Oncology is a main area of focus for many pharmaceutical and biotechnology companies around the world. The facts about cancer are startling: cancer claims over 7 million lives each year and the number continues to grow. It is no wonder why drug development companies are focusing on this complicated therapeutic area which has over 450 indications.
CROS NT examines the implications of the challenges companies face in developing oncology therapies and how implementing good study designs can decrease the probability of failure in early phases.
We’ve already discussed what makes oncology a unique therapeutic area:
- Long timelines to reach clinical endpoints
- The use of treatment combinations
- The large number of partially related diseases
- The importance of disease sub-types and/or genotypes
- Regimen modifications during treatment
- The high impact of the disease on patient life
- The high costs of treatment
- Slow Recruitment
What are the implications of these unique traits?
- Study Design in early phases is extremely important: safety and efficacy, ethical considerations and long patient recruitment need to be take into account.
- Patient Recruitment and Retention is challenging: biostatisticians should be involved in the beginning to define protocol requirements.
- There will be vast amounts of data to analyze, including SAE safety data, and therefore biostatisticians will need access to real-time data in order to make go/no-go decisions
- Investing time in the proper design set-up of an oncology trial in the early phases is essential to increase success rates in later phases.
In Phase I oncology studies, the drug is tested for safety of drug combinations are tested to recommend dosage for Phase II. The cohort design of a Phase I trial tests for drug safety as well as efficacy. Phase I considerations for oncology include protocol planning, analysis of EDC solutions for real time data collection and centralizing clinical data in order to have access to the same biostatistician throughout the study and one central database.
Good Practice Designs: Involving the Biostatistician
The Statistical Analysis Plan for oncology trials, especially for Phase I trials, is extremely important in terms of determining trial design, sample size, endpoints and determining inclusion/exclusion criteria. The biostatistician should be involved in the beginning of an oncology study to consult on:
- Protocol Development
- Trial Design
- Defining the Study Objectives and appropriate design
- Defining the statistical method
- Defining hypothesis and testing procedures
Good Practice Designs can speed up the planning phase; a team with previous oncology experience will enable a reduction of time from the study synopsis to first patient in the study because it defines adequate target criteria, interim analyses and specifies the most efficient statistical method for analysis.
Standardization means establishing uniform technical specifications, criteria, methods, processes or practices, adverse effects documentation, QoL questionnaires and follow up information. Using these specific forms, it is possible to improve quality and reduce project costs through a validated database structure, validated SDTM and ADaM formats or ePRO and EDC solutions.
Establishing criteria, methods, processes and practices for presenting results can optimize the output. Good practice designs in early phase oncology studies can reduce the risk of project failure and advance development to later phases where statisticians can revert to adaptive trial design to optimize late phase study outcomes.
CROS NT excels in the statistical design and analysis of oncology trials from Phase I-IV including Adaptive Trial Designs. For more information on how to optimize the outcome of your oncology trials and consult our expert biostatisticians, please contact us.