Have you ever wondered how project management and collaboration between statisticians and clinical operations professionals impact clinical trials?
What challenges do they face, and how can they ensure high-quality, timely, and budget-conscious results?
Today, I’m thrilled to have Jessica Cordes with us. Jessica brings over 15 years of experience in clinical operations, particularly in oncology and cell and gene therapy. She founded her own consulting company, helping small to mid-sized companies with their clinical trial needs, and she launched a digital training academy to share her extensive knowledge.
In this episode, we dive into the intricacies of project management and collaboration, exploring how effective communication and detailed planning can significantly enhance the synergy between these crucial functions in the clinical research landscape. Tune in to gain valuable insights!
Key Points:
- Introduction to Jessica
- Project management
- Collaboration
- Clinical operations
- Quality assurance
- Timeliness
- Budget management
- Effective communication
- Functional synergy
- Overcoming challenges
- Best practices
These insights are crucial for anyone involved in clinical research aiming to achieve high-quality, timely, and budget-conscious results.
If you found this episode helpful, please share it with colleagues and friends who can benefit from these strategies and insights. Together, we can enhance the efficiency and effectiveness of clinical trials across the industry.
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Jessica Cordes
Senior Consultant Clinical Operations
She possesses extensive experience as a department head in establishing a unified and globally distributed Clinical Operations team, consisting of both office-based as well as remote staff. Her initiatives focused on refining Clinical Operations procedures to enhance GCP compliance, increase operational efficiency, accommodate ATMP clinical trials, and prepare for late-stage clinical trials.
In her capacity as a Clinical Project Manager, she undertook responsibilities such as site and service provider selection, ensuring timely operational setup, and effective management of the clinical trial budget.
She collaborated with interdisciplinary teams to conceptualize clinical trials, strategize clinical trial processes and documentation, oversee early-phase and late-stage clinical trials, and conclude clinical trials.
Transcript
Project Management And Collaborations With Statisticians
[00:00:00] Alexander: Welcome to another episode of the effective statistician. And today I’m super happy to have Jessica on the show because she represents a function that both statisticians work a lot with and yeah, sometimes that’s some tension there as [00:00:20] well. So Jessica, maybe you can introduce yourself.
[00:00:25] Jessica: Thank you for having me, Alexander. I’m happy to join this episode. Yeah, actually I’m Jessica Cordes. I’ve been working in clinical operations for more than 15 years nowadays, becoming older, by the way. Yeah, I’m [00:00:40] mainly on my way in oncology as well as cell and gene therapy. Starting from day zero with a Clinical trial design where we have the first connection to the biostatistician until we are writing the Clinical study report.
[00:00:57] So all the operational [00:01:00] feasibility and the operational planning and conduct is something I’m very experienced with.
[00:01:05] Alexander: Yeah, and you actually run your own company now.
[00:01:09] Jessica: That’s that’s true. For a few months I’ve been running my own company. Being a consultant for especially smaller companies, but also mid sized [00:01:20] companies, whenever they have a resource or expertise demand, I can help.
[00:01:26] And by the way, I launched a training academy as well with the first digital training course. So I’m trying to share my knowledge in the digital world as well.
[00:01:37] Alexander: Awesome. And we’ll link to your [00:01:40] homepage and your LinkedIn profile in the show notes. So that’s, that’s really, really great. So clinical operations.
[00:01:48] So for those that I’m maybe a little bit more new to the industry and haven’t been so much in touch with clinical operations people yet. [00:02:00] What do clinical operations actually do?
[00:02:04] Jessica: Yeah, that’s a good question. I often get to be on. So it’s really starting To think about the Clinical Trial design and think about how to plan your Clinical Trial in a [00:02:20] way that it’s operational feasible for the physicians, for the patients, for the service provider being involved, and obviously for the sponsor as well.
[00:02:30] So here, the first aspect is already trying to be smart. and have some innovative approaches to [00:02:40] balance the quality you need to come up with, but at the same time, the timelines you need to achieve your goals and the budget you need to fulfill all the tasks required. So it’s really starting from protocol writing.
[00:02:55] We have some impact there. If you need service provider, the service [00:03:00] provider selection all the functional plans about clinic and monitoring, maybe even data management, sometimes we are covering that as well. Yeah. How to select your physicians, your sites where to find your patients. Here again, patient recruitment, [00:03:20] identification, but the whole procedure at the site is something clinical operations is thinking about.
[00:03:26] And we are trying to ensure that the contractual basis is there. The documents are available when it comes to how do we envision that the clinic trial is [00:03:40] conducted and at the same time we are rolling out the training to all the involved parties to ensure that they are conducting the trial according to our plan.
[00:03:51] Alexander: What has been your work experience working with statisticians been up to now?
[00:03:59] Jessica: Oh, [00:04:00] very mixed. Okay. I think there is always some kind of stereotype in a specific functional area. And this is really without value, right? It’s really like there is a specific character, and I believe you need a specific character to work in a [00:04:20] specific field.
[00:04:21] So in clinical operations as well, and I assume in biostatistician world, It’s the same. You need to be very picky and think about details. This is something where I, I’m very hands on what were the statistical colleagues, because [00:04:40] the mindset, how to approach topics, questions, challenges is very detailed and thought through.
[00:04:49] This is something where I think we have a good fit. On the other hand, my experiences in the biostatistics [00:05:00] world, you have a completely different language, right? And so do we have a complete different language in clinical operations. And this is something you need to be aware. So we had some hurdles in the beginning while [00:05:20] interacting and connecting to each other, because everybody was more like in a silo thinking like, okay, I’m doing my tasks I’m, I’m assigned to do, and then I push the result to you.
[00:05:32] And then you can continue without understanding each other and the rational behind the [00:05:40] outcome we see. I find it pretty difficult because you, you have, you’re losing energy.
[00:05:47] Alexander: You
[00:05:48] Jessica: are not completely understanding each other. So I’m a fan of, of a robust training for clinical operations. They need to be aware what are the main [00:06:00] drivers for specific statistical considerations.
[00:06:03] Oh gosh, we are not statistics, right? So this is really heavy, heavy food for us. But the, the basic concepts, this is something we should understand and why we are coming up with a statistical method or some, some approach, right? [00:06:20] Because biostatisticians are giving us the number of. patients we need to recruit, the number of events we need to look for.
[00:06:29] And this is impacting our site feasibility, site selection our monitoring approach, how closely we are monitoring the data [00:06:40] we are capturing. So it’s also impacting data management. And this is This brought us always to robot spaces when we started to talk to each other and try to understand the other language and understand the vocabulary the other side is using because only then you are aligned and you have a [00:07:00] good understanding.
[00:07:01] Yeah, equal starting point.
[00:07:04] Alexander: Yeah, I completely agree. It’s, it’s very, very important to understand what’s important for the other person. Yeah. What are, for example, crucial constraints that you have? Okay. See understand, create a common [00:07:20] goal that you want to reach. Yeah. If you talk about quality, yeah, that means something very, very different to different people.
[00:07:30] Yeah. And so for example, if you think about quality from from your point of view, what does a high quality [00:07:40] study actually means to you?
[00:07:43] Jessica: For me, I’m really driven by GCP, so quality means I can ensure the patient is safe. Data are reliable. And this is the most portion, right? Because it’s interconnected to each other.
[00:07:58] Data [00:08:00] reliability, just two words, but meaning so much. It’s really starting from being smart, how to collect the data, whether to automate any imports and, Minimize the manual entry by that you can minimize the error and error is meaning [00:08:20] something else than the statistical error here, right? Then you need to review those data, the clinical monitoring activities, but also the medical monitoring activities, the drug safety activities, so safety monitoring.
[00:08:36] So it’s such an interdisciplinary field [00:08:40] that everybody needs to review data from a different angle. that you need to be very smart and very clear how the data are captured, how data flow is going, who is receiving which information, whether you check it, are there any QC [00:09:00] steps or is it possible to get automated?
[00:09:03] Are you importing data? You know, so I, I had a very very emotional discussion about is it worth to import ECF data into your safety database?
[00:09:17] Alexander: Yeah. Yeah. These kind of [00:09:20] connections. These
[00:09:20] Jessica: kind of questions we have, right. And, you know, I, I got a statement that, well, I don’t care which data are captured in your ECF because the Bible is the safety database.
[00:09:33] And I said, I can’t agree to this. And you know, this person [00:09:40] was very commercially driven. So completely understood where this person was coming from, but even with a commercial product and you’re not, reconciling your data between the ECF and the safety database, you might miss some serious events.
[00:09:58] Alexander: Yeah. Or kind [00:10:00] of misinterpreted. Yeah.
[00:10:01] Jessica: Even if they might have not been classified as serious, right. Then you you’re completely blind spotters.
[00:10:09] Alexander: Yeah.
[00:10:09] Jessica: Think about the statistical analyzes at the end, right? So you need to ensure that you have a very good quality because it’s for your own decision [00:10:20] making process in the end as a sponsor.
[00:10:22] Alexander: Yeah, but also for patients and physicians out there. Yeah. One of the things that really helps a lot if you work on in a clinical trial as a statistician is understanding how data happens. Yeah. [00:10:40] So I can highly recommend that you speak with your clinical operations person and ask whether you can attend one of the site monitorics.
[00:10:53] Yeah. Possibly there’s a site close to you, yeah, which is monitored and where you can [00:11:00] have a, you know, just watch what they are doing. What are the discussions there? What are kind of the typical questions? How’s the data entry system looking from there? And how’s the, you know, engagement with the patients going?
[00:11:16] These kind of things will help you a lot [00:11:20] to understand how data happens, where the challenges are, what kind of things that you have to thought about could be easy or not that easy. Yeah. And that helps you a lot about seeing kind of how we can streamline studies [00:11:40] and where most of the effort is coming from.
[00:11:43] Jessica: That’s a very interesting approach. I completely agree because you get a better picture what’s happening at the site and you can feel the administrative burden for the site when being there, right? This is so much [00:12:00] underestimated. So coming back to the operation of feasibility, which is the core business for clinical operations.
[00:12:06] Unfortunately, often We are not really heard in regards to site burden and administrative burden. And I would love a lot of functions to go this way. And I’m [00:12:20] now undergoing this kind of training, attending a site visit, sitting there, watching, learning, and seeing how, how much stress the site has, especially during treatment visits, right?
[00:12:36] Or screening visits where you have so many assessments. [00:12:40] So it’s not easy to collect all this data.
[00:12:44] Alexander: Yeah.
[00:12:44] Jessica: I agree.
[00:12:45] Alexander: In terms of feasibility, what are kind of key things that you look into when you speak about trial feasibility?
[00:12:57] Jessica: Well, the key things are coming from, from GCP, [00:13:00] right? Is the investigator experienced has he or she enough knowledge about the indication, the product type is enough.
[00:13:09] stuff available, are the facilities okay? So this is the general stuff you’re always looking to because it’s mandated by GCP. [00:13:20] In addition to that, what I learned, especially when I worked for cell and gene therapy clinic at Rides, is the the cultural component, the communication component. So really worth during the site feasibility is already to create an understanding of [00:13:40] how the site is communicating to potential clinical trial participants.
[00:13:46] Alexander: Okay.
[00:13:47] Jessica: To understand the information flow, the communication flow, how this is working, because this might be a little bit site specific. So how is a site [00:14:00] identifying potential patients and which steps are required and how the patient is routed through the screening process until the site is achieving to enroll the patient. Because the main challenge we all see in clinic, it tries to be honest. [00:14:20] Yeah. So this is the operational portion and the other portion might be more the statistical one, right? So you guys, you are telling us we need a hundred patients, right? And then it’s on us to say, okay, how many sites do I need to enroll these hundred patients?
[00:14:39] And [00:14:40] especially in cell and gene therapy, we are talking about 70 to 95 percent screen failure rate. Right. Right. Right.
[00:14:46] Alexander: Yeah,
[00:14:47] Jessica: this is massive, right? And then you can open up a lot of sites, but you’re burning your resources because it’s an effort and you’re also burning your budget. So you need to try a [00:15:00] little bit smart and selecting your sites to find the right sites.
[00:15:04] And the same is true to find the right patients, right? So understanding the whole process step by step is creating you a good basis to see whether. Online patient recruitment can help you create a [00:15:20] patient enrollment plan, how to find the patients, but also the right patients to come up with the required number. And in addition to that, even the communication between the departments within the site. If you think about hospitals, you [00:15:40] might have one main department conducting your clinical trial, but maybe four, five, seven other departments being involved, and they are impacting your data reliability in the end, they are capturing data for you.
[00:15:56] And, you know, it’s especially in early [00:16:00] clinical trials. The BICE statistician is making The assumptions based on the data you’re getting, and it’s on us to ensure that you get high quality data, because only then you are able to make the statistical analysis in a good way. Think about those escalations, [00:16:20] very early clinical trials, or even the modern designs with Bayesian statistics, where you’re rolling up your doughs.
[00:16:29] By patient even right or you want to enrich treatment arms based on the data you see. So those designs are more and more [00:16:40] mandating the clinical operations activities activities being adequate and on time.
[00:16:47] Alexander: Yeah. With an
[00:16:47] Jessica: ongoing activity supporting the biostatistics because you are on the way and continuously analyzing and adapting the clinical trial design, right?
[00:16:58] So I [00:17:00] believe in future with the modern designs, the biostatisticians and the clinical operations professionals with all the different functions, we are even living closer to each other than we are used to already.
[00:17:14] Alexander: Absolutely, yes. The more adaptive the design, yeah, [00:17:20] the more closer you need to work with clinical operations.
[00:17:23] Because then you need to have, you know, all your data cleaned in time. You need to have speak about assumptions much more. You need to talk about feasibility much more. You need to talk about kind of, you know, All kind of different things. Yeah. Having the right [00:17:40] doses at the right sites. There’s so many kind of things that you might not think about as a statistician.
[00:17:50] Yeah. That makes it really, really hard on the clinical operation side. So speak through these, you know, [00:18:00] what does that if we’d Make that assumption or if we have this design feature, what does that mean from a clinical operations point of view is really, really important. You mentioned screen failures and that’s a really, really big topic.
[00:18:19] [00:18:20] What are your what, what’s your experience in terms of statistical input that can help to. improves this kind of screen failure problem?
[00:18:32] Jessica: So I have a lot of experience in smaller biotech companies. And I need to admit, [00:18:40] I never received any feedback. Because the biostatistician colleague never thought probably that there is an impact beside the general clinical trial design, right? So we were only given the numbers, right? So [00:19:00] we got some medical assumptions around the discontinued patients.
[00:19:07] From the biostatisticians, we got the sample size or number of events. But that’s it.
[00:19:15] Alexander: Yeah, because Tell
[00:19:17] Jessica: me more!
[00:19:17] Alexander: Yeah, there can definitely be [00:19:20] much more interactions on all these different steps, yeah? If you think about what are the main drivers for screen failures, yeah? How important are they? What Is the, what are the diagnostic tools that you use, say, for screen [00:19:40] failures?
[00:19:40] Are these things that you can make easier, yeah? Is there maybe some kind of two step approach? Instead of doing directly kind of a lab test, yeah, that gives you absolute clarity of whether the patient is can be enrolled and maybe that lab test. [00:20:00] I don’t know. It takes a week. Maybe there’s some other tests that you can directly kind of do so you can screen out easier.
[00:20:10] Yeah. Things like that. The other point is what you mentioned is discontinuation of, of treatment. Yeah. Especially with [00:20:20] thinking about estimates managing how you capture data after patients have discontinued treatment is a really, really important thing. Yeah. I have seen lots of, lots of miscommunications there where people think like discontinuation means discontinuation from the [00:20:40] study, but actually discontinuation from treatment does not necessarily imply discontinuation from the study.
[00:20:46] Yeah. Yeah. These things play a big role and. Yeah, what do we offer to patients once they kind of discontinue the, you know, the blinded treatment? [00:21:00] also can have a major impact on recruitment, discontinuation rates, all these kinds of different things. If you have compliance problems, yeah, compliance and not so much in GCP for compliance, but kind of adherence to treatments and things like that.
[00:21:17] Yeah. Or staying in the [00:21:20] study because of It’s a burden of the study. Yeah. What happens if patients move? Yeah. From one side to the other. Yeah. And my best story with working with clinical operations was actually my first phase three [00:21:40] studies that I worked in. Once got an email from from one of the countries that were included in the study and asked what they do with patients when they switch sites and do they keep their patient ID kind of [00:22:00] thinking.
[00:22:01] That’s kind of a weird, weird question. And I got on the phone with the respective person and that person explained, well, that patient got randomized in that site, but was randomized to the comparator. [00:22:20] And because it was an open study, that patient then said, no, I don’t want so. the comparator, I want the active, yeah?
[00:22:27] And so discontinued from the study on that side, moved to the next side and wanted to be randomized again. And just because of the [00:22:40] close relationship, we could identify this challenge and get that resolved. Yeah. And of course that patient wasn’t randomized. Yeah.
[00:22:52] Jessica: Yeah. That’s a very good example where you can see that risk management in the very, very early beginning [00:23:00] of your clinical trial is already required and is also included, including all functional area experts.
[00:23:09] including the biostatistician, right? So this is something with an open label clinical trial, it’s easy to detect that you might have ethical issues because the [00:23:20] patient obviously wants to get the, the verum, right? Yeah. And sometimes you can already mitigate in your clinical trial design, right? So I was often asked once I finalized the protocol, then I started risk management.
[00:23:36] I said, no, you should start before because [00:23:40] the risk mitigations in best case can influence your clinical trial design and your protocol. If you finalize that before no chance, then you have the extra effort of an amendment.
[00:23:52] Alexander: Yeah. Yeah. Yeah. And risk management is a really, really important [00:24:00] topic. I actually have another episode with another chess by the way earlier in in this podcast.
[00:24:06] So if you just scroll back as a listener, you can easily find that as well. Now let’s talk a little bit more about amendments. Very often an amendment from a statistical point of [00:24:20] view doesn’t create a lot of work for us. What does an amendment mean from a clinical operations point of view?
[00:24:29] Jessica: Probably I can give a harsh statement saying we are the ones suffering the most. So it’s, it really depends on the amendment, right? But I worked through [00:24:40] some adaptive clinical try designs just recently and you know, you’re, you’re some kind of shocked. Because you’re changing figures and you are adapting the treatment algorithm, the assignment, the randomization, etc. But for clinical operations, it’s always like we [00:25:00] need to update all the functional plans.
[00:25:02] We need to check whether the documentation like checklist forms, etc. need to be updated. We need to roll out everything with a training to the sites, but also to the vendors, to the sponsor team. And then we need to follow up that they are using the new [00:25:20] version and not the latest version before. Right.
[00:25:23] So for us, it’s so much of an administrative burden. It’s not easy to go with.
[00:25:30] Alexander: Yeah, amendments drive a lot of work and incur a lot of costs. So minimizing [00:25:40] amendments is really, really important. Yeah, so that’s why that’s why also checking for feasibility is so important because very often amendments come because there’s problems with recruitment.
[00:25:54] Yeah. Yeah. Yeah, there’s problems with visibility and that wasn’t kind of thought [00:26:00] through very well at the beginning of the trial design. And yeah, interactions between statisticians, clinicians. and clinical operations was not optimal at that point.
[00:26:14] Jessica: Yeah. Yeah. I have the same experience.
[00:26:18] Unfortunately, often the [00:26:20] whole clinical trial planning is under time pressure, right? So if you talk to the people involved, most of the time I’m hearing something like, yeah, I know, but I haven’t had enough time of the timelines given top down. But I think it’s, it’s [00:26:40] really not smart because as you mentioned, you are initiating the first protocol amendment right away with a lot of extra effort from the administration point of view when it comes to the resources.
[00:26:54] And here we are not talking about the sponsor resources, but also the vendor resources, if they [00:27:00] impact, I don’t know, the full service CRO, data management, lab, IMP supply, but also the sites. You put the burden on the sites as well, and you need to get that submitted and approved before and everything is creating costs as well.[00:27:20]
[00:27:20] So looking back, and that’s why I believe a lessons learned meeting at the end of the clinical trial is so much valuable to look back to your clinical trial and have an estimate what has happened, and then try to extrapolate like [00:27:40] If I have invested two more months for the planning and have a detailed planning up front with a robust feasibility, wouldn’t I have been faster, cheaper in the end?
[00:27:54] And often I think the answer is yes. I’m always trying to, [00:28:00] to push the industry to Invest enough time for pre planning. You have a robust detailed planning. It’s a pain in the peep, right? But it’s so well invested because you will speed up later on, still keep the quality and achieve your goals [00:28:20] in time.
[00:28:21] Think about the reputational aspect of going out to the, to your investors telling them, Oh, I promised to complete recruitment this year, but it’s delayed until next year. Okay.
[00:28:33] Alexander: Yep. Yep. Yeah.
[00:28:36] Jessica: Those things are not even covered in the [00:28:40] clinical trial level, but the company reputation, you know, I work for stock markets companies and the price was always going down.
[00:28:52] I call it a homebrewed issue. You can avoid those issues while [00:29:00] sitting together, have a robust kickoff meeting with all parties involved, talking to each other, as you mentioned, right? Talking to the biostatistician, understanding the design and the Key triggers will be even more important with the adaptive designs [00:29:20] and with the adaptive designs, you need to come up with your algorithm up front.
[00:29:25] So you are, you are pushed into the detailed planning. And this is really something I like about the adaptive designs, the collaboration within the sponsor organization, but [00:29:40] also outside of the sponsor. organization will be forced to improve.
[00:29:46] Alexander: Yeah.
[00:29:48] Jessica: And I believe one of the consequences we will see is that we have a good planning up front
[00:29:56] Alexander: and
[00:29:56] Jessica: we are just pushed into the right direction.
[00:29:59] Alexander: Yeah. [00:30:00] Because adaptive trials are great. And they can help a lot. And they need good planning. That is one of the most important things. Awesome. Thanks so much, Jessica, for this great discussion. We talked about [00:30:20] lots of, lots of different parts of where clinical operations and biostatistics can work.
[00:30:27] better together to make sure that we have high quality studies that deliver on time, on budget, yeah, and actually give us robust evidence [00:30:40] so that we can make good decisions within the company, but also for regulators and ultimately for patients and physicians.
[00:30:48] Jessica: Indeed.
[00:30:49] Alexander: And we talked about We need to learn from each other in terms of the languages, the goals, the constraints that we work under and said, especially [00:31:00] with all kind of more difficult.
[00:31:02] modern designs, more complicated designs. It’s really important. We even touched on a couple of things where maybe you have never thought about doing like visiting a site like speaking about what are the biggest challenges in terms of recruitment, [00:31:20] looking more closely into Screening, how do you do these kind of different things?
[00:31:25] What is actually happening at the side? What are the, you know, biggest barriers where you haven’t never thought about, you know, so this is really, really crucial. And it’s
[00:31:37] Jessica: working together, right? Yeah. [00:31:40]
[00:31:40] Alexander: Let’s work together. That is just the thing that I wanted to ask you about. What’s your main takeaway?
[00:31:46] Let’s work together. Thanks so much, Jessica. And maybe that wasn’t the last episode.
[00:31:53] Jessica: Thank you for having me. Looking forward.
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