With the constant change in clinical trial technology, it can be a challenge for staff at every level to stay on top of the latest tools and trends. Anders Mortin, eClinical expert and cofounder of TriTiCon, discusses ways companies can harness ongoing training programs to prevent from falling behind.
OSP: Could you please share the ‘elevator presentation’ description of TriTiCon—who you are, what you do, key capabilities/service offerings, and what makes you stand out from the competition?
AM: We are an advisory, training, and knowledge-sharing company in clinical development, primarily in data management (DM) and clinical trial systems, but also in other areas of clinical development.
We advise and train in hands-on data management as well as managing data management, for example regarding organization, system, and sourcing strategies and oversight.
Naturally, we primarily work with the "newer” or “changing” areas like oversight and risk management, validation and privacy with cloud-based systems and new technology, but of course also with the fundamentals such as a good eCRF and ePRO design, SAE handling, and User Acceptance Testing.
We strive to have the combined subject matter knowledge and individual company understanding, alongside providing company-specific advice and help. Companies are not unique but they are different.
We are different in that we don’t want to do the work for our clients, like CROs or many consultancy companies do. We want to help the client with what they need to do, and thereby actually make ourselves redundant.
It might sound like a bad business idea, but we strongly believe in advising, knowledge-sharing, and education, and we believe there is plenty of work for who we want to be in that space.
We also believe that the business can and needs to be better at what it is doing. Knowledge-sharing is one of several required paths to get there. We don’t compete at data management; we compete on our products. Helping each other to do DM in a better way, not remaking each other’s mistakes or working redundantly, is a win-win.
OSP: Please share why ongoing training is important for life-sciences professionals, especially regarding data management.
AM: There is a lot to know in clinical development/life science; it is maybe not as complex as we would like to tell ourselves, but there is a lot to know. It is however difficult to “know it all”, and you actually don’t need to either since you don’t use it all at one time. What you need at any given time in your situation is ever-changing.
For example, given the indication or phase of the trial you are assigned to, you might not need to use ePRO (electronic patient-reported outcomes) and therefore you don’t need to know anything about it. There are plenty of other things to focus on. Your compound might then progress to the next phase and suddenly you need to manage ePRO in your trial: now you need the knowledge.
In addition, the world is changing, not least related to data management. DM is based on computer systems and is about collecting data, and we know how fast this area is changing: everything from your phone and other equipment, which is more or less automatically collecting data, to the cloud, to privacy laws. Regulatory expectations are also changing, expecting data management to use risk-based approaches, do more oversight of their vendors, and much more.
The pandemic gave the virtual trial concept a huge push forward, and now we are talking more and more about collecting data directly from the patients and healthcare institutions and labs, and not having a trial site as the main data collection channel. This raises a series of brand-new requirements, questions, and considerations.
OSP: Is it challenging for companies to keep up with data-management training, considering the rapid tech evolution common to the field?
AM: Yes, it is. Firstly, the rapid technology evolution, as you mention, and the new ways of collecting and managing high amounts of data pose a significant challenge. Data is information; information is knowledge; knowledge is money. Data is the new hyper currency. One point to remember is that DM is not only a rapid tech development area; it is also in a rapid transformation phase, as mentioned before.
Secondly, there is limited university education enabling one to be trained specifically as a clinical data manager. Without this solid foundation, it is challenging to pick up the new things and to deal with the changes that may occur whilst on the job. This is where problems arise.
There is generally not much training in the “how’s and why’s” of the new developments available. Many vendors claim that they know all the new areas, have the knowledge, and not only do they want to sell their technology or approach to you, but they also want to implement it for you. However, they often have limited training or advisory help in how to do it.
OSP: How do organizations typically approach training, from your perspective? What might most organizations do right, and where are they lacking or missing the mark?
AM: I think we generally do two things okay:
- The general basics regarding clinical development: the company products and medical aspects (steady-state) and GxP training. Although changing, it is not that rapid, and base training and yearly maintenance will usually suffice.
- The specific details of “this is how we do specific tasks in our company”. The subject matter expert (SME) training: “this is how you file a doc in this system, this is how we do validation (the docs and templates), this is our process for reconciling external data and this is the biology behind our compound”.
I think we fail badly on two key things:
- Understanding key and new concepts. The “why” and “how” for what we want to achieve, the guiding principles. For example, things such as oversight and risk management in a data management context.
- What do the latest updates to the ICH guidelines really mean and how do we map that to what is key in our company?
- What are we trying to achieve?
- How should we structure it to be efficient, effective, and compliant?
- What are the pros and cons with different sourcing models—why should I choose one over the other, and how do I manage the downsides with the model I have chosen?
- What are the key concepts and understanding points in ePRO? Leaving it all in the hands of the vendor is honestly not a good idea!
- The dominating training format is the old fashion “yearly bulk” or 2-day course for everyone. Honestly, this goes in and out. Not “if and when needed” and not in a “readily available format”. Look at how our kids learn today: Short, explanatory sessions, “when needed and as lookup/reference” using the one eLearning tool there is: YouTube.
My oldest boy is 19 and has grown up with “I haven’t got a clue, but I’ll just find out on YouTube”. Even my 8-year-old daughter knows where to learn stuff here and now. Well, for clinical trials and data management, you can’t find it all “out there” – yet! At TriTiCon we want to contribute to filling this gap and making training available in a more up-to-date format and up-to-date content.
OSP: Please share some information about TriTiCon’s training program—how does it generally work, and who are your training programs designed for?
AM: We see training as broad-spectrum and multifaceted. We have our training program, but we also share guides, articles, tools, and opinions, open and free. We also try to participate in focus groups, panels and give presentations amongst other things. Training is about conveying knowledge and there are many ways to do that.
The specific training program we have is a module-based program with six defined course packages (some modules are found across several courses due to their relevance):
- Data Management – The Basics
- Data Management – In-Depth
- Introduction to Today’s Data Management
- Introduction to eCOA / ePRO
- Managing Data Management
- Data Management for Non-Data Managers
So far, we have run these courses as both classroom and online, plus specific modules on request to different companies or groups. We are working on converting the entire program to the “modern way of learning”, i.e., self-service eLearning modules, packaged together with examples and exercises, but also with associated tools, templates, and best practices.
We anticipate that the classroom/online option will still be there, but we envisage a decrease in demand since the “on-demand” flexibility of eLearning is much more suitable in today’s working situation.
OSP: I’m especially interested in the “Data Management for non-Data Managers” program. Could you please tell us why it’s important for folks not handling data management on a regular basis to have a grasp of DM?
AM: Great question! It is not only that DM is “widened” and there is a need to know about new stuff. It is also that others, not working in the field of DM, need to know about DM.
I was at a meeting last week with a client who was looking to contract a new DM and programming vendor. Explaining the basics of data management to IT compliance, QA, vendor management, the clinical project manager, and legal is a necessity. They all need to understand the basics of data collection and handling to assess IT security and risk, GDPR considerations, legal terms, pricing negotiation, project management, and governance. New sourcing and collaboration models with more distributed services and tech, result in the DM work and DM data spreading out.
Another typical area is new data collection methods such as ePRO (not very new but increasingly used with high expectations for Health Economic and Quality of Life data), wearables, specialty labs, and biomarkers, etc. This melts in with processes like site qualification, CTA/IRB application, start-up timelines, and much more, which are handled by trial management, site management, medical safety, project management, QA, and vendor management. Therefore, all of these branches need to understand the key concepts in DM.
OSP: Do you have anything to add?
AM: I do think we have some major challenges currently in the industry; we are in a period of rapid change, and we do have large knowledge gaps. These knowledge gaps can lead to detrimental consequences.
Another challenge is that we totally over-size “solutions”, which is not a problem in itself, but as we all have limited resources and capacity, this inevitably comes with the consequence that other important things don’t get done. For example, I think we often totally overkill risk lists at the expense of identifying and truly managing the really important risks, and the details of so-called responsibility split at the expense of aligning expectations on ownership and drive.
The good news is that small pieces of knowledge can help. And they should be as close at hand as a one-hour eLearning module or just publicly available as shared information.
