account for longitudinal repeated measures of total toxicity profile over multiple treatment cycles, accounting for cumulative toxicity during dosing-finding. A linear mixed model was utilized in the Bayesian framework, with addition of Bayesian risk functions for decision-making in dose assignment. The performance of this design is evaluated using simulation studies and compared with the previously proposed quasi-likelihood continual reassessment method (QLCRM) design. Twelve clinical scenarios incorporating four different locations of maximum tolerated dose and three different time trends (decreasing, increasing, and no effect) were investigated. The proposed repeated measures design was comparable with the QLCRM when only cycle 1 data were utilized in dose-finding; however, it demonstrated an improvement over the QLCRM when data from multiple cycles were used across all scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Dose finding with longitudinal data: simpler models, richer outcomes

Phase I oncology clinical trials are designed to identify the optimal dose that will be recommended for phase II trials. This dose is typically defined as the dose associated with a certain probability of severe toxicity at cycle 1, although toxicity is repeatedly measured over cycles on an ordinal scale. Recently, a proportional odds mixed-effect model for ordinal outcomes has been proposed to (i) identify the optimal dose accounting for repeated events and (ii) to provide some framework to explore time trend. We compare this approach to a method based on repeated binary variables and to a method based on an under-parameterized model of the dose-time toxicity relationship. We show that repeated binary and ordinal outcomes both improve the accuracy of dose-finding trials in the same proportion; ordinal outcomes are, however, superior to detect time trend even in the presence of nonproportional odds models. Moreover, less parameterized models led to the best operating characteristics. These approaches are illustrated on two dose-finding phase I trials. Integration of repeated measurements is appealing in phase I dose-finding trials.

An FDA oncology analysis of antibody-drug conjugates

Antibody-drug conjugates (ADCs) are complex molecules composed of monoclonal antibodies conjugated to potent cytotoxic agents through chemical linkers. Because of this complexity, sponsors have used different approaches for the design of nonclinical studies to support the safety evaluation of ADCs and first-in-human (FIH) dose selection. We analyzed this data with the goal of describing the relationship between nonclinical study results and Phase 1 study outcomes. We summarized the following data from investigational new drug applications (INDs) for ADCs: plasma stability, animal study designs and toxicities, and algorithms used for FIH dose selection. Our review found that selecting a FIH dose that is 1/6th the highest non-severely toxic dose (HNSTD) in cynomolgus monkeys or 1/10th the STD10 in rodents scaled according to body surface area (BSA) generally resulted in the acceptable balance of safety and efficient dose-escalation in a Phase 1 trial. Other approaches may also be acceptable, e.g. 1/10th the HNSTD in monkeys using BSA or 1/10th the NOAEL in monkeys or rodents using body weight for scaling. While the animal data for the vc-MMAE platform yielded variable range of HNSTDs in cynomolgus monkeys, MTDs were in a narrow range in patients, suggesting that for ADCs sharing the same small molecule drug, linker and drug:antibody ratio, prior clinical data can inform the design of a Phase 1 clinical trial.

Challenges of clinical trial design for targeted agents against pediatric leukemias

The past 40 years have seen significant improvements in both event-free and overall survival for children with acute lymphoblastic and acute myeloid leukemia (ALL and AML, respectively). Serial national and international clinical trials have optimized the use of conventional chemotherapeutic drugs and, along with improvements in supportive care that have enabled the delivery of more intensive regimens, have been responsible for the major improvements in patient outcome seen over the past few decades. However, the benefits of dose intensification have likely now been maximized, and over the same period, the identification of new cytotoxic drugs has been limited. Therefore, challenges remain if survival is to be improved further. In pediatric ALL, 5-year-survival rates of over 85% have been achieved with risk-stratified therapy, but a notable minority of patients will still not be cured. In pediatric AML, different challenges remain. A slower improvement in overall survival has taken place in this patient population. Despite the obvious morphological heterogeneity of AML blasts, biological stratification is comparatively limited, and translation into risk-stratified therapeutic approaches has only best characterized by the use of retinoic acid for t(15;17)-positive AML. Even where prognostic markers have been identified, limited therapeutic options or multi-drug resistance of AML blasts has limited the impact on patient benefit. For both, the acute morbidities of current treatment remain significant and may be life-threatening alone. In addition, the Childhood Cancer Survivor Study (CCSS) highlighted many leukemia survivors develop one or more chronic medical conditions attributable to treatment (1, 2). As the biology of leukemogenesis has become better understood, key molecules and intracellular pathways have been identified that offer the possibility of targeting directly the leukemia cells while sparing normal cells. Consequently, there is now a drive to develop novel leukemia-specific or "targeted" therapies. These new classes of drugs will have mechanisms of action, toxicities, and therapeutic indices quite different from conventional cytotoxic drugs previously encountered, thus rendering current clinical trial methodologies inappropriate. Clinical trial methods will need to be adapted to accommodate these features of these new classes of drugs. This review will address the challenges and some of the techniques for developing clinical trials for targeted therapies.

Dose-finding designs using a novel quasi-continuous endpoint for multiple toxicities

The aim of a phase I oncology trial is to identify a dose with an acceptable safety profile. Most phase I designs use the dose-limiting toxicity, a binary endpoint, to assess the unacceptable level of toxicity. The dose-limiting toxicity might be incomplete for investigating molecularly targeted therapies as much useful toxicity information is discarded. In this work, we propose a quasi-continuous toxicity score, the total toxicity profile (TTP), to measure quantitatively and comprehensively the overall severity of multiple toxicities. We define the TTP as the Euclidean norm of the weights of toxicities experienced by a patient, where the weights reflect the relative clinical importance of each grade and toxicity type. We propose a dose-finding design, the quasi-likelihood continual reassessment method (CRM), incorporating the TTP score into the CRM, with a logistic model for the dose-toxicity relationship in a frequentist framework. Using simulations, we compared our design with three existing designs for quasi-continuous toxicity score (the Bayesian quasi-CRM with an empiric model and two nonparametric designs), all using the TTP score, under eight different scenarios. All designs using the TTP score to identify the recommended dose had good performance characteristics for most scenarios, with good overdosing control. For a sample size of 36, the percentage of correct selection for the quasi-likelihood CRM ranged from 80% to 90%, with similar results for the quasi-CRM design. These designs with TTP score present an appealing alternative to the conventional dose-finding designs, especially in the context of molecularly targeted agents.

Inorganic phosphate enhances sensitivity of human osteosarcoma U2OS cells to doxorubicin via a p53-dependent pathway

Osteosarcoma is the most common malignant primary bone tumor in children and adolescents. The clinical outcome for osteosarcoma remains discouraging despite aggressive surgery and intensive radiotherapy and chemotherapy regimens. Thus, novel therapeutic approaches are needed. Previously, we have shown that inorganic phosphate (Pi) inhibits proliferation and aggressiveness of human osteosarcoma U2OS cells identifying adenylate cyclase, beta3 integrin, Rap1, ERK1/2 as proteins whose expression and function are relevantly affected in response to Pi. In this study, we investigated whether Pi could affect chemosensitivity of osteosarcoma cells and the underlying molecular mechanisms. Here, we report that Pi inhibits proliferation of p53-wild type U2OS cells (and not of p53-null Saos and p53-mutant MG63 cells) by slowing-down cell cycle progression, without apoptosis occurrence. Interestingly, we found that Pi strongly enhances doxorubicin-induced cytotoxicity in U2OS, and not in Saos and MG63 cells, by apoptosis induction, as revealed by a marked increase of sub-G1 population, Bcl-2 downregulation, caspase-3 activation, and PARP cleavage. Remarkably, Pi/doxorubicin combination-induced cytotoxicity was accompanied by an increase of p53 protein levels and of p53 target genes mdm2, p21 and Bax, and was significantly reduced by the p53 inhibitor pifithrine-alpha. Moreover, the doxorubicin-induced cytotoxicity was associated with ERK1/2 pathway inhibition in response to Pi. Altogether, our data enforce the evidence of Pi as a novel signaling molecule capable of inhibiting ERK pathway and inducing sensitization to doxorubicin of osteosarcoma cells by p53-dependent apoptosis, implying that targeting Pi levels might represent a rational strategy for improving osteosarcoma therapy.

Targeting cancer with peptide aptamers

A major endeavour in cancer chemotherapy is to develop agents that specifically target a biomolecule of interest. There are two main classes of targeting agents: small molecules and biologics. Among biologics (e.g.: antibodies), DNA, RNA but also peptide aptamers are relatively recent agents. Peptide aptamers are seldom described but represent attractive agents that can inhibit a growing panel of oncotargets including Heat Shock Proteins. Potential pitfalls and coming challenges towards successful clinical trials are presented such as optimizing the delivery of peptide aptamers thanks to Nanotechnology.

The cytotoxic and growth inhibitory effects of palladium(II) complexes on MDA-MB-435 cells

The antitumorigenic potential of two palladium(II) complexes, [Pd(ca(2)-o-phen)Cl(2)] - C1 and [Pd(dmba)(dppp)Cl] - C2, was evaluated, using MDA-MB-435 cells, a human breast adenocarcinoma cell-line that does not express the estrogen receptor α (ER-). Growth inhibition and induced alterations in cell-morphology were analyzed. The sulforhodamine B test showed that, compared to control cells, both C1 and C2 significantly inhibited (p < 0.5) cell growth. The maximum effect with both was achieved with 1 μM complexes, after 24 h of treatment. No further cell-growth inhibition was achieved by increasing concentration or incubation time. Cell morphology was analyzed after staining with hematoxylin-eosin (HE). The morphological changes noted in the treated cells were cell rounding-up, shrinkage, nuclear condensation and reduction of cell length (p < 0.05), thereby indicating that both C1 and C2 are cytotoxic to breast adenocarcinoma cells. All together, there was every indication that, by decreasing cell growth and inducing morphological changes, the tested complexes are cytotoxic, hence their potentiality as promising candidates for antineoplastic drug development.

ICH S9

International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) S9 is the first international regulatory guidance document devoted to a specific therapeutic area, highlighting its importance in harmonizing regulatory expectations for the nonclinical development of therapeutics designed to treat advanced cancer. ICH S9 successfully outlines the core requirements for the nonclinical development of novel oncology therapeutics, and the unique risk-benefit considerations for expediting drug development to treat these most grievous diseases. However, development companies and regulatory agencies have had limited opportunity to apply this guidance, so our collective experience in developing therapeutics under the guidance is limited. Discussed here are several key areas of ambiguity in the guidance, including identification of the patient population, selection of the initial safe dose for first-in-human trials, and requirements for nonclinical recovery data.