Traditionally, early-stage clinical trials focus on toxicity assessment and dose selection. Today, a growing number of Phase 1/2a trials are designed to draw inference about preliminary response rates due, in part, to the use of biomarkers and adaptive design approaches that enhance the early detection of efficacy signals. These approaches may add to study complexity and thus require careful planning from study design to execution.

Successful design and execution of early-stage trials in precision oncology require cross-functional collaboration and careful consideration of critical study elements that can be aided by these nine tips.

Define the trial objective. Articulating the overarching goal of the study – whether it is safety, pharmacological activity, preliminary efficacy signal, feasibility, or a combination of these – helps ensure the protocol is aligned with the research objective.
Engage with key stakeholders. Identifying and engaging with patients, caregivers, clinicians, key opinion leaders, payers, and other key stakeholders is an opportunity to validate that the study is relevant and to seek feedback on the protocol, including the nature and frequency of study-related assessments.
Select appropriate biomarkers. Classify the genetic or molecular markers that will be used to pinpoint patients who are most likely to benefit from the treatment under investigation. The use of predictive biomarkers also helps minimize the number of patients who are exposed to therapies or doses that are unlikely to be effective.
Key considerations when selecting biomarkers include:
- Relevance to the disease
- Sensitivity and specificity
- Analytical validity
- Clinical utility
- Feasibility of measurement in a clinical setting
- Body of supporting evidence
Identify the study population and subgroups. This is particularly important for clinical trials that incorporate biomarkers. Clearly defined inclusion and exclusion criteria can be used to enrich the study population. These criteria can also be used for identifying sites that have access to not only the target patient population, but also any specialized equipment or software necessary for biomarker analysis. Special consideration should be given to how to handle patients who progress after initial treatment, especially if overall survival is a study endpoint.
Define the methodology used to assess response. Historically, imaging-based anatomical criteria were the primary method for assessing response in solid tumors. With the emergence of immunotherapies that trigger different tumor response patterns than classic chemotherapy drugs, iRECIST became more common. In precision oncology trials, biomarkers may be more sensitive than tumor measurements for gauging response. If a biomarker is used for response assessment, an assay for measuring that biomarker may need to be developed and validated, which may increase the lead time to study start-up.
Consider patient-reported outcomes. With increasing regulatory emphasis on the patient perspective and the value of real-world evidence, collecting data on patient-reported outcomes such as quality of life helps provide a more comprehensive picture of the impact of the treatment. Such data may help support the therapeutic value story.
Decide whether to include a control and whether to blind the study. Selection of an appropriate control group facilitates the assessment of early clinical activity or efficacy signals, as well as enriching the interpretation of safety data. Where possible, using a standard-of-care control is preferred as it may be unethical to assign patients to placebo alone. If concurrent controls are not feasible, it may be possible to use historical controls. In addition, recent innovative approaches using modeling and simulation techniques to develop in silico (or computer-generated) control arms are gaining more traction since the release in 2021 of FDA’s guidance on complex innovative designs.
Determine a dosing regimen. If using an adaptive design for Phase 1 dose escalation, sponsors will need to decide what the starting dose will be, how many doses to include, and what the dose-escalation strategy will be. With trials exploring a high number of dose candidates (say 4 or more dose levels), model-based dose escalation designs, such as the Bayesian optimal interval model, provide greater efficiency in identifying the optimal dose.
Establish a data management plan. Biomarkers generate a significant volume and variety of data, so having a robust data management plan is critical for ensuring data quality. Prior to developing the plan, it is important to clearly define and understand the scope of the biomarker data to be collected and managed, including the types of biomarkers, the sample types, and the methods that will be used to collect and analyze the data. This plan should include protocols for sample collection, storage, and shipment and procedures for data entry and quality control. It should also include policies for data access and sharing, including processes for granting access, maintaining data security, and protecting patient privacy.

Taking it to the clinic

There are more than 21,000 early-stage oncology studies that are either ongoing or planned.¹ Precision oncology trials typically focus on niche patient populations, with the aim of maximizing a drug’s potential and detecting early response signals. When properly designed and implemented, biomarker-driven early-stage oncology trials can effectively generate evidence that can be used to inform, optimize, and accelerate later phases of development.

At Premier Research, our experience spans all aspects of oncology and hematology drug development and clinical trials, encompassing more than 190 studies across multiple indications in the past five years. To learn more about how we can help you design and operationalize your precision oncology study, contact us.

[1] Clinical Trials Arena. Early phase cancer trials: how to draft a successful blueprint, June 17, 2022.