Early phase oncology research involves Phase I clinical trials, which determine the safety and effectiveness of a drug (or drug combination) in treating cancer1. Phase I trials usually recruit only a few patients intending to identify a safe dose with an acceptable toxicity profile, the maximum tolerated dose (MTD), for subsequent testing. Dose escalation studies are conducted to find the best dose, whereby a series of cohorts are given the trial drug at different dose levels. Early phase oncology research is essential to assess the safety of experimental oncology drugs, their effect on the body, and their side effects, as well as to determine a safe dose range.

As clinical research has shifted from traditionally histology-based to molecularly-targeted oncology drug development, innovative trial designs are critical to successfully advancing cancer treatment. The shift to molecular targets results in increasingly smaller cancer populations, whereby traditional statistical designs may result in underpowered trials. Innovative trial designs account for patient and treatment effect heterogeneity, e.g., trials that match a patient’s molecular alterations with a specific targeted agent.

Key challenges of the traditional 3+3 design developed for cytotoxic chemotherapy include more efficiency and accuracy for molecularly targeted agents. Additionally, conventional Phase I dose-finding designs assume efficacy increases with increasing dose, which is applicable for cytotoxic chemotherapies but less so for targeted agents that have different dose-response relationships. Further, conventional designs assume that Phase I trial participants are the same, i.e., the optimal dose is the same for all participants. In reality, targeted agents in precision oncology have demonstrated a need for subgroup-specific dosing, as biomarker subgroups may have different dose-toxicity curves.

Read on to learn more about early-phase oncology research and innovative trial designs!

 

Understanding Early-Phase Oncology Research 

Early-phase oncology trials are the foundation of successful oncology drug development programs. In these studies, a new drug or drug combination is applied for the first time in humans to define the drug dose and schedule that is then evaluated in subsequent trials. 

The key objectives of traditional Phase I oncology trials are to evaluate the safety and activity of investigational drugs, including determining dose and preliminary efficacy. Dose optimization seeks to identify a dose that preserves clinical benefit with the best possible tolerability. Historically, the MTD in a Phase I trial is used in the subsequent Phase II trial. 

 

Traditional Trial Designs vs. Innovative Approaches 

For over 70 years, the dose and schedule of oncology drugs have been guided by drug development design and assumptions of the earliest cytotoxic drugs. However, very few new cancer drugs in development are cytotoxic agents, challenging these prevailing assumptions, e.g., Phase I trials for therapeutics such as monoclonal antibodies may never reach the MTD. Further, drug exposure to new agents may change over time due to various factors, such as changes in tumor burden. Harmonized guidelines, particularly the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E4, introduced in the 1990s, recommend thoroughly defining the dose-response relationship for efficacy and toxicity.  

 

Overview of traditional clinical trial designs  

While traditional clinical trials are considered the gold standard of evidence, clinical research problems are becoming increasingly complex as resources for research are increasingly scarce. For example, traditional clinical trial designs with fixed sample sizes and one or two arms may be unable to address emerging research questions vs. adaptive trial designs, which allow for prospective modification based on data accumulated during the trial8. Jaki et al. highlight the drug fulvestrant, an example where the “best” dose was not found during the Phase I trial, emphasizing the need for rational and rigorous dose-finding studies to avoid large Phase III trials based on a suboptimal dose.  

 

Emerging Trends in Innovative Clinical Trial Designs 

Historically, oncology drug development followed the sequential path of Phase I, II, and III clinical trials using traditional trial designs where a single experimental drug is evaluated in a single disease population. Advances in genomic tech, e.g., next-generation sequencing (NGS), enable genomic profiling and biomarkers in oncology drug development. Over time, trials have evolved from tumor type-centered to gene-directed and histology-agnostic trials, requiring innovative trial designs that enable personalized treatment strategies matched with individual biomarker profiles. The traditional drug development path has become suboptimal and less efficient compared with innovative trial designs such as basket and umbrella trials, platform trials, and N-of-1 patient-centric studies, which can simultaneously evaluate more than one investigational drug and/or more than one disease population. As a result, innovative trial designs accelerate drug evaluation and approval and are increasingly replacing traditional trial designs.  

 

Adaptive clinical trial designs 

Adaptive trials include preplanned modifications of an ongoing trial, e.g., terminating a trial early due to futility or efficacy, based on the accumulating trial evidence. The U.S. Food and Drug Administration (FDA) recognizes the benefits of adaptive designs over traditional trial designs, including improving statistical efficiency, addressing ethical considerations, understanding treatment effects, and being more acceptable to stakeholders. The FDA published guidance on the use of adaptive designs for clinical trials in 2019. Innovations in adaptive trials include borrowing information from historical or supplemental data sources, sequential multiple-assignment randomized trials (SMART), and seamless designs. 

 

Basket and umbrella clinical trials 

Basket trials simultaneously evaluate a single investigational drug or drug combination across multiple cancer types or subtypes of the same cancer in different populations defined by disease stage, histology, number of prior therapies, genetic or other biomarkers, or demographic characteristics. The rationale is that treatments targeting specific molecular alterations can potentially treat all tumors regardless of origin. Since the same intervention is tested across all baskets, a recent article explored borrowing information across baskets to improve statistical precision and power using Bayesian methods.

Basket trials can enhance operational efficiency and increase patient participation. An operational advantage of basket trials is that only one study team and protocol are needed. Regarding patient participation, basket trials can benefit patients with rare tumors where individual tumor types cannot be adequately powered. Further, basket trials allow for stratified analysis, where statistical analysis for each substudy can be independent of the other studies. One of the challenges facing basket trials is that molecular variant(s) may not be the only driver of tumor response. 

Umbrella trials test multiple investigational drugs or drug combinations in a single disease with different molecular subtypes, where all investigational drugs (or combinations) are enrolled at the same time. A benefit of umbrella trials is that they can add knowledge specific to a given disease population, which could support a therapeutic confirmatory result. Additionally, predictive and prognostic biomarkers can be distinguished if randomization to treatment arms within a subgroup occurs. Umbrella trials can also cycle quickly through ineffective treatments.

In practice, a major difficulty of umbrella trials is that a specific molecular target requirement can make enrolling patients difficult. To increase trial efficiency and control for multiplicity, statistical methods focus on information borrowing across sub-studies or from historical studies. 

 

Platform clinical trials 

Platform trials test multiple investigational drugs in a single disease or a hybrid of different disease indications and treatments (or drug combinations) in the same trial. Additionally, platform trials allow flexibility in adding or dropping treatment arms. As platform trials address multiple research questions using a single protocol, they reduce the time needed to reach a meaningful trial endpoint. Innovative statistical methods increase the flexibility of platform trials with mid-trial adaptations, e.g., seamlessly adding new treatments as they emerge and dropping poorly performing treatments while maintaining strong type I error control.  

 

Challenges and Considerations with Early-Phase Oncology Trials

 

Regulatory considerations for implementing innovative designs 

The complexity of innovative trial designs results in increased methodological and regulatory challenges. Master protocols are efficient and can expedite drug development. However, they can also introduce additional operational and regulatory complexities.

A collaborative public-private partnership to identify regulatory issues of master protocols collected the needs of all relevant stakeholders and recently reported their findings. The EU Patient-Centric Clinical Trial Platforms (EU-PEARL) was funded by the Innovative Medicines Initiative, with around 36 organizations representing patients, clinicians, researchers, authorities, and industry. Researchers Nguyen et al. discovered that issues needing harmonization or clarification in guidelines or further methodological research include questions around clinical trial submissions in Europe, the need for multiplicity control across the whole master protocol, the use of non-concurrent controls, and the impact of different types of randomization. Early interaction and communication with regulators are essential to discuss proposed trial designs. In line with this, the FDA issued a guideline specifically for interactions with the FDA on complex, innovative trial designs.  

 

Operational challenges 

Master protocols can introduce operational complexities. A survey to understand the current usage of master protocols and identify challenges faced by stakeholders revealed operational concerns focused on the increased operational complexity associated with master protocols vs. traditional clinical trials. Respondents highlighted specifics, including taking longer to plan and initiate a master protocol trial vs. a traditional trial, issues related to the development of master protocol documents, and the scale and complexity of trial processes such as data collection and reporting. Another operational challenge identified was developing and maintaining a trial infrastructure that continuously supports these trials’ fast-paced and ever-changing nature. Regarding patient enrollment, the availability of validated biomarker assays and timely processes could affect enrolment and assignment of therapy.

Overall, respondents reported that one of the most significant operational challenges is having a system that ensures the quality and timeliness of data. Data flow velocity is paramount, particularly in early-phase oncology trials. Sponsors depend on data to assess treatment toxicities and safeguard patient safety.  

 

Statistical complexities and approaches to mitigate risks 

Statistical challenges include the difficulty in evaluating the statistical properties of the master protocol by clinical trial simulation, the lack of guidance on the use of non-concurrent control patients, and the lack of guidance on multiplicity control. In light of the statistical complexities of master protocols, clinical trial simulations are needed to evaluate statistical properties such as type I error rates, power, and bias in estimation. Regarding the lack of guidance on using non-concurrent control patients and on multiplicity control, the researchers highlighted that various authors, including representatives from regulatory agencies, have addressed the gap by publishing their reviews on the topic(s).  

 

Future Directions and Implications for Early-Phase Oncology Research

 

Potential future trends in early-phase oncology research 

Regulatory agencies like the FDA and the European Medicines Agency (EMA) recognize innovative trial designs in early-phase oncology research as an essential addition to available clinical trial designs. Additionally, patient engagement is viewed as a critical factor by both regulatory agencies. Huml et al. propose that optimizing patient engagement in master protocols by including the patient voice throughout master protocol development and conduct will raise adoption, increase trial efficiency, and improve success rates for sponsors, providers, and patients. 

 

Implications for oncology CROs and clinical trial sponsors 

A recent review found that rule-based study designs, such as the ‘3+3’ design, remain very common in early-phase oncology research. The recommendation that model-assisted designs should be the design of choice is timely, and statisticians in contract research organizations (CROs) and sponsor organizations have the opportunity to improve early-phase oncology drug development programs. 

Key challenges of the traditional 3+3 design developed for cytotoxic chemotherapy described above include the need for more efficiency and accuracy for molecularly targeted agents. New targeted drugs, immunotherapies, cell therapies, and vaccines require more efficient designs and a refocusing on including study designs that estimate the Optimal Biological Dose (OBD), changes regulators are encouraging sponsors to make. Explore the evolving landscape of immunotherapy in oncology, promising advancements, and the shaping of future oncological care. 

As trials become more complex, clear communication between sponsors and regulators becomes more crucial. Guidelines recommend early interaction to discuss proposed trial designs. For example, the FDA issued guidelines specifically for sponsors to interact with the agency on complex, innovative trial designs, namely on aspects of the design, including the purpose, execution, and operating characteristics.

To match the increasing complexity of designs, ethics committee members emphasize the need for training and the availability of relevant statistical expertise. Stakeholders of the public-private partnership studied and reported on by Nguyen et al. stress the need for open and collaborative dialogue.  

 

Conclusion on the transformative impact of innovative trial designs 

Advancements in genomic technology enable genomic profiling and biomarkers in oncology drug development, enabling a shift from histology-based to molecularly targeted drug development. Innovative trial designs provide a transformative impact on oncology drug development, as relying on traditional statistical designs for new molecularly targeted drugs would likely result in underpowered trials. 

 

Conclusion 

Early-phase oncology research is important to assess the safety of experimental oncology drugs, evaluate their effect on a patient, evaluate side effects, and determine a safe dose range before progressing to the next stage of drug development. Innovative trial designs are a critical aspect of advancing oncology treatments, as traditional trial designs have constraints that limit their applicability for molecularly targeted drug development.

With ongoing changes in health needs, advances in technology, and the evolution of healthcare systems and regulatory environments, we may discover that current innovations in clinical trial design may become irrelevant, lead to inaccurate conclusions, or have unintended consequences for oncology treatment. Continuous innovation in advancing early-phase oncology research is essential. Examples of innovation in adaptive trials include borrowing information from historical or supplemental data sources, sequential multiple-assignment randomized trials (SMART), and seamless designs.

Global collaborative public-private partnerships that involve relevant stakeholders to identify and address issues related to innovative trial designs like EU-PEARL indicate that stakeholders are already participating in the conversation. To mutually benefit from innovative trial designs, stakeholders should embrace, support, and actively shape the continuous development of innovative trial designs.  

 

TFS Oncology CRO

 

Overview of TFS’s expertise in early-phase oncology trials 

The TFS oncology and hematology team has specialists who understand the challenges of modern oncology and hematology trials and will strategically support your research and development at its crucial go/no-go stage. Discover how TFS provided full CRO services for a First in Man Solid Tumor Oncology study, including site identification/initiation/training; patient enrollment; project management/monitoring; data management; biostatistics & programming; medical writing, safety, medical monitoring, and regulatory consulting. This open study required close follow-up on safety and disease.

As sponsors depend on data to assess treatment toxicities and to safeguard patient safety in early-phase oncology trials, data flow velocity is paramount. An uninterrupted data flow enables timely decision-making to address clinical trial challenges quickly and effectively. Early-phase oncology trials often encounter unique challenges that create data flow bottlenecks, such as the gated patient enrollment, post-pandemic resource constraints commonly witnessed at research sites, and overcomplicated electronic case report form (eCRF) design. TFS HealthScience is experienced in implementing enhanced data flow strategies, including improved cohort management planning, site support, training, and careful electronic data capture (EDC) system selection and testing, allowing sponsors to tackle early-phase oncology trial challenges holistically while increasing trial efficiency. 

 

Specific capabilities in supporting innovative trial designs 

TFS provides oncology and hematology scientific, medical, regulatory, and operational expertise and tailored solutions to ensure the successful execution of complex oncology trials. This highly specialized discipline requires extreme attention to detail and a broad understanding of your requirements. Your trial is unique—we have the strategy and experts to support it from design to completion. 

TFS supports innovative trial designs through clinical trial design and management. From complex early-phase trials, including basket trials, precision medicines, immuno-oncology, and rare hematologic diseases, the TFS team is here to support the development of your trial. Trial design and delivery, for example, includes leveraging adaptive and novel trial designs, incorporating patient feedback and insights, and applying AI and machine learning (ML).

Ready to request a proposal or speak to a team member? Contact us today!