Oncology Clinical Research Organization (CRO)

Highly complex datasets

Due to the large amount of data capture and analyze because of multiple data points and a large range of endpoints, as well as the range of different data sources in your oncology trial, datasets are often highly complex.

Quanticate statistical programmers are experienced in producing complex datasets. Having worked on a range of different oncology indications and also other Therapeutic Areas (TAs), we are used to producing datasets which have data from multiple sources, large volumes of data, and standardizing such data for clinical trial reporting.

Data Standardization

Your oncology data will likely come from multiple sources which you will have to be standardized to a single format for your clinical trial reporting and regulatory submission needs. Oncology studies require large efforts in data standardization, not only in converting non CDISC data into CDISC standards for regulatory submissions, but also of converting existing CDISC data into the same version across all sources and datasets.

As well as your data being standardized from different sources, you’re also likely to encounter data with multiple differences in terminology, make sure your adverse events, concomitant medication and medical coding data are consistent to your chosen industry recognized dictionaries. All of this requires additional mapping to CDISC and adds to the complexity and size of your oncology trial.

Quanticate has experience in managing many different data sources/vendors and combining all of these sources to create a consolidated database in standardized formats such as SDTMs and ADaMs. Having completed several CDISC mapping studies, our data experts are well revised in the latest CDISC guidelines and regulatory guidance. Our clinical data managers are well rehearsed in the most up-to-date medical dictionaries such as Meddra, WHODD and many more.

Analysis of Real World Data

Your oncology trial may not have a comparator treatment arm and therefore you may require your historic control data to come from a real-world setting. Ensure your study is utilizing Real World Data, giving you the best chance of proving your investigation hypothesis from the most efficient data types available.

Quanticate has vast experience in alternative trial types and has successfully supported large pharmaceutical customers in regulatory approvals with studies that used real world evidence as the majority of their trial data, which was an industry first.

Selecting the appropriate Oncology Study Designs

Ensure your oncology trial is set up for success from the start. Make sure your study design helps you select the right dose which gets the correct balance between therapeutic efficacy and toxicity during your phase 1 dose finding study. Take a modelling-based approach instead of the traditional 3 + 3 design to allow more flexibility in your trial design and the opportunity to consider a better trade-off between therapeutic efficacy and toxicity.

Quanticate can provide support on selecting the appropriate study design and sample size using simulation-based methods for phase 1 dose finding studies. Simulations enable us to provide sample size estimates for various scenarios to aide decision making. We can also provide support in running the models and providing the data/reports required for the decision making at the reviews at the end of each cohort.

Resourcing for Peaks and Troughs

Responding to peaks and troughs in your pipeline is vital for resource efficiency, idle workers can increase your drug development costs. Alternatively, not enough resource to handle the analysis required and you are at risk of failing to meet a regulatory submission deadline.

It is important to be able to respond to these variating requirements rapidly by ramping up or scaling down resources.

At Quanticate we offer flexible outsourcing solutions. Whether you require a whole functional team in an FSP model, or a single consultant on an ad hoc basis, we can quickly provide the right amount of resource to fit your requirements.

Efficacy endpoints

Ensure your efficacy endpoints are well defined in your trial so you that know how effective your treatment is when determining if cancers are improving or getting worse, quality of life improves and the impact on overall survival rates. All of these factors need to be analysed with the best clinical data methods and standardization.

Our team has worked on a range of oncology trials, with experience in different endpoints from RECIST criteria, confirmed and unconfirmed best overall response, disease control, best change in tumor size and progression free survival. We are well-versed in designing trials to ensure that, whatever your goal endpoints are, they are easy to measure to prove your treatments efficacy. We are skilled in the statistical programming required to analyze and report these endpoints and placing them into required CDISC standards for submission.