Phase 1 Dose-Escalation Oncology Trial

Case Study Introduction

Patients with advanced solid tumours who have progressed after prior platinum-based therapies often face limited treatment options. Platinum-based chemotherapy remains foundational across multiple tumour types, but clinical benefit can diminish over time, particularly when disease becomes less responsive to treatment.

To address this unmet need, a sponsor initiated a Phase 1 oncology study evaluating an investigational oral WEE1 kinase inhibitor in combination with a platinum-based chemotherapy agent. WEE1 is a key regulator of cell-cycle progression and the DNA damage response. In theory, inhibiting WEE1 can reduce tumour cells’ ability to repair DNA damage, potentially increasing the anti-tumour effect of DNA-damaging chemotherapy. While WEE1 inhibitors had shown promise in early research, there were still gaps in understanding how this approach performs in combination across different solid tumour types, and how to run safe, efficient first-in-combination dose-finding in the clinic.

Quanticate was engaged to support the programme with integrated operational and analytical services, helping the sponsor turn emerging trial data into clear, timely decisions.

Objectives and Key Challenges

Objectives

Establish a safe and tolerable dosing regimen for an investigational WEE1 inhibitor in combination with platinum-based chemotherapy.
Use an adaptive dose-finding approach to support selection of a recommended phase 2 dose (RP2D).
Ensure that safety, laboratory, and biomarker-adjacent data could be reviewed quickly and consistently to guide cohort progression.

Key challenges

Dose optimisation in a novel combination regimen
Determining the right dose and schedule required careful cohort management. Combination regimens increase uncertainty around tolerability, and the interaction between agents can raise the risk of toxicity.
Managing uncertainty around toxicity and tolerability
The study needed rapid detection and response to safety signals. Specific concerns included myelosuppression and kidney-related toxicity, alongside uncertainty about potential off-target effects of sustained WEE1 inhibition in healthy tissues with high cell turnover, such as bone marrow and gastrointestinal tissue. Consistent evaluation of dose-limiting toxicities (DLTs) within defined windows was essential.
Operationalising real-time decision-making across complex data streams
Cohort progression depends on up-to-date safety and laboratory data, but combination studies also generate granular pharmacokinetics (PK) and pharmacodynamics (PD) data. Collecting, cleaning, and integrating these data across multiple sites, without compromising quality, was critical to keep reviews on track.
Implementing an adaptive Bayesian model
The programme planned to use the Modified Continual Reassessment Method (mCRM), a Bayesian dose-finding approach that adapts escalation and de-escalation based on accumulating DLT data . The model offered advantages, but it had to be implemented correctly, supported by reliable data pipelines, and presented in a way the study team could trust during review meetings.

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Strategic Approach and Tailored Solutions

Quanticate provided integrated data management, statistical analysis, and statistical programming services aligned to the practical needs of adaptive Phase 1 dose-finding. The focus was straightforward, keep the data clean, keep the outputs consistent, and make decision points easier to run.

Data management built for time-sensitive reviews
- Worked within the sponsor’s electronic data capture (EDC) environment to support reliable collection of safety, laboratory, and PK/PD data.
- Implemented data checks and validation processes to flag missing, inconsistent, or outlying values early.
- Supported dataset readiness by maintaining structured query management and ongoing review, reducing the risk of delays caused by late data entry or prolonged query cycles.
- Ensured that key cohort inputs, especially those tied to DLT windows, were current, traceable, and suitable for decision-making.
Operationalising adaptive dose-finding using mCRM
- Supported implementation of the mCRM approach so that accumulating DLT outcomes could inform dose transitions in a controlled way.
- Produced model outputs aligned to the timing of review points, enabling consistent interpretation across meetings.
- Helped embed the statistical approach into a practical workflow, grounded in validated data, so Bayesian results were usable and comparable across cohorts.
Statistical programming and reporting that connected safety, PK, and PD
- Delivered reproducible outputs to support ongoing review of patient status, adverse events, and emerging PK/PD information.
- Aligned reporting to protocol requirements and the review cadence, supporting continuity as the programme progressed.
- Provided integrated summaries that helped teams focus discussions on what mattered for the next cohort decision.

Successful Client Outcomes

With Quanticate’s support, the sponsor was able to run an adaptive Phase 1 dose-finding programme with stronger control over timeliness, data quality, and statistical implementation.

Review meetings were supported by cleaner, more consistent safety, laboratory, and PK/PD data.
The adaptive mCRM approach was operationalised with outputs that were aligned to decision points and easier to interpret.
Cohort transitions were supported by a coherent evidence package, improving confidence in the pathway toward RP2D selection for the next stage of development.

Phase 1 Dose-Escalation Oncology Trial: Supporting Adaptive Decision-Making for a Novel Combination Regimen