Chasing Your Data…and Winning the Race!

Chasing Your Data…and Winning the Race!
Lessons Learned from a Virtual Town Hall held on November 20, 2020

As an industry, we produce data. Lots of it. It is inherent to what we do and clearly necessary for bringing innovative therapies to patients. Whether it is monitoring patient data for safety, or operational data for oversight purposes, the pandemic has escalated data accessibility to a top strategic priority for companies. Increasingly, Sponsors are positioning themselves to take more ownership of their data and processes, further questioning the need for relying on a third-party middleman.

Halloran’s November Town Hall focused on how Sponsors have adopted new tools and processes to provide better and more rapid access to critically important operational and patient data. The panel members discussed important steps to utilize new tools and processes, including understanding where to start, selecting technology and building internal capability, and implementing those processes to operate better in an increasingly data-rich environment.

What is Your Why?

Data has always been critical for decision making, and as the volume of data (and data sources) continues to increase, new platforms and technology solutions are emerging that can help sponsors better harness the power their data holds. Prior to embarking on any specific data platform or solution, it is important to clearly define your problem statement and what you want to achieve. This is your why. After framing what you are trying to solve for, you will be better informed if you have the internal capability and infrastructure available vs. pursuing an off-the-shelf solution.

During the Halloran Town Hall, only 31% of attendees indicated that they were satisfied with the level of service they currently receive from their vendors around access to trial data (both patient and operational). This is an excellent “why”.

The Benefits of Data Accessibility

  1. Agility – Access to your own data and analytics quickly to enable decision making in real time.
  • Improved access to data allows for time-sensitive decisions to be made efficiently and effectively and for questions to be answered derived from a single source of truth (vs. multiple and often conflicting data sources). In a complex and highly regulated environment where turnaround times are critical to ensure patient safety, this value cannot be underestimated.
    • This allows for ease in overseeing day-to-day activities and multiple ways to look at the data depending on the task at hand.
  • For larger or even Master Trials, quick access to data can facilitate decisions regarding keeping, expanding, removing, and adding assets in a timely manner
  • Aggregating and visualizing data from multiple sources allows for executives and study teams to digest information more quickly and for the various stakeholders

 

  1. Scalability - while maintaining a single source of truth
  • It is difficult and time consuming to approach individual people to pull together PowerPoint presentations or Excel spreadsheets. The scalability of new data analytics solutions allows for one common platform approach to answer questions and explore use cases.
    • It allows for the ability to aggregate and visualize data sources when running multiple trials, enabling more effective program-wide decision making
    • The centralized aspect can also improve patient monitoring and study oversight
  • Using a platform approach, data can be entered once into any single existing source (EDC, CTMS, even Excel) and the data platform will map, aggregate and visualize the information for better end-user consumption. The important value proposition here is that this frees up substantially more time for data consumers to spend on examining the strategic insights from the data vs. the operational and non-value add compilation and reporting activities.
  • Data solutions provide both a vertical and lateral view of the data. This enables you to thoroughly explore your datasets for hidden patterns.
    • Lateral view allows teams to compare data across studies and make decisions based upon that. For example, one could look at site performance from another trial and use that to inform their decision about site selection and management on another trial.
    • Vertical view allows teams to drill down information within a single study. For example, one could look at a specific patient after having identified an issue at the site or visit level for further monitoring and investigation.

 

  1. Quality – perhaps the most important value proposition.
  • Inherent to many of the benefits above is that these platforms better curate your data from a quality perspective by:
    • Automation. Like it or not, humans make mistakes. Yes, we have many redeeming qualities, but aggregating and analyzing large amounts of data is not one of them. Whenever a process can be automated, the higher quality that process will have. Automation eliminates human errors around compiling conditionally formatted spreadsheets or manual PowerPoint dashboards. All of us have worked in Excel and understand how easy it is to inadvertently remove a cell’s contents or lose track of a hidden row or column or know how best to format the data to provide the right insights to enable decision-making. Let’s stick with what we are good at – the strategic insights piece and leave data integration and automation to the CPU.
    • Single source of truth. While mentioned above, it is also worth mentioning it under quality as well. This is incredibly important to ensure there is no redundancy in reporting critical data.
    • Standards. While standards can certainly exist in the absence of technology, a data platform best enables them. Standard definitions are maintained (FPI anyone?) and consistent reporting is ensured.
    • Visibility/Transparency. Lastly, the more visible our warts are, the more likely we are to control for them. The mere presence (or absence) of data in your visualizations expose existing data quality issues for everyone to see. Negative cycle times, missing planned dates and outliers are now visible whereas they formerly laid dormant in your CTMS.

What is Your How?

Implementing and Maintaining the Data Solution

So you have identified your “why” - now you need to tackle your “how”. Below are some considerations to keep in mind when implementing a data platform or technology solution.

 

Change Management

  • Start here. Change management doesn’t start after the implementation – it should be the first thing you do once your strategy is defined.
  • Users need to understand the need for a solution and how it will impact them. Will their role change? What existing tools will be replaced?
  • Incorporate resources like centralized communication hubs and simplified trainings to ensure all relevant stakeholders are informed.
  • Successful change management practices include senior leadership support, consistent messaging, ongoing refinement of information and weekly communication.
  • Involve your vendors in the change management process early – more on this later…

 

Pilots and Use Cases

  • Keep it simple at first. A pilot or well-vetted use case should be part of a short-term goal in implementation.
  • Trying to do to many things at once will trip up the implementation, making it more difficult to completely adopt.
  • Consider both short-term and long-term goals and keep them in mind as you adopt a data solution. Then, if your use case allows for it, do not try to customize too much immediately. Keep it simple in the beginning and provide more customizations over time for a smoother transition.
  • With a multitude of data and multiple data sources, there are many dashboards that can be generated, some of which may only have minor relevance to your biggest needs. It may sound simple, but make sure you are only looking at the dashboards that are useful to you and your team. You will want to focus on the ones that provide you relevant insights and answer important questions.
  • Consider the consumer of the information and present them with dashboards that are helpful and digestible. For example, an executive view should only focus on the key 4 or 5 parameters that leadership prioritizes in a single page, whereas a trial manager will be interested in more granular, trial-specific information.

Customization

  • Be wary of customizing too quickly – keeping it simple at first enables you to adjust to the process.
  • An off-the-shelf data solution may satisfy 90% of your requirements initially. More often than not, that may be more than enough to get you started with implementation. Again, customization can be a longer-term goal once change management and adoption is addressed. Most data solution providers have dozens of turnkey visualizations and algorithms, such as that offered by Saama Technologies, Inc. – make sure you review these first before you start providing them with customizations.
  • Understand any internal support requirements. This looks quite different in a small biotechnology company operating in a fully outsourced model and a large pharmaceutical company with a well-staffed technology support function.
  • Leverage your technology vendor’s expertise. They have done this before and understand different companies have different priorities. The data solution provider can work with a sponsor company to build new data streams, and enhance existing ones to better serve a sponsor, as it learns more about its own operations and needs.

Partners and Vendors

  • Balance your partnerships with your CROs, data solution vendor, and other vendors. Your CRO and other vendors will be the source of data you will integrate into your data solution platform, and that raw data isn’t always easy to obtain.
  • Be transparent with your vendors – since they hold the key to the data sources you require access to, they need to be informed about what you need from them and how it will impact their current business process with you.
  • Engage your vendors in discussions around data integrations. Discuss your data sources and the frequency at which you would like data provided.
  • Understand that an integration or API may not be needed for every data source – a flat file or csv export may suffice for data that does not refresh frequently
  • Expect access to the CTMS to take the longest. Plan accordingly.
  • Make sure you discuss with your vendors what you are looking for and determine what they are willing to provide. Find out if there are fees associated with getting any of the data. Use what you learn in these conversations to inform your next steps.

Winning the Race

Ten months after the first confirmed case of COVID-19 in the United States, the virus continues to impact our industry. We have been forced to be creative and to tackle new challenges with creative solutions. We have modified the way we construct trials, conduct trials, and collect data…and are marshalling toward the next frontier: aggregating, organizing, and visualizing the data.

Winning the data race is really about shortening the course and accessing your data sooner in an informative way. To do this, we must look to new technologies and data solutions that enable us to efficiently consume and digest our data better. The world, including the microcosm of a clinical trial, is ever evolving, and maybe more rapidly than ever. Luckily, there are new automated solutions to help us keep up.

Please reach out to us if we can help in any way or would like to be included in any of our upcoming town halls.