Could you provide a brief outline of what Quanticate is offering when it comes to data visualization?
Quanticate is offering a range of clinical trial visualizations to allow sponsors to get valuable, real-time insights into their trial data.
One of these are our automated TLFs (tables, listings, figures) visualizations for existing or new clinical data management customers, and the second form of visualizations is part of our Data Quality Oversight (DQO) service which improves data integrity and quality by detecting data anomalies and outliers via a centralized statistical monitoring package.
Could you provide an example of how data visualization could be used?
The automated TLFs visualizations tool enables tables, listings and figures to be generated before a database lock so that study managers can see insights into how the trial results are performing during the clinical data management stage. Traditionally these insights would be a result of a statistical analysis delivery provided by programmers once the database is locked or frozen at predetermined points. The TLF service is effectively a preview of the trial results before the actual validated data are produced. The automated TLFs facilitates another level of quality control where the customer has the opportunity to review their data for issues and have more transparency to the data cleaning process.
The use case for Data Quality Oversight (DQO) visualizations are for anyone who is seeking to improve data quality, integrity and data fitness during the study which in turn would increase their chance of a successful regulatory submission. They are a part of Quanticate’s new Regulatory Submission Review service offering. The visualization is instantaneous in that the technologies integrate into most electronic data capture (EDC) systems. With the use of these visualizations study teams can quickly identify data outliers and problematic sites so that data and sites can be investigated to improve the overall data fitness of a trial.
What are the industry trends driving the demand for data visualization?
We are seeing more technology solutions being embedded in clinical trial services and it is important to provide customers with the latest available technologies when these technologies add value. In the case of the TLF visualization solution, we are offering CDM customers an insight into how the results of their data may look earlier in the trial stages as traditionally without this technology they would be seeing these results at the end of a statistical programming stage.
As data are yet to be validated these are not final results and should not be used for final decisions until final TLFs are created at the statistical programming stage, but the tool can be used almost like a forecast into what the results might look like.
Regarding DQO visualizations, Quanticate saw the importance of the ICH E6 r2 addendum in that companies can embrace technologies and should look to improve data fitness and quality and these visualizations enable that. It also addresses a key reason for a failed regulatory submission.
In a recent analysis conducted by the FDA, 32% of submissions with study data had critical data conformance issues. Then only 50% of new NME/IND applications that passed the screening process for study data conformance are approved on first submissions by the FDA. There is a median delay of 435 days to approval following the first unsuccessful submission and 24% of the first-time submission failures include inconsistent study results either across endpoints or sites and studies. DQO visualizations discover issues that may not have been detected otherwise and via this improved data quality, and the documentation of correcting such issues, we support the greater likelihood of a successful submission.
Who will be most interested in data visualization?
Study managers, project managers and clinical development managers who are responsible for trials will be very keen on TLF visualization. TLFs allows teams to take a step back from the data and view the trial at an earlier stage, data visualizations are a potential predictive tool offering early insight into how a trial is panning out – something that was previously unavailable. The data of course will be in their raw, blinded state.
DQO will be of interest to heads of statistics and programming, regulatory affairs and heads of clinical development. It offers the ability to pinpoint problematic sites and equally well-run sites to make adjustments to monitoring eff orts as part of a risk-based approach to reduce CRA travel time and make savings for sponsors. Also, the ability to identify data anomalies and investigate these outliers improves data quality and fitness which as mentioned helps improve the chances of a successful regulatory approval.
Although the industry is still unsure on where the budget should lie for centralized statistical monitoring services, anyone who is involved in a trial passing a regulatory body and being a success should be interested in visualizations to improve data fitness and quality to achieve that regulatory approval.
What could the potential impact on trial design and outcomes be?
It’s unlikely the TLFs would necessarily impact trial design as insights are not meant to change the course of the study, for example, you couldn’t run an interim analysis as the data has not been validated or unblinded. However, seeing the visualizations creates a better prepared study team for the next stages of the study. The visualizations within DQO may have an impact on trial design as it enables a risk-based approach and a potential reduction in monitoring efforts. The processes would need to be defined within the trial protocol and monitoring plan as part of its design. Also, the visualization within DQO may enable decisions to be made sooner when improving data quality and a trial might be designed to be more flexible to interim analysis where studies are stopped earlier or adjustments made based on the results.
What will happen in this area in the future?
The industry is ever evolving and visualization of clinical data is becoming more and more readily available, clinical research organizations need to review their product portfolios and look at the technology stacks they have available to provide clients with additional value.
Whether it be partnerships with third party visualization suppliers or the development of visualizations in house, the demand for visualization capabilities to support clinical decisions and gain an understanding of trial data is ever growing. Both pharma and CROs need these capabilities to make informed decisions to improve data integrity and quality. It should be expected that CROs will further offer technology capabilities to remain competitive in the market place, but also their duty to provide better insights and service to maximize the success of clinical trials.
These technologies are being put in place as it is recognized by the FDA that reducing costs and improving efficiencies are important to both drug development companies and society. Data visualization is opening the door for trial sponsors to significantly improve data quality and prove drug efficacy sooner than ever before – saving time and money whilst improving patients’ lives.