Case of dose regimen optimization for paclitaxel

A US-based biotech company partnered with Excelra to identify whether the optimal paclitaxel dosing regimen for cancer is ‘QW’ (once per week dosing) or 'Q3W' (once every 3 weeks). This study demonstrates the value of clinical data management and bioinformatics solutions in addressing critical dose optimization challenges in oncology.

Overview

Determining the optimal dosing regimen for oncology therapies is critical for balancing treatment efficacy and patient safety. Paclitaxel, a widely used chemotherapeutic agent, can be administered using different dosing schedules such as weekly dosing (QW) or once every three weeks (Q3W). Understanding which regimen provides the best therapeutic outcome requires extensive analysis of clinical trial data.

Excelra partnered with a US-based biotech company to identify the optimal paclitaxel dosing regimen by analyzing clinical trial outcomes across multiple studies. By leveraging advanced Clinical Data Services, Bioinformatics Solutions, and Scientific Informatics, Excelra developed a structured database of clinical outcomes to support dose regimen optimization in oncology.

Our client

Our client

The client is a US-based biotechnology company focused on improving cancer treatment outcomes. Their research team aimed to determine whether the paclitaxel dosing schedule of QW (once weekly) or Q3W (once every three weeks) offers better safety and efficacy in clinical practice.

Client’s challenge

Client’s challenge

Optimizing chemotherapy dosing regimens requires comprehensive analysis of clinical evidence across multiple studies.

The client faced several challenges:

  • Large volumes of published clinical trial data on paclitaxel dosing
  • Variability in treatment regimens and patient populations
  • Difficulty comparing safety and efficacy outcomes across trials
  • Need for a structured dataset suitable for quantitative analysis
  • Requirement for evidence-based insights to guide oncology dosing strategies

To address these challenges, the client required a model-based meta-analysis framework capable of integrating multiple clinical datasets.

Client’s goals

Client’s goals

The client sought to:

  • Identify the optimal paclitaxel dosing regimen (QW vs Q3W)
  • Quantify relationships between dose schedules and clinical outcomes
  • Build a comprehensive clinical trial database for paclitaxel monotherapy
  • Analyze safety and efficacy endpoints across oncology indications
  • Support clinical decision-making using data-driven insights

Our approach

Literature review using PICOS framework

Excelra used the PICOS methodology (Population, Intervention, Comparator, Outcomes, Study Design) to scope and review relevant scientific literature related to paclitaxel dosing regimens.

This structured approach enabled the identification of relevant clinical trials across multiple oncology indications.

Clinical outcome data curation

Excelra curated clinical trials outcome data from multiple publications, capturing summary-level safety and efficacy endpoints for paclitaxel monotherapy.

The curated dataset included key parameters such as:

  • Patient population and cancer indication
  • Treatment intervention and dosing regimen
  • Comparator regimens
  • Clinical efficacy endpoints
  • Safety outcomes
  • Study design and sample size

These structured datasets enabled quantitative comparison of paclitaxel dosing strategies.

Model-Based Meta-Analysis

Using the curated database, Excelra conducted model-based meta-analysis (MBMA) to quantify relationships between paclitaxel dose regimens and treatment outcomes.

MBMA integrates multiple clinical studies to generate statistically robust insights into dose-response relationships, enabling evidence-based treatment optimization.

This analytical approach aligns with modern data-driven drug development strategies, similar to those discussed in data curation for model-based meta-analysis.

Data visualization and insights

Excelra used its BioVisualizer platform along with Visualization Services to translate curated clinical datasets into actionable insights.

Interactive visualizations enabled the client to easily compare safety and efficacy outcomes across different paclitaxel dosing regimens.

Case of dose regimen optimization for paclitaxel

Conclusion

Excelra’s integration of clinical data curation, model-based meta-analysis, and visualization tools enabled the client to evaluate paclitaxel dosing strategies using evidence from multiple clinical studies. By building a comprehensive database of safety and efficacy outcomes, Excelra helped the client identify optimal dosing regimens and support oncology treatment decision-making.

For more insights into Excelra’s expertise in biomedical data analysis and clinical research, explore additional case studies or learn more about precision medicine solutions.