IQVIA Holdings Inc. (IQV) Earnings Call Transcript & Summary

Hi, everyone, and welcome to today's live broadcast, Patient Centricity in Design. My name is Andy Studna, Editor of pharmaceutical executive, and I will be your moderator for today's event. We are pleased to bring you this webcast presented by Pharm Exec and sponsored by IQVIA. I'd like to take a moment to share a statement from our sponsor IQVIA before we begin. IQVIA is a leading global provider of advanced analytics, technology solutions and clinical research services to life sciences industry. IQVIA creates intelligent connections to deliver powerful insights which speed in agility, enabling customers to accelerate the clinical development and commercialization of innovative medical treatments that improve health care outcomes for patients. With approximately 82,000 employees, IQVIA conducts operations in more than 100 countries. You can learn more by logging on at www.iqvia.com. And now I want to take a moment to highlight a few important announcements before we begin. This webcast is designed to be interactive, and we encourage you to ask questions during the event. You could submit questions by typing them in the Q&A box, which can be found at the bottom of the video player. You can enlarge the slide window by clicking on the small icon in the bottom right corner of the media player. The slides will advance automatically during the event. And finally, if you have any technical problems viewing or hearing this presentation, please click on the question mark Help widget in the top right of your presentation window. I would now like to introduce today's speaker. We are pleased to be joined today by Ivan Petrov. Ivan Petrov is based in the IQVIA Sofia office. He has experience in both health care and FMCG consulting. He holds MBA with a specialization in strategic management from Sofia University. Prior to joining IQVIA, he was a part of the Nielsen Consulting team, leading the business for Bulgaria and advising FMCG companies by creating tailor-made solutions to meet client goals. Ivan has been with IQVIA since 2015 and is currently part of the design analytics team, where he helps clients optimize their study design, excuse me. His focus is on patient perspective, ensuring patient voice is heard throughout the clinical development continuum. So thank you all for joining us today. And I will now hand it to Ivan to get us started.

My name is Ivan Petrov, and I'm a member of the design analytics team in IQVIA. Our team specializing in applying data and advance analytics to support the design decisions. Today, I'll be sharing how analytics and patient perspectives can be used to understand patients, drive patient centricity and lead to more efficient clinical program execution. Let's start with some background on why a study should be patient-centric. The Tufts Center for Study of Drug Development recently published trial performance metrics revealing that longer-than-planned cycle times and budgets exceeding plans have been relatively common. Furthermore, the latest Tufts impact report has highlighted that the prevalence of protocol amendments continues to rise across all phases of studies, currently reaching nearly 77% of our protocols. In general, protocols are more complex, with more than 70% of managed protocols regarding modification of study procedures and trial designs. Also, a [ third ] Tufts study highlighted that nearly 1/3 of clinical study patients experienced at least one protocol deviation. These challenges can be addressed though, and that is through improved patient engagement. According to Tufts, studies with input from patients resulted in simpler protocols, more targeted designs, fewer end points, less eligibility criteria and fewer procedures performed per visit. Also, these patient-informed protocols had a lower percentage of procedures supporting [indiscernible] and miscellaneous end points. Now the results indicated that patient-informed protocols had better relative performance. Notable differences included faster study initiation, shorter clinical trial duration, quicker study closeout, reduced study budgets and fewer average number of substantial protocol amendments. Furthermore, another study highlighted that higher patient engagement was associated with a lower number of substantial protocol deviations. Overall, these metrics show that patient engagement can be a key for more efficient operations. Now typically, the way that the [indiscernible] sponsor may focus on a patient is looking on -- looking at their eligibility. They look at whether the patient requires financial or travel support in order to reach the sites. They're looking on how to motivate this patient to participate in the study. However, patients decision may be driven by an extensive treatment and personal experience. This may have shaped their world view substantially. It may have shaped the way that they look at their condition. We had a recent example and recent discussion with the patient who was very interested in participating in a cardiovascular disease study since they had mentioned that they lost a close relative. So there is quite a lot of consideration coming behind a choice by a patient to participate in a trial or not. Now IQVIA with founded applying design analytics and leveraging patient perspectives early and often during study design, is an effective way to engineer a patient-centric study. This combination can be conducted anywhere along the study development continuum. From the very beginning, when we have a target product profile definition. So we know who our patients will be right into starting operations. The outcomes of these assessments can be applied in 2 main ways. The first would be changing study design in order for it to be more patient-centric. However, oftentimes, that may not be feasible, some procedures are necessary in order to collect the appropriate data for the trial in order to monitor safety or in order to meet certain regulatory requirements. As such, some design changes may not be implemented. So there is a second way for applying this combination of design analytics and patient perspectives, take action to mitigate patient risk during this study. This can be as simple as providing some more informative materials for the patients, which can prepare them as well as prepare the sites for burdens and procedures, which might be necessary as part of the study design. Earlier application of both design and analytics and patient perspectives can help avoid changes that may become more costly as we approach operationalizing the study. If we dive a little bit deeper on what are design analytics and patient perspectives and very simply put their methods to incorporate the patient viewpoint into a clinical study. They leverage surveys amongst patients. They leverage real-world data. They leverage a variety of other databases as well as the IQVIA expertise. Now these analytics allow us to understand how our design compares against others in terms of patient burden. How familiar patients are with certain procedures, which procedures can be a concern for specific races and ethnicities. Also, we can take a look at whether our patient-reported outcomes can be optimized. What may patients say about study design or strategy. And last but, essentially, not least, how can we provide patients with more options, including the centralized approaches. Our analytics are executed with the patient focus. The idea is to ensure a design that fits the patient rather than expecting the patients to fit the study design. If we look at specific examples of each of these methods, we can start with patient burden. Patient burden is an assessment which leverages a survey with patients, which has been incorporated into an algorithm that can quantify the level of burden specific design has. This quantification allows us to parse the studies procedures, ranking them from level -- by level of burden, starting from the most burdensome invasive procedures or elements which are burdensome in terms of high frequency of visits or long visits. Then moving through moderately burdensome procedures and elements. And finally, reaching the least burdensome ones where we have a few short visits as well as low burden procedures such as imaging. Now the standardized algorithm also allows a comparison of a study design to recent similar trials and also allows a comparison towards different versions or scenarios of the same trial. So speaking of the latter, how is this applied in the real world. This is an example of that, where we quantify specific scenarios for 1 protocol. We can see that here, we have 3 scenarios with scenario 1 having less visits. However, they are longer. Scenarios 2 and 3 have more visits. However, they are shorter. Such an approach allows for an easy comparison of patient burden between different design options. And ultimately, this evaluation of the patient burden of different design scenarios does prompt awareness and discussion on design parameters that influence patient engagement. The objective or the goal of this is to take action and decrease patient burden where possible prior to having a final protocol or a final design for your study. Certain procedures may be potentially unnecessary such as screening biopsy where an archival 1 is sufficient. However, some burden is inevitable. It can be due to efficacy. It can be due to safety monitoring. It can be due to regulatory requirements. In such a case, design may remain unchanged. However, taking a look at understanding which elements might be found more burdensome is still very valuable as it can provide the basis of risk mitigation plans. These risk mitigation plans can be as simple as if patients find a specific duration of visit burdensome, they can be provided with a dedicated waiting room between procedures during long visits or even as simple as providing lunch to these patients. Now taking a look at whether and how patient burden correlates with various trial performance metrics. What we have here is an assessment of 100 protocols between 2010 and 2020, which compares design variables with study performance metrics. The idea is to better understand how patient burden correlates with study performance. The result of this assessment was that higher patient burden correlated with longer start-up time, higher number of protocol amendments and higher screen failure rate. Ultimately, these results are aligned with the industry metrics that we have shared in the beginning of this presentation, underscoring the importance of a patient informed design. Adding to patient burden, we may also take a look at certain procedures that are done in standard of care and how familiar are patients with them. Our recent IQVIA study highlighted that 75% of patients do not have personal experience with a clinical study. And even though nearly 90% are hopeful that the treatment will help them and improve their condition. A significant majority are concerned about side effects as well as the types and number of procedures. Due to these procedures being a concern, understanding them is a key consideration when building a patient-centric study design. IQVIA assessments have shown that nearly half of studies include procedures that patient -- the more most patients will not have had in their standard of care. And in over 90% of studies, procedure frequency might be higher than what patients are used to. Now streamlining and removing procedures that patients may not be familiar with or educating patients on what they could expect in a clinical trial setting may help with this reduction of the overall patient burden, and thus, drive potential efficiencies in trial execution. If we build further on patient burden and study procedures, what we have identified are certain differences in perceived burden across different races and ethnicities. In general, nearly 75% of patients are either extremely or very willing to participate in a clinical study, regardless of race and ethnicity with patients identifying themselves as [indiscernible] being very often extremely willing to participate. Now at the same time, in terms of burdens and study design parameters, these patients also vary in terms of elements that they find burdensome or not. And you can see that there are some differences according to race in the share of elements that certain races and ethnicities may find burdensome, indicating that a specific or special approach may be required. So to identify which procedures would require such an approach, we might wish to go a level deeper. In this example, we can see that there are certain procedures that specific races and ethnicities might find relatively more burdensome than others. And this is, of course, controlling for other variables. In this case, visit frequency, blood draw frequency, need to complete a diary, number of patient-reported outcomes to be filled in, number of in-person visits. These are all elements that may be found relatively more burdensome by patients who are identified as Hispanic. Alternatively, other patients and other patient groups may have different concerns. To apply this in the real world, we have -- we can have, for example, an investigator proactively discuss the benefit of having multiple patient outcome assessments with patients who might consider this burdensome elements of study design. Speaking of patient-reported outcomes, another perspective for another deep dive can be conducted for them. The patient reported outcomes or PROs have been on a steady increase in use. And according to our latest assessments, they're present in nearly 20% of all clinical studies irrespective of phase or indication. PROs can provide valuable insights. They can provide insights on how patients experience a clinical study, what are the effects of their disease, what are the effects of their treatment. And there are some notable examples here including the Short Form 36 or the 5 dimensions scale. However, some studies may evaluate multiple PROs in order to gather as much data as possible. One point for consideration here is a potential overlap in valuated domains. Some combinations of PROs may synergize fairly well, whereas others may not as they may have fairly similar questions. The identification of overlapping PROs can point to noncritical endpoints for removal without compromising the data which is being collected. This reduction in term in number of PROs can reduce overall patient burden for patients who are participating in the study. Moving on, in addition to applying design analytics, there are certain patient perspectives that can also be included. One of these is patient voice, allowing direct outreach to patients or other stakeholders about their experience and preferences. Now IQVIA consults over 400 publicly available secondary research sources, in addition to a library of internal proprietary sources. And this is all done to allow an even deeper dive into a patient or a stakeholder point of view. This is an example from an RSV discussion where we saw some interesting facts where certain age groups, 55 and older had not heard of it of RSV that is. And we saw that both of the patients had received their last vaccine from a physician. And there was a remainder, which could be recruited through a community health partner as well as online since the patient population can be fairly active online. Thus design can be informed by these patient preferences or stakeholder preferences to a very high degree of granularity. Another patient perspective is using design options such as remote or at-home visits, which allow patients to engage with the study as they please. We have all seen recent developments. [indiscernible] ever increasing and now widespread digitalization that have been further accelerated by COVID-19. Remote has become more and more common. Remote work quickly has become the norm in many industries. Remote care monitoring visits has also become more common in this post-pandemic reality. So similarly, with this increase in digitalization, we are seeing that patients want more options. They want to choose how they engage in the study. This may include the ability to have a doctor's office visits or remote visits or a combination of both, ease and convenience have been the primary benefit cited by patients about remote visits. However, the word options is key. Patients have expressed that there are not only benefits but also some concerns. Having sites that visit them in their home has been the greatest concern, followed by the need to self-administer the study medication. Despite that patients are open to decentralized options, but many other elements that we have seen so far, the approach should be such that it should ultimately allow for the patient choice or the patient preference. Now if we move to the key takeaways that we have from this webinar. In summary, we have seen that placing the patients as the focus of our studies and making sure that our studies fits to the patient rather than expecting the patient to contort and to fit the study may have significant benefits to -- in study operations. Applying design analytics, leveraging patient perspectives can be done early during study design in order to ensure or to actually to avoid changes to that become more costly as we approach operationalizing the study. Design analytics, focused on evaluating patient burden. They take a look and evaluate whether patients are familiar with certain study procedures, whether the burden differs depending on certain races and ethnicities as well as what is the use and how -- what is the way that we use patient-reported outcomes, whereas patient perspectives focus on incorporating the patient and stakeholder voice and allowing greater flexibility by using certain decentralized options. However, I just want to underline that now these assessments can directly lead to a more patient-centric design unless these insights or knowledge is translated in some way into the study itself. Operational reality dictates that some burden is inevitable. It is necessary for obtaining the appropriate data. It is necessary for ensuring patient safety for meeting regulatory requirements. Still, some design changes are possible or whenever these are not possible, risk mitigation plans can be built in order to ensure that the patients are heard and engaged. This, in turn, can lead to operational efficiencies. And ultimately, the goal is to allow these interventions to reach the market sooner. And thus, reach the ones who needed the most. Okay. And now we have some time for questions and answers, and I will hand it over to our moderator.

[Operator Instructions] So with that, we have some questions in already, so we will get right to it. Ivan, first question, you mentioned U.S. races and ethnicities. What about non-U.S. patients and their perceived burden?

Yes. Thank you very much, Andy. This is an excellent question. So we have started with IQVIA with U.S. races and ethnicities, just to the fact that the FDA has underlined that there is a strong need to -- and the focus is to enroll clinically diverse population. Now I wanted to support with -- starting with the U.S. market. And we have taken quite a bit of learnings from that market. Our efforts, and we are currently developing a global understanding of patient burden, and we are expanding to 18 additional countries. There will be more than 10,000 patients that we're going to be discussing patient burden with. And we expect this more global patient burden to be available around Q2 of 2024.

Great. On to our next question. How does IQVIA obtain patient and site staff feedback on protocol design during protocol development when time is constrained?

Yes. Another great question. Ultimately, we have a lot of critical milestones to meet during study development and time is of [indiscernible] always. So the idea behind some of these assessments is that they can be performed fairly quickly, but it all depends on scope. So in essence, Design Analytics, what they do is they leverage completed survey data, real-world data, a lot of proprietary databases as well. And we are using this data in order to provide not only an ease of comparison and a consistent methodology, consistent benchmarking throughout studies but also this quick turnaround. Usually, we have -- we can provide some preliminary results within a week or 2. So it's a fairly quick turnaround and it's fairly quick to turn around. Now if we require a more customized approach, let's say that we are aiming for a specific niche patient group or we aim to understand a specific type of stakeholders to engage with a specific patient advocacy group, for example, then this might extend time lines. But still, we do understand that time line is fairly important, and [indiscernible] design in such a way to meet that. Now to update and to improve that even further, we are developing some tech-enabled solutions. One of them is protocol analyzer, and we are currently piloting it with some interested clients. It goes to completely automate some of these assessments and to -- and it provides self-serve analysis. In essence, that means that different types of protocol designs or study designs can be evaluated on demand. And we are -- as I said, we are leveraging some discussions with some clients, and we are leveraging some clients for that. And we are hoping to have some more news about that in 2024.

All right. Great. Now our next question, is your approach to patient centricity disease/condition dependent?

Yes, very much so. Now obviously, there are huge differences in the way that patients perceive their condition. And there are tremendous differences in both symptomatology, burden to the disease -- from the disease as well as standard of care. So such an approach should be tailor-made. We're leveraging some medical expertise. We are also leveraging different types of information and data. For example, there is -- there are some databases, which, for example, for oncology, we can go into quite a bit of detail on patients' clinical journey since we -- for oncology, there are quite -- there is quite a lot of information on the medications that are used on a different therapeutic rise of treatment. So to cut a rather long answer short, it is very much dependent on therapeutic area and indication, and it varies significantly from one to another, in fairly a customized project needs to be applied.

All right. Now our next question is what if we are not able to change some of the elements suggested. For example, what if we need to have 2 burdensome biopsies?

Also [indiscernible] very interesting question. We did speak about patient burden and how some elements are more burdensome than others. Now it's clear to understand that some burden, as I mentioned, is inevitable. We do need specific procedures in order to provide the necessary efficacy data in order to obtain necessary information for regulatory approval for -- to ensure patient safety monitoring. So in this example, if we have 2 burdensome procedures, such as biopsies, one in the start to confirm patient eligibility and establish baseline and one in the end to evaluate the effect of our treatment, then we do -- we cannot change the fact that these 2 biopsies need to be conducted. This can, and understanding which elements may be considered burdensome, can open the door towards a more efficient risk mitigation strategy and more -- and better risk mitigation plans. For example, if we know that we have these burdens and procedures coming, we can prepare the patients for them. We can provide more information on -- to the patients if the patients need to prepare. I have seen studies where there were examples where we had highly burdensome procedures. However, the patients who are not as well prepared for them, and as such, patient preparation in order to obtain the optimal results of a burdensome procedure is often key. So there are a lot of strategies discussing patient concerns, providing information to patients on how to prepare for a certain procedure that can help and that can ensure that we are obtaining quality results out of our procedures.

All right. Now on to our next question, do you believe that providing patients with a medication adherence solution is an important part of patient centricity? And adherence solution that enables them to more effectively self-manage their medication regimen minimizing noncompliance and allows clinical teams to have greater patient oversight of how well the patient is complying with the dosing regimen away from the clinical sites, and increasing proactive patient engagement?

Excellent question. I do believe that this should be a very much indication and condition-specific. So for specific indications for specific conditions where we have self-medication and adherence need to be monitored quite carefully. There are certain indications where I have seen that especially adherence to medication has been somewhat lower until influence trial results or study results. So this is something to keep in mind. However, it needs to be a tailored strategy towards the specific indication, the type of patients and the mechanism or -- actually, not only the mechanism of action, but the methods of administration of the product. Obviously, there are some products which are much easier to administer than others, and this might need to be also taken into account.

All right. And now we have our next question. When it comes to applying design analytics and patient perspective, do you see a difference between early-stage studies, for example, Phase I and Phase II and late-stage studies such as Phase III?

Yes. So when we apply such a perspective, I would like to underline that this is very much focused on not only the indication but on phase. There are quite a bit of differences between different phases when it comes to studies. We have seen that obviously phase -- earlier phases are much more burdensome. And [indiscernible] phases are -- they don't have as many procedures so they are less burdensome. And the way that we approach and analyze or assess such studies would vary significantly. So something that might be considered a very burdensome design for Phase III might be a burdensome at all for an earlier Phase I.

All right. Great. Now just looking like -- I'm not sure if we have an extra question or 2 coming in. Ivan, what do you think of -- this one that just came in. So -- yes. I'll ask it now. The question, do you yet have evidence of burden reduction decreasing WD rate in comparable populations? And then I think you mentioned screen failure reduction in the presentation.

Yes. There are several factors that we have analyzed that are correlated with lower patient burden. So we have analyzed. I think it was 12 different -- 18 different variables. So out of them, a significant amount of them, 12, had a reduction of -- so they became more efficient with the decrease of patient burden. And this was statistically proven by our models, and we are working at the moment to enhance that even further and see if a specific reduction in terms of percentage you saw that we are speaking of patient burden as a score. So we are working to see if a specific percentage of patient burden can reduce certain metrics or certain trial execution metrics by a specific percent. So what will happen if I reduce my patient burden by 10%, would that change my recruitment rate or increase it by an x amount of percent. We can see that it does change. So there is a correlation there. The exact number behind that correlation is something that we are currently exploring.

All right. Great. And with that, we will wrap up for today. I would like to thank our audience again for attending and for participating in today's event. I would also like to thank our sponsor IQVIA for making today's webcast possible. We would like to ask everyone in the audience to participate in a brief survey, and this survey will appear on your screen after today's presentation has ended. You will receive an e-mail alerting you when this webcast will be available for replay, and we invite you to forward that announcement to your colleagues who may have missed today's live event. Once again, thank you all for joining us. We hope to see you all next time, and goodbye.