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

Hello, everyone. Welcome to today's live broadcast, precision medicine and clinical trials, adapting to the new demands of clinical research today. I'm Lisa Henderson, the Editorial Director of Applied Clinical Trials and I'll be your moderator for today's event. We are pleased to bring you this webcast presented by Applied Clinical Trials and sponsored by Inteliquet. I would like to share a statement from our sponsor. Inteliquet is a leading provider of innovative technology and comprehensive support services for cancer clinical researchers. They bridge sponsors, patients and cancer centers nationwide for the ultimate purpose of increasing patient access to cancer trial treatment options. From trial selection to patient matching, Inteliquet enables a streamlined and more accurate journey to patient enrollment. You can learn more at www.intelliquet.com. We have a few important announcements before we begin. This webcast is designed to be interactive, and we encourage you to ask questions during the event. [Operator Instructions] Your slides will advance automatically during the event. And if you have any technical problems viewing or hearing this presentation, please click the question mark help widget in the top right of your presentation window. And now I'd like to introduce today's speakers. We are pleased to be joined today by Betsy Wagner and Joanna Hill. Betsy Wagner is a seasoned clinical research professional with over 15 years of progressive site CRO and vendor experience. She has a deep background in clinical trial operations and patient recruitment using traditional and tech-enabled solutions. She has overseen departmental growth in both academic and community research settings, providing a variety of experiences to inform how sites can be their best in order to facilitate more patients having access to more trials. And Joanna Hill has over 25 years of experience in overseeing research and clinical operations in both academic and community-based health care systems. Throughout her career, she's helped impact health care innovation, exhibiting proven financial, regulatory and clinical management proficiencies. She has contributed to strategic institution-wide advancements, driving for better financial and operational outcomes. She received her undergraduate degree from Indiana University and her MBA from the University of Minnesota, Carlsons Globe Management. Joanna current serves the Director of Health Partners and Cancer Research Center in Minneapolis, St. Paul, Minnesota. So thank you for joining us today so much. Betsy, could you get us started?

Okay. I'm going to jump right in here with our agenda. Today, we are excited to talk to you about precision medicines evolving impact on clinical research, digging into protocol complexity and the implications of that for operations at research sites. We want to talk about some technology solutions that are out there for navigating these types of trials and then finally leave you with some actionable takeaways. You're likely aware of the development of precision or personalized medicine this way of finding treatment for medical issues, focused on specific groups or even a single individual patient. As we learn more about the genetic and environmental determinants of disease, we're able to focus on options for treatment that are specifically tailored to those causes or factors. Oncology care is a strong example of this trend, where genetic testing allows providers to optimize their choice of chemotherapy regimen for a fairly like of success and a lower chance of adverse events, but determining the interplay of these genetic biomarkers and medications is difficult and must be evidence based. And this is -- this requirement has huge implications for the clinical research industry, which we'd like to dig into today. As you can see here, precision medicine has been used since- in some form since ancient Greece, when reactions to faba beans were used to detect what we later learned was an deficiency leading to hemolytic anemia, changing the dosing of malaria treatment. In the modern era, especially since the discovery of DNA, it's going to represent a larger piece of health care. Over the last few decades, investigators and physicians use a new understanding of genes like 450 roles in drug metabolism, HER2s impact on breast cancer survival rates and VEGFs role in numerous diseases from cancer to cardiovascular health to even COVID-19. As genetic testing has become more commonplace, trials are being built to take advantage of this information such as the NCI's MATCH protocol which enrolled over 1,200 cancer patients and demonstrated a viable method for identifying and treating patients based on biomarkers alone. We've seen FDA approvals of new drugs based on biomarker-based strategies jumped from 5% in 2005 to now representing the majority of clinical trials in some therapeutic areas, especially those with a high correlation of where genetic determinants play a large role such as in cystic fibrosis or Duchenne muscular dystrophy. So how do precision medicine trials work? Joanna is going to walk through a few models that you're likely to see in your own trials.

Great. Thank you, Betsy. Given the identification of different mutations in molecular alterations, the design of clinical trials continues to change to facilitate the discovery of new treatments for many diseases. A particular interest are what's known as basket trials and umbrella trials. Historically, most clinical trials focused on patients group by diagnosis, which historically was determined by symptoms or in oncology, location of the primary tumor in a particular organ. Precision medicine trials look for patients who share these genetic markers and then design a trial to test a hypothesis about those markers. So basket trials refer to designs in which the targeted therapy is tested in multiple diseases that have a common molecular alteration, whereas umbrella trust conversely test multiple targeted interventions within a single disease. In these studies, patients are stratified in subgroups based on their molecular alteration. So both basket and umbrella trials have the potential to improve the efficiency and effectiveness of clinical trials, which can accelerate drug development and ultimately lead to better treatment options for patients. In addition, since the cost of NGS testing can be prohibitive, particularly for patients without insurance, access to basket umbrella trials, which cover the cost of this testing, is a key factor for patients and providers looking to use genetic markers in care decisions. However, there are some pitfalls or clinical research sites when operationalizing these types of trials. Most importantly, knowing which trials to open is key because mutational and molecular alteration status are key factors in these trials, it's imperative to have a real solid understanding for your patient population. This is not always easy, though as NGS testing results are captured in a variety of fields and language in different EMRs, making them difficult to search for. As a result, sites might not realize just how common or uncommon certain mutations are in their patient population. The bottom line is that with the advent of precision medicine trials, we now have new challenges to the way we operationalize research.

Over the last few years, the complexity of all clinical research has increased, in particular, when trials have a precision focus. Industry surveys show the number of procedures in a typical protocol has increased 70% with the average number of significant amendments rising from 2.3 to 3.3 per protocol. We've also seen a 60% increase in the number of inclusion and exclusion criteria. Thinking about enrollment, when a trial is looking for a niche subpopulation, by definition, those patients are less common and harder to identify. For example, a trial that enrolls all sickle cell anemia patients is going to have a larger patient pool than a trial that's looking for hemoglobin SS type sickle cell patients who have already undergone treatment with hydroxyurea. This is true in all the therapeutic indications, though. And the granularity of these subpopulations is increasing with every new discovery of a genetic indicator of disease or disease treatment. There's also evidence that precision medicine trials have a shorter time to completion, possibly due to smaller enrollment goals as shown by the decrease in average sample size. And my own experience of growing a program, I've seen this play out with a need to open a higher number of trials in order to have a portfolio ports the same number of patients while those trials open and close more quickly. Alternatively, regulations around new biomarkers are more stringent due to a focus on the technology of testing for those markers and also on emerging technology for treating patients, such as gene and cell therapies. And while the FDA and EMA have both published guidelines, precision trials may be built using novel trial designs, such as adaptive trials or master protocols that bring another level of complexity. And while the improved outcome for patients, both in terms of response and adverse events, is very welcome, the operational implications of this trend are complex and likely only increasing further.

Yes. And the interesting thing is that unfortunately, the funding for oncology clinical trials has remained relatively stable over the years despite the growing complexity of these trials. This is due to several factors. Firstly, advances in technology and precision medicine have led to more complex trial designs and the need for larger sample size. Additionally, regulatory requirements have become more stringent, leading to an increased cost associated with data management and monitoring. Secondly, competition for funding has increased with a greater number of clinical trials being conducted in oncology more now than ever. This has led to an increased competition for funding from pharmaceutical companies, government agencies and philanthropic organizations. Finally, there is a growing recognition for the importance of clinical trials in advancing cancer treatment and improving patient outcomes. Despite the challenges associated with funding these trials, many organizations continue to prioritize funding for oncology clinical trials, recognizing the potential impact that they can have on patient care. To address the growing complexity of oncology clinical trials, researchers and funding organizations are exploring new approaches to trial design and implementation including the use of innovative technologies. To address the growing complexity of oncology clinical trials, researchers and funding organizations are exploring new approaches to trial design and implementation, including the use of innovative technologies such as artificial intelligence and machine learning to streamline trial processes and reduce costs. Additionally, collaborations between industry, academia and government are helping to facilitate greater access to funding and resources, enabling researchers to conduct more complex and comprehensive clinical trials.

So thinking through a typical prescreening enrollment process, this increased complexity and trial structure has many implications for the process. Let's start with physicians or other providers who are often looking for ways to keep up to date on open trials while seeing more and more patients each day. When considering a patient for a study, a provider needs to quickly know which trials are available to that patient. But if the portfolio is a complicated mix of trials, each with their own very specific parameters for eligibility, this is difficult, maybe to the point of impossible. In one of my first roles at a large academic center, we had patients who fit into just a few groups and for each of those patient groups, we had a newly diagnosed trial and a relapse trial. And these dozen or so trials represented a complete portfolio where we had something for nearly every patient who walked in. Now each trial is looking for patients with a specific diagnosis, known biomarkers at a certain stage in their treatment journey or looking for patients who've seen a very specific prior series of therapies. And the end result is that providers and research staff are all juggling a lot more options and is becoming unmanageable with existing tools. Furthermore, this complexity can be a barrier for patients in many arenas, especially as DCTs become more prevalent, patients are seeking out trials versus being presented with options. And while that accessibility is a great step forward, it also introduces a level of friction in the need to understand medical terminology in biochemistry and pharmacology that's beyond most people. Think about an ICF in the language and the level it's written at versus what's available at clinicaltrials.gov or in a protocol. And even in the best scenario, when our patient has been identified as a candidate for a trial, the ICF is going to provide the patient with information about what's going to happen, what their risks are, but also what procedures to expect, and again, a longer list of eligibility criteria and enrollment procedures. Breaking down that information with the patient and on their behalf, then falls to either the provider or the research staff, and it simply takes time. These are often patients who are bombarded with information, especially in the context of a new or worsening diagnosis. And it would be easy for this complexity and this barrage of information to be a turnoff with regard to participation in the trial. It's simply an arena where the staff spends a lot more time than they did when trials were simpler.

And not to mention, there are additional barriers to participation that we often forget to consider. For example, patients often say no to participating in clinical trials because they don't have the information they need to say yes. Due to their complexity, it's difficult to outline the direct cost for the patient's treatment while participating in a trial. Also, rarely do patients have details about transportation and parking and reimbursement. And lastly, there are concerns about the commitment of such trials and the lost time from family and work. So for example, if you think about their grandmother who is possibly missing her grandson's T-ball game because her treatment is going longer or she has to stay for extra blood draws. In addition, there are further barriers that disproportionately affect minority participation in clinical trials, mistrust, lack of awareness due to unconscious bias, apps and decision-makers and lack of cultural humility and knowledge among staff are some of those. As such, in addition to explaining the technical aspects of clinical trials, researchers really need to focus on building relationships with the patients. Researchers also need to increase cultural humility by educating themselves and ourselves about differences between racial and ethnic groups and the general population that may influence decision-making. Finally, with all patients, researchers need to consider the level of health literacy of each patient. When trial awareness is compromised, our patients lose the benefit of knowing the clinical trials are one of their options. We know that there are several studies that indicate awareness changes, attitudes towards clinical trials, enrollment and the benefits of participation. In an interactive survey done by Harris in 2001, 85% of patients were either unaware or unsure that participation in clinical trials was an option at the time of diagnosis. 75% of these patients said that they would have been willing to enroll have they known that it was possible. So when given the information about clinical research, survey respondents affirmed its importance. 32% of American adults indicate that they would be willing to participate in a clinical trial at vast. 28% indicated that they would consider it but hold some reservations. Focus groups with the public and caregivers found that many lacked familiarity with clinical trials were unaware of opportunities for participation by healthy volunteers, and they generally express negative attitudes about participation. These attitudes significantly changed after learning more about clinical trials. So in order to successfully manage the complex precision medicine trials, you need to have some institutional infrastructure and support clinical trials, office infrastructure and expertise and support of internal health care providers and network content. So we have with institutional infrastructure and support. You definitely need a dedicated experimental pharmacists or pharmacies. You need a dedicated physical facilities. You need to have alignment with administrative support and buy-in from your senior executives, and you need to have a dedicated financial team to handle budgets and contracts with an accelerated turnaround time. Legal infrastructure with experts who understand the limits of intellectual property and have experience with research contract organizations, material transfer agreements and investigator sponsorship is really key in having the right infrastructure and support. Secondly, you need clinical trials office infrastructure and expertise. Not only do you need the medical expertise and the nursing expertise, you also need the regulatory affairs expertise. So they need to have knowledge of federal, state and local and organizational requirements and guidelines. You need to have specimen processing expertise and special equipment for those specimen and laboratory tests that you're doing. Lastly, you need support from internal health care providers and your network of contacts. Vast and deep networks of context, referring physicians and industry partners is key. This will help you bring in more for your studies. Collaboration with an access to high-level interventional radiology is also needed, for example, because sometimes the biopsies that need specimen acquisition and you also need specialty teams, for example, specialized medicine or surgical services.

The operational implications of precision medicine trials extend well beyond the patient consent process. As we've noted, increasingly niche trials enroll fewer patients per trial than more general studies. If you're the director of a research program, what does that mean for you? Looking at the bottom line, you know the revenue you need to generate in order to keep the lights on. For each trial, you likely have calculated estimated enrollment and the revenue resulting from those enrollments. If the trial is smaller in terms of potential revenue because of a smaller patient population, you likely need to open multiple trials to generate that same revenue. If I need to open more trials, both to cover the patient population that I serve and meet my bottom line, that means a lot more work. The start-up of any given trial means site selection, budget negotiations, training, regulatory submissions and any other pieces of sponsor start-up process. All that work requires people, time and operational resources, meaning your program has a higher overhead to open more trials to serve the same number of patients. And layering on top of that, as we've noted, these trials are more complex both for staff and for patients and may require that you up-skill your staff in some way.

Yes, and this is further complicated when there are Phase I precision medicine trials due to the small sample size that's usually require. Regardless of the phase, however, some of the mutations that are needed for eligibility can be rare. So on one hand, you want to ensure that you have trials available to fit even those rare patient populations because those will set you apart from the other clinical research sites near yours. But on the other hand, the time and effort to not only open a study, but to keep that study ongoing with annual review, safety reports, drug maintenance and et cetera, can be intense. One of the challenges our site faces is that there isn't a great mechanism to search for patients with specific mutations. Currently, this information is available in our EMR in 1 of 2 ways. Number one, in free tax within and number two, as a scan document from the NGS testing site in our Media tab. While your EMR may have a genomics module for such data, entering those data into the module is also very taxing. While there may be ways to directly interface with the NGS companies so that data are discretely important into that EMR, oftentimes, there are more than one NGS vendor used by large organizations. As an example of how precision medicine trials can be difficult to manage at my sight, we opened a child that required patients to have advanced solid malignancies harboring the ALK, ROS1 or NTRK gene rearrangements. We opened this study because we had an eligible patient within a week. However, after that patient, we really struggled to identify our other patients that came through our clinic with these targeted mutations. This could have been for 2 reasons. Number one, perhaps there was just a rare mutation for our population, and that first patient was a product of lucky timing. Or number two, we simply do not have a great way to search our EMR for these patients, and we're missing potentially good study candidates.

Joanna, that's a great example. And you bring up an interesting point that as we look at genetically determine populations, there are racial, ethnic and other diversity considerations that we need to bring into this conversation.

Yes, absolutely. There are several benefits to ensuring that there is diversity in clinical trials. One of the benefits of diversity is the generalizability of it. With lower participation rates among underrepresented populations compromise the generalizability of research findings. The entire U.S. population would be more accurately represented if there was an increase in diversity among clinical trial participants. And underrepresentation results in data from clinical trial only applying to a select group of population. People of color are projected to account for over half of the U.S. population by or before the year 2050. So intentional efforts to increase diversity in clinical research is really imperative and even more so as the population becomes more diverse. There are also differences among groups. Diverse population helps explore and better understand differences in disease biology and the efficacy of medical treatments across race, ancestry, ethnicity and gender. Aged genetics, gender, weight, ethnicity and even geographical location all play a role in how the treatment may work or how safe it may be. A lack of diversity in clinical trial participants means that we currently don't know if all medicines are equally safe and effective for everyone. Differences in disease and medication response often aren't known until after the drug is approved, in widespread use, which raises red flag on safety and efficacy. So if the FDA approves a medication, it will be prescribed for all people, so the data need to reflect the effectiveness and potential side effects for all groups, not just the small groups. Medical advancement and equity is another advantage to diversity. While general scientific knowledge in medical care have advanced substantially in the years, Black Americans, Latinx women, LGBTQIA+ and other underserved U.S. groups have benefited less from those advances. Inclusion of diverse populations in clinical trials may lead to more robust and complete data that proves the understanding of racial, ethnic and gender differences in treatment responses and contributes to the reduced disparities in disease outcomes. Having these diverse groups of participants in the study makes medical products safer and more effective for everyone because it allows researchers to see how interventions affect individuals of different ages, races, ethnic groups and genders. Increased awareness is another advantage, and intentionally increasing diversity in clinical trials gives a larger segment of the population access to standard care and cutting-edge treatment for their conditions. This increase is the likelihood that historically underserved communities can benefit from novel therapies. In cases where underserved communities may carry a greater burden of disease, increased access to clinical research and trials can potentially lead to more effective treatments and better health, thereby reducing health disparities. And lastly, we have to make sure we look to the equity lens. Implementing best practices and strategies to increase diversity in clinical research promotes access to clinical trials, creating new treatments and care options that work well for all patients. This is critical to advancing health equity and providing equal opportunity for people to live the healthiest life possible. Equity and awareness, options and opportunities really is key. But how do we break these down these disparities and advance health equity? There are a lot of data to show that information regarding clinical trials has not been made widely available to underrepresented communities. Basic information on when and where people can receive treatment or how to navigate complex health systems is not easily available, much less what our clinical trial would entail and mean for their care. In addition, providers and clinical research teams asked some groups to participate in clinical research less frequently than other groups. This is often a result of assumptions held about a particular group or implicit bias, which we all have them. If we could help to eliminate these assumptions, our recruitment of potential participants will increase, representation will be more prominent and health disparities will diminish. At my side, that is why we're considering the use of some AI technology to help match patients to our clinical trials. In that way, we will look at our scheduled patients and can present our providers with the patient schedule for that day, denoting any patient who appears to be eligible for a trial. And this isn't about bringing more revenue or getting a statute erected in your honor on rolling the most patients outside of your hospital. It's about the best way to serve your community and to serve your patient population. It's about ensuring that the science and research is reflective of and effective in our entire population. Ensuring that you have diversity in your research populations is complicated further when protocols themselves are increasingly more complicated.

Some really good points there. And Joanna, I know you've managed a Phase I program during the rise of precision medicine. Some -- what are some of the financial implications you've had to consider or change?

Well, Betsy, I think we've touched on a lot of the considerations. The selection process for finding patients with specific biomarkers or genetic profiles. It's really time consuming and it requires advanced testing techniques to identify the eligible patients. Additionally, patient privacy and informed consent must be carefully managed during patient selection process. Because the design of precision medicine protocols is of a higher acuity than traditional clinical trials, it also takes specialized and detailed training on the study, including kind of handle, manage, interpret data, data privacy, security and patient confidentiality. Also, precision medicine trials can take longer to complete because of the time required for patient selection and data collection. This can result in increased costs associated with prolonged trial management infrastructure. And yet, the budgets of these trials are more appropriate for the traditional clinical trials. I can't tell you how many times I'm constantly providing justification for our cost. And I think that sponsors and CROs don't realize that precision hard [indiscernible] that is needed to manage these trials at the site level. And that takes time and effort in every minute of time and effort must be accounted for.

Yes. So knowing that these trials are more difficult to enroll to, what are your concerns with sites who need to maintain a strong reputation that will facilitate them having access to future trials?

Right. Well, I think there are several things you can do. And number one, we always think of the old adage, you never get a second chance to make a first impression. From the contact that we have with our CRO, our sponsor, we provide document and information about our site, and this includes information about our staff and our researchers, our experience, our time lines for getting the protocol through to approval, our physical resources and maintenance schedules, et cetera. We also have created several policies and documents that clearly outline our processes, first screening and recruitment and that is really an absolute must. You also need to have a solid recruitment strategy and not only a recruitment strategy in general, but one from a DEI perspective. That is something that sponsors and CROs are requiring more frequently. At HealthPartners, our cancer research center, we've developed a DEI action plan to outline the ways that we are looking to increase diversity for clinical trials participation. This includes getting the demographic breakdown from our 11 County area for our patients that we serve and using that as our benchmark. We also realized the traditional methods for identifying patients -- or potential patients through like tumor registry and our virtual data warehouse, our clinical data warehouse and our EMR searches is no longer sufficient given the complexity of eligibility criteria. So we're pursuing these different AI technologies, as I mentioned earlier, that will help improve our operational efficiency for screening recruitment as well as tumor assessment measurements. The more prepared and organized you are, the more sponsors, CROs will continue to advocate for your site, and you will be able to participate in future trials because you'll become their go-to site.

So most importantly, what do you see is the impact on patients with this move towards tailored trials? There's an obvious benefit, more personalized care has shown great outcomes, fewer adverse events, but there's also drawbacks. Where are we on that spectrum right now? And where do you see it going in the future?