COO’s Blog

May 2019

In this video blog, Tammy talks about how Centralized Monitoring won’t solve all your Quality Management issues, the changing role of the CRA because of RBM, the first readout of the E8 (R1) guidance and much more…

What’s new and exciting in the Sector?

April 15th 2019: We’re finally starting to get a readout from some of the regulatory agencies about their expectations around E6 (R2) and Risk-Based Monitoring. The FDA have recently released their draft Q&A document. We’re still getting a read-out on it, but on first glance it’s everything we’ve been saying around risk assessment being a requirement. It’s really trying to highlight what’s important in your trials and what could potentially go wrong.  It then goes on to give a little bit more guidance on your monitoring strategy when you’re not using a more traditional on-site monitoring strategy and when you’re using a centralized monitoring strategy. I think that’s new and exciting because everyone’s been looking for that information. I.e. without the need to have an inspection and the inspection finding, what is it that the agencies are really looking for, and this document helps.

Some of the industry bodies, like TransCelerate and the MCC, are going back and looking at Quality Tolerance Limits (QTLs). There’s some information in the E6 (R2) guidance that states that as part of risk reporting you should set QTLs and when you when you deviate from those limits you should report that in your clinical study report. Some companies are starting to look at “what is a QTL”?  For example, we had a great discussion at a recent event that we ran in Copenhagen with our partners Klifo.  People were saying that you can apply QTLs to anything, but it really comes down to how much risk are you willing to tolerate in your trial, what are you going to do when you breech those limits and what are the early warning signs? What this tells me is that the way that companies are choosing to define and implement is very different. Some are looking at it at a study level, looking at all clinical trial data for their studies. Others are looking at it really only being a subset of their data and the potential for your trial to fail if something were to go something drastically wrong with that data.

An example is if you have a survival study and you’re looking at long term survival and have a high drop-out rate, you wouldn’t be able to reach your survival endpoint. You’d therefore want to keep a track of that discontinuation rate because if you have a high number of patients dropping out early, you’ll never get to the 5-year end point. That’s something you’d probably want to measure at a KRI level site by site, but it’s also something you’re going to want to keep an eye on at the study level.

So there’s been a lot of discussion in industry about QTLs being a subset of data indicators that really could have a strong influence on whether your trial is successful. That leads to discussions on how we implement those QTLs at a study level. MCC are looking at applying process control limits and questions like how do you normalise to get the earliest warning signs?

TransCelerate have put some QTL definitions out based around absolutes but other industry bodies and others in the space are starting to challenge some of those definitions. They’re asking “are those the right way to do it and how do you normalize your data”?

Interestingly, we been doing that level since the concept of OPRA. Even before we started to talk about QTLs, and even before the ICH published their guidance paper, we applied it to all of our data in OPRA. We spent a significant amount of time looking at normalization to be able to get that early read-out and fair comparison of site-by-site. A key concept in OPRA is using funnel plots to enable us to normalize data and deal with small amounts of data, potentially at an earlier phase in the trial, and still have an equal comparison. It’s interesting to see that’s the direction of travel with QTLs and KRIs because we’ve been working in that way for the last 5 years. We believe that RBM in early-phase trials and small data sets will become a big topic for the sector and an important area where we feel we’re ahead of the curve (no funnel plot puns intended).

Removing resistance to RBM one protocol risk assessment at a time …

Jan 6th 2019:  In the last weeks of December I was heavily involved in facilitating protocol risk assessments for two very different prospects.  The first was a phase 1 paediatric study, where the risk assessment is being led by the sponsor and being initiated at the point of protocol synopsis.  The second was a phase II oncology study where the risk assessment is being led by the CRO partner and the study is just about to begin site initiations.

During the kick off for the phase 1 paediatric study, the process was met with open hostility from the clinical science function, but very much supported from the operations, project management and safety functions.  After setting out the process and guiding the team through some fascinating discussions where the clinical science function was very much at the centre, we wrapped up the meeting with a solid list of critical variables, good set of risks and excellent mitigating actions which included agreed changes and clarifications to the protocol, and an agreement to seek further expert guidance from the PK consultant.  On the surface this study seemed to be following standard of care processes, although dealing with a vulnerable population.  But when we started to work through the processes we were asking the site to perform, and the data being collected, the complexities became evident very quickly.  In spite of that the team came up with some excellent controls that could be put in place to simplify the processes, support the sites and set the study up for the best chance of success and generating good quality data.  We even received public acknowledgement from the clinical science function that it was a very worthwhile exercise and there were lots of notes to follow up on with the protocol.  A great result!  I left the meeting with a grin on my face and a spring in my step … A win for process and a win for the risk based approach!  I look forward to seeing how this team implements their study conduct risk controls.

In contrast to the first, the second risk assessment process was met with great enthusiasm. It’s the team’s first foray into the world of risk based monitoring and there was genuine excitement to be spending time discussing the study and how to approach the study conduct phase.  What I was really encouraged by was that there was cross functional representation.  The CRO provided medical input into the process and that was the focus, not the usual operational delivery metrics, such as first patient in, recruitment etc.  While there were some risks raised around patient population, the team did a great job in defining the critical variables and working methodically through the risks to those variables, focusing on subject well-being, ethical considerations and data quality. Items such as: the importance of treating emergent AEs; the impact on earliest date of clinical disease progression if AEs were not assessed and recorded accurately; impact of including subjects with poor life expectancy; and the complexities of DLTs, drug interruption and dose reductions.  The other fascinating point was that when it came to evaluating the detection of risk, the general assessment was that the risk would be easily identifiable by onsite monitoring.  However, when we started to pick into this, it became apparent that detecting this risk was reliant on all monitors picking up on all nuances without any room for error, and that if it was caught during monitoring, it would be patient by patient.  The implication of that is that by the time the monitor realised there was a trend, it could be too late.  During these discussions, the power of centralized data monitoring, looking at data per site and subject became obvious.  The team were able to see how KRIs, specifically designed to control the study risks, could be used as part of their monitoring strategy, together with targeted onsite monitoring.  The team were strong advocates of onsite monitoring, with targeted activities from the central monitoring, because the onsite monitoring supported the investment in the site relationship.  This is an integral and important part of their risk controls, together with the oversight of some of the processes which were going to be difficult to assess remotely for this study, such as drug accountability and supply management.  All very sound justification!

Being hands on with the study teams is such a valuable activity for me, it helps me to better understand the resistance points, how to demonstrate the importance of protocol risk assessment and the power of centralized monitoring to in early identification of errors and trends.  Hopefully this helps the organizations we work with to embrace new ways of working and realise the efficacy of these processes …  and it helps me bring back real world experience to our product development team.

RBM is not about reduced SDV, that may be one of many outcomes, but it’s not the intent or benefit of the process.  And no study is too small to apply a risk based approach, just consider the positive impact to our phase 1, 24 patient study …