Analytics

CRO/Sponsor

Clinical Operations

Clinical Trial Supply Chain

DE&I

Data Management

Early Phase Development

Emerging Technology

Executive Roundtable

Feature Article

Industry Trends

Investigative Sites

Metrics and Benchmarks

Oncology

Online Extras

Patient Participation

Peer-Reviewed Articles

Protocol Design

Real World Evidence

Regulatory

Risk-Based Monitoring

Study Start-Up

Therapeutic Areas

Trial Design

Vendor Strategy & Collaboration

eClinical

mHealth

News

Publications

All Publications

E-Books

Media

Editorial Podcasts

Editorial Videos

Conferences

Conference Coverage

Conference Listing

Columns

All Columns

A Closing Thought

Clinical Trial Insights

View from Brussels

View from Washington

Resources

Advertise

Blogs

Brand Insights

Events

Front & Center

White Papers

Webcasts

Subscribe

Latest solutions, case studies, interviews, practical articles for clinical trials operations, data management, technology, investigative sites and services.

About

Contact Us

Editorial Contacts

Do Not Sell My Personal Information

Privacy Policy

Terms and Conditions

Applied Clinical Trials Online

LinkedIN

Instagram

Facebook

Youtube

Soundcloud

Threads

Spotlight

2023 Salary Survey

Topic

1rem

Authors

Emerging investigators play a vital role in bringing new patient populations to clinical trials, but reservations around their ability to deliver persist. Recruitment and retention continue to pose a hurdle to clinical research resulting in increasing recruitment of practicing physicians outside of academic centers, and for good reason.

Investigators with a rural practice, such as mine in Stephenville, TX, add more geographic variability to the predominantly urban and suburban landscape of clinical trials. As community physicians, we are often also able to reach more ethnically and racially diverse participants, due to close personal ties with patients in these areas.

Such recruitment benefits impart a compelling endorsement of emerging investigators. However, several additional advantages of engaging these investigators in clinical trials are less frequently discussed.

Strong familiarity with patients and communities

When physician investigators such as myself are embedded within a community practice, we have intimate knowledge about the patient populations served. As a result, we provide valuable (and otherwise unobtainable) input for many aspects of study design. This begins with recruitment. For example, we can predict which trial designs will be palatable for our patients. We also have insight into factors that will aid in participant retention, such as a clearer understanding of which trials and protocol iterations will be more attractive to our patient population. Many times, I have provided feedback to sponsors about protocol design that could be off-putting to the targeted patient population and the sponsors listen.I see many subjects in the research clinic and my personal clinic, which improves communication, compliance with e-diaries due to reminders of the importance of data collection, and enthusiasm for continuing with clinical research. Research is only a small facet of my relationship with most of our subjects and thus, they trust the research center and fewer barriers impeded retention and compliance.

Patient care backed by personal connection

Our concern for the health of our patients leads us to genuinely and enthusiastically encourage them to participate in trials that we think will help them. I have practiced in my community for ten years, and I plan on practicing for many more. Beyond my professional obligation, I have relationships with people within the community who go on to become trial participants—I see them at the grocery store, at football games, and in church.

My greatest source of pride as an emerging investigator is being able to provide newer treatment options and medical care to those who would not otherwise have access. Additionally, through the trial screening process, we have the potential to unearth other health conditions that were previously unnoticed. A few months ago, at a screening visit we noted some EKG changes in a patient with cardiovascular disease, and referred them to a cardiologist, where they received catheterization and stents before having a cardiovascular event. We have also screened for cervical cancer and sexually transmitted diseases as part of a birth control study and identified disease in women who were not previously aware of their health status—and did not have access to cervical cancer screening otherwise.

Providing these services to our patients through an integrated approach to trial delivery is extremely motivating for us as investigators. Because clinical research is established within our healthcare practices, trial participation is accessible as part of our overall offerings. This provides added value to our patients, while also providing momentum supporting clinical research advancement as a whole.

Emerging investigators often ask a lot of questions at the outset of a trial, reaching out to colleagues, trial support staff and even leadership from our sponsor or vendor partners. We must seek out best practices as we gather knowledge about the trial landscape. This leads to valuable interaction and collaboration. Fresh eyes on a protocol can only augment the sponsors’ offerings through the application of clinic curiosity.

There is no doubt that new investigators need support as they enter their first trials. Sponsors might hesitate to include new clinic-based investigators due to fear of compromised data, laxity concerning GCP procedures, difficulty managing investigational product, and so on. In my very real-world experience, with the proper partnerships, infrastructure, processes and plans, getting started really can be relatively frictionless. The clinical investigator’s initial curiosity and collaborative spirit surmount these barriers and allow the embedded clinical research center to truly thrive, despite industry’s initial hesitations concerning their lack of experience.

In the beginning, my greatest challenge in Stephenville was to train staff. This did take some time, but it was made possible through collaboration with our clinical research partner, Javara, an integrated research organization (IRO). They are contracted by my medical group, Privia Health. With Javara’s support, combined with online training resources, we rapidly gained the knowledge and skills necessary to launch clinical trials from our practice.

This partnership has continued and is central to how we conduct all our clinical trials. In addition to serving as an investigator, I am also the medical director of clinical research for Privia Health in North Texas and meet with Javara leadership once or twice a month. This is a chance to offer feedback on our successes as well as any challenges we are experiencing. Close collaboration of this nature really allows emerging investigators to stay curious and to bring a fresh perspective to the conversation. With the right support, we can contribute to clinical research as efficiently as those more experienced in the field.

Without the help of a knowledgeable IRO or CRO partner, I would not have been able to manage clinical research independently. They oversee staff, provide necessary equipment and guide our team through regulatory documents and processes. This support also helps allay any compliance risks that can emerge, given the level of scrutiny faced by clinical trials.

A fresh approach and enthusiastic mindset

As we emerging investigators embark upon our journey into clinical research, we are not tied to certain processes or procedures. There is no obligation to maintain the status quo, and we are less apt to accept the “it’s the way it’s always been done” mentality. I believe our open-mindedness provides all stakeholders a unique opportunity to explore newer methods and systems during mentorship and training as well as throughout a clinical trial. The landscape of new digital tools and platforms, including artificial intelligence applications, is continually changing. Those of us newer to research often tend to be more open to embracing such tools because our instruction does not require any unlearning and thus saves time, energy, and potentially resources.

New clinic-based investigators are enthusiastic. We are accustomed to long hours and the intricacies of clinical practice and clinical research offers the emerging investigator a new and exhilarant flavor to our daily work. I have been thrilled with my journey into the world of clinical research, as it gives me an opportunity to learn about new medications and treatment regimens as they are being developed. This has helped to keep me on the cutting edge of advancements in medical science, and I have been able to keep my patients informed about what is on the horizon.

Clinical practitioners can sometimes fall into the habit of treating the same old maladies with the same old therapies—that may or may not exhibit the efficacy desired. Every day it seems, there is a new opportunity in my inbox, and I relish reading about the novel mechanisms of action and therapeutic targets I get to participate in bringing to those that need them most. This translates into an enthusiasm for the work that drives my desire to engage subjects and keep them engaged. Ultimately, I believe the spirit of clinical investigators positively affects the clinical trial ecosystem. Our patients sense our enthusiasm for their care, and I have seen this spirit invigorate other research staff at investigator meetings as well.

Overlooking the advantages of engaging emerging investigators in clinical trials negates the influential role they play in the sustainability and evolution of clinical research. I believe that as new investigators, we not only boost research capacity and expand access to geographically, racially, and ethnically diverse patients but also hold the power to help integrate research into communities more effectively. The fact that we are newer to the clinical trial ecosystem may mean that we bring in less hands-on trial experience, but we bring new perspectives, open-mindedness, and enthusiasm. As we collaborate with more established members of clinical trial teams and learn from them, we add new dimensions and carry knowledge forward for the ultimate benefit of all involved. We are a rich resource ready and waiting to engage sponsors in the real world where medicine happens—I can’t wait to see where we go from here.

, MD, is a family practitioner at Stephenville Medical and Surgical Clinic, a part of Privia Health, in Stephenville, TX.

Miessler, J. With high investigator dropout rates in trials, sites and sponsors must offer more support. CenterWatch. 

https://www.centerwatch.com/articles/25706-with-high-investigator-dropout-rates-in-trials-sites-and-sponsors-must-offer-more-support

. Published June 6, 2023. Accessed July 9, 2024.

New investigators practicing in community-based settings bring enthusiasm and a fresh approach to clinical research, while also boosting collaboration and merging personal connection and patient-centric insights.

Engaging Emerging Clinical Investigators Yields Unique Benefits for All

The pharmaceutical industry is facing a challenging landscape where the cost of bringing new drugs to market is rising and the return on investment (ROI) is sharply declining. 

 shows that the average cost of drug development has surpassed $2 billion, with a concerning 

, marking the lowest point since tracking began. Escalating costs and diminishing returns present a significant obstacle to sustained innovation in the pharmaceutical sector.

In response to these challenges, life sciences companies are increasingly turning to real-world data (RWD) and real-world evidence (RWE) to find efficiencies, increase profitability, and fast-track therapies to the right patients. Traditionally, claims data has been the backbone of this effort, providing insights into treatment choices over time. However, in today’s fiercely competitive environment, claims data alone is no longer sufficient. To gain a competitive advantage, companies must leverage the full potential of RWD, particularly data derived from electronic health records (EHRs).

Historically, medical and pharmacy claims data has been the primary resource for informing clinical trial design and patient recruitment. However, claims data has significant limitations that can hinder the trial process.

First, claims data is often delayed. It can 

take up to six months to access certain claims data

, impeding real-time decision-making, which is crucial for efficient drug development. Additionally, claims data lacks clinical context. It focuses on billing and reimbursement, missing key details such as patient symptoms, disease progression, comorbidities, and treatment outcomes—key elements that are essential for robust clinical trial design and execution.

Moreover, some claims data only captures what happens during billed and reimbursed healthcare services. They can also leave out pre-diagnosis and post-treatment details. These gaps make it challenging to identify the right patients that fit a trials’ inclusion and exclusion criteria. For clinical trials, this can cause delays, resulting in higher costs and longer timelines. While claims data can offer some insights into real-world usage, it often falls short of capturing the full picture of how and why therapies were chosen and their subsequent outcomes.

To overcome these limitations, life sciences companies are increasingly turning to EHRs as a richer source of RWD. EHRs offer a comprehensive view of a patient’s medical history, which can be found in structured data (e.g., demographics, encounter details, and condition specifics). But the real value lies in the wealth of unstructured data found in clinical notes, which provide deeper insights into patient experiences and outcomes. This is particularly valuable for clinical trials, where understanding the nuances of patient conditions make it easier to identify the right patients and meet recruitment timelines.

Clinician notes include detailed descriptions of symptoms, clinical reasoning behind diagnoses, or even diagnoses and procedures that are outside of a simple medical ICD code, such as ICD-10, as well as treatment decisions and patient-reported outcomes. This data offers a more nuanced understanding of a patient’s condition and the effectiveness of therapies in real-world settings.

The challenge, however, has been extracting meaningful insights from this unstructured data. Traditionally, this required labor-intensive manual searches, which were time-consuming and lacked scalability. The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized this process. AI and ML algorithms can continuously monitor and analyze vast amounts of patient data, extracting vital information from clinician notes to provide valuable insights into disease progression, treatment, and outcomes.

AI also enables the development of data-driven taxonomies that identify keywords and language patterns associated with specific clinical cues. These curated datasets create a framework for understanding diseases, treatment approaches, and longitudinal outcomes, allowing for more informed decision-making in healthcare.

 of this in action involved a pharmaceutical company facing the challenge of identifying trial sites for a condition without a specific ICD code—chronic induced corneal pain (CICP). By leveraging RWD from a specialized medical registry, the company identified seven new trial sites with high volumes of CICP patients. Four of these sites passed screening, and one became one of the top-performing study sites. This approach not only accelerated the trial process but also ensured that the right patient population was targeted, demonstrating the power of comprehensive RWE in overcoming complex clinical challenges.

The transformative potential of real-world evidence

The ability to leverage RWE effectively has the potential to unlock significant financial impact for pharmaceutical companies. Industry leaders estimate that by integrating RWE into the value chain—informing research decisions, supporting market access, sharpening product strategies, improving pharmacovigilance, and enabling adherence—pharmaceutical companies could unlock upwards of 

The implications of this shift are profound. By tapping into the rich insights offered by EHRs, life sciences companies can not only improve the efficiency of drug development, but also enhance patient care. As the industry continues to evolve, embracing comprehensive and dynamic data strategies will be essential for overcoming the challenges of today’s pharmaceutical landscape.

Industry is turning to enhanced data collection methods in response to high demands for efficiency and profitability. 

The Evolution of Real-World Evidence: Moving Beyond Claims Data in Clinical Trials

Do you know how AI can inform clinical development planning and drive competitive advantage? In this webinar, learn how AI can be used to simulate clinical development pathways, from pre-clinical all the way to post launch, helping to inform clinical development planning to optimize speed, cost and value.

https://www.pharmexec.com/pe_w/successful-clinical-development

As clinical trials increase in complexity and the race to market intensifies, AI/ML methodologies can provide insights that support the probability of technical, regulatory and even commercial success. Predictive modeling, generative AI and other techniques can be layered to help sponsors objectively assess their assets, design better trials and develop strategies to increase speed and value, while reducing costs. This webinar provides an overview of the many ways AI/ML can be applied throughout R&D to guide sponsors in their decision making.



Discover how AI can predict the success of clinical trials in terms of efficacy, regulatory approval, operational feasibility, reimbursement attainment and product uptake.


Understand how AI can help with indication selection and sequencing for an asset, as well as trial parallelization and sequencing, to optimize the value of clinical development plans from a cost, time to market and value perspective.


Explore how AI-powered scenario planning can identify both design and planning risks so sponsors can correct course early on.



 is focused on transforming life sciences with Applied AI. As the VP for Machine Learning, Raja is determined to change healthcare with the power of AI. He believes that imagination is the biggest barrier and motivates his team to create new narratives that fully leverage AI's potential to reshape the industry from R&D through to commercialization. Raja brings together a diverse set of technical and strategic capabilities, including Machine Learning, Deep Learning, Generative AI, Product Development, Life Sciences Expertise and Business Consulting Skills. His team combines data science, domain expertise and consulting skills to create "superhero" change makers who drive impactful change by applying AI to life sciences and healthcare decisions. Raja is a trusted advisor to global life sciences companies, public sector clients, as well as international organizations.



Webinar Date/Time: Wednesday, September 25th, 2024 at 10am EDT | 7am PDT | 3pm BST | 4pm CEST    

Webcasts: Clinical Operations

Webcasts: CRO/Sponsor

Webcasts: Trial Design

Webcasts: Regulatory, Other

Using AI to drive successful clinical development planning

In an interview with Nico Saraceno at DPHARM 2024, Pellegrino highlights current challenges she is seeing in patient recruitment and the use of technology to identify patients. 

DPHARM2024: AutoCruitment CEO Jill Pellegrino Discusses Patient Recruitment

ACT: You hosted a session on how to “Unlock the Power of the Patient for Better Patient Recruitment Outcomes.” What was the premise of the presentation?

 It was talking about a company, AutoCruitment, which focuses on bringing patient recruitment solutions. There's really two primary points I was trying to make in that. One is that to really substantially change the way that clinical trials are enrolled, and to increase the patient number of people that get access to trials, you really have to develop solutions that focus on a very large part of the population that doesn't get the opportunity to participate in trials when you're working through sites alone. We find that only 10% of the patients that are eligible for trials actually get the opportunity to participate in one with the relationships they have with sites. Our recruitment focuses on that other 90% in developing strategies to access that population. That was the first primary point, but the second point is that you have to have in place the right services to qualify those patients to help support the sites and the patients to make sure that they are translating into randomized patients. We talked a lot about the services and the ways that we accomplish that.

ACT: In your experience, what are the most common patient recruitment challenges that you’ve encountered?

 Access to patients is absolutely one of them, but even when you get access to those patients, qualifying them is really, really critical, because the protocols usually have very narrow inclusion/exclusion criteria. A lot of times that inclusion/exclusion criteria can't be validated unless you have a relationship with that patient or have access to their medical history, so depending on the requirements and the complexity of the protocol, sometimes it can be difficult to find patients that are qualified and appropriate for the clinical trial. That's one of the challenges. The other challenge is that you do rely on the clinical trial sites to make a recruitment campaign successful and clinical trial sites are working on a lot of trials right now, and sometimes they're understaffed and they don't have all the resources they need, so you need to be able to have support for those sites to be able to work with the additional patients so that they can capture more patients in their practice, see those patients, and then put them into trials.

ACT: Could you describe what EMR Capture & Intelligence technology is exactly, and how it can help identify and qualify patients?

 Yes, that was EMR Capture & Intelligence, and that's one of the services that we have to help better qualify patients for complex protocols. Patient recruitment companies a lot of the time rely on self-reported data from patients in order to see if they're eligible to refer them to trial sites, so we're not relying purely on self-reported data. We have a new service, EMR Capture & Intelligence, which allows us to get the consent from the patients directly to review their medical records. It's all automated in our technology, where we can collect their medical records very easily for them, and then we have AI-powered technology that reviews those records and organizes that data and assesses it to see if they're eligible for the protocols. We find that is really effective in some of those harder conditions and more complex protocols to be able to find some of those harder to find patients.

ACT: What other sessions or topics at DPharm have piqued your interest?

 I would say an area that's always top of mind and top of interest for me is different strategies to be able to access patients, as I shared. We find that to be really effective in driving higher enrollment rates, you have to be able to reach that 90% of the population, so I find I'm really pleased to see so many companies that are working in this space now looking for creative solutions and ways to find patients, and that's always an area of great interest to me and AutoCruitment.

Latest Conference Coverage

The FDA issued draft guidance that provides recommendations for companies holding multi-regional clinical trials (MRCT) for cancer drugs.

 Trials such as these are important in determining the effect a drug or treatment has on a variety of populations, but they can also produce skewed results. According to a press release from FDA, MRCTs are including shrinking proportions of US citizens, which may make the results less effective for determining the impact on the US population.

As FDA is a US agency, its goal is to determine the safety and efficacy of drugs and treatments on the US population.

In a press release, FDA’s director of its Oncology Center of Excellence and acting director of the Office of Oncologic Diseases in FDA’s Center for Drug Evaluation and Research Richard Pazdur, MD, said, “The FDA encourages sponsors to pursue multi-regional clinical trials, but stresses that such trials should be conducted within the appropriate context. It is important that data from multi-regional clinical trials are applicable to patients in the United States who may use the drug and our current standards of oncological care. The new draft guidance, when finalized, will not only support the agency's review of data generated from multi-regional clinical trials, but also help sponsors improve the generalizability and applicability of results from these trials to the U.S. population and to U.S. medical practice."

This is just the latest draft guidance issued by FDA. In July, the agency issued guidance related to companies responding to misinformation about clear and approved medical products.

In a press release issued at the time, FDA commissioner Robert M. Califf, MD, said, “Regulated industry plays a critical role in ensuring consumers have accurate information about medical products. We've updated our draft guidance to help further ensure industry has clarity and additional flexibility to promptly and proactively issue responsive communications to address misinformation they are seeing. The growing spread of rumors about science and medicine continues to put patients and consumers at risk. We remain steadfast in our commitment to address this public health concern and continue to support and encourage all parties in the public health ecosystem to take an active role."

In June, the agency also issued guidance that provided pharma companies with diversity action plans for clinical trials.

“Participants in clinical trials should be representative of the patients who will use the medical products," Califf said in a press release issued at the time. "The agency's draft guidance is an important step—and one of many ongoing efforts—to address the participation of underrepresented populations in clinical trials to help improve the data we have about patients who will use the medical products if approved."

Also, in April, FDA issued guidance aimed at ensuring the safety of LDTS.

"LDTs are being used more widely than ever before – for use in newborn screening, to help predict a person's risk of cancer, or aid in diagnosing heart disease and Alzheimer's. The agency cannot stand by while Americans continue to rely on results of these tests without assurance that they work," said Califf said. "The final rule announced today aims to provide crucial oversight of these tests to help ensure that important health care decisions are made based on test results that patients and health care providers can trust."

FDA Issues Draft Guidance on Conducting Multiregional Clinical Trials in Oncology. 

. September 16, 2024. https://www.prnewswire.com/news-releases/fda-issues-draft-guidance-on-conducting-multiregional-clinical-trials-in-oncology-302249082.html

FDA Updates Guidance to Further Empower Companies to Address the Spread of Misinformation. 

. July 8, 2024. Accessed September 16, 2024. https://www.prnewswire.com/news-releases/fda-updates-guidance-to-further-empower-companies-to-address-the-spread-of-misinformation-302190916.html

FDA Guidance Provides New Details on Diversity Action Plans Required for Certain Clinical Studies. 

. June 26, 2024. Accessed September 16, 2024. https://www.prnewswire.com/news-releases/fda-guidance-provides-new-details-on-diversity-action-plans-required-for-certain-clinical-studies-302183322.html

FDA Takes Action Aimed at Helping to Ensure the Safety and Effectiveness of Laboratory Developed Tests. 

. April 29, 2024. Accessed September 16, 2024. https://www.prnewswire.com/news-releases/fda-takes-action-aimed-at-helping-to-ensure-the-safety-and-effectiveness-of-laboratory-developed-tests-302130166.html

Multi-region clinical trials can provide for varied results, but may not paint a full picture for a specific population.

NOINDEX

NOFOLLOW

FDA Issues Draft Guidance on Multi-Regional Clinical Trials

One of the first presentations to kick off DPHARM 2024 (following the patient keynote) was hosted by Ken Getz, executive director and research professor, Tufts Center for the Study of Drug Development, Tufts University School of Medicine, centered around “Examining Short and Long-Term ROI of DCT Deployments.”

Getz noted that ROI—or return on investment—is “an extremely important way that we [the industry] persuade and ultimately drive adoption,” in essence, it serves as a way to entice the adoption of an innovation.

His objectives heading into the presentation were to review the past research that measured the short and long term ROI of DCT (decentralized clinical trial) deployments; discuss the on-going techniques that organizations are employing in order to incorporate DCTs into their clinical trial planning and execution processes; and share results from the PACT Consortium, which is essentially a collective of 30 sponsors and contract research organizations who have shared metrics for benchmarking DCT use and impact.

Short-term vs. long-term quantitative ROI assessment

In a nutshell, Getz explained that short-term ROI, is arguably the most meaningful measure today. It's most commonly used for clinical trials during periods where the economy is more challenged—particularly in a softer economic environment—and could be represented by periods of high inflation. However, it’s limited by being narrowly focused, and the fact that it only measures point-based effects.

On the other hand, long-term ROI is utilized in the opposite climate: a robust financial environment, measured during program development.

eNPV modeling—short for expected net present value—is a long-term financial technique used to measure investment value, specifically pertaining to technical, operating, and regulatory risk. It’s run by many major pharma and mid-sized pharma companies, mapping out the outflows (all of the program development costs) and inflows (commercialization revenue).

This model, Getz added, “looks at multiple scenarios, some where a drug will fail, others where it will succeed, and the expected net present value is the average for all of the outcomes in the model.”

And according to Tufts CSDD studies, a Phase III program’s probability of achieving approval is 56%, with with an average overall direct clinical phase cost of $285 million. For additional perspective, Cortellis, Adis Insight data revealed that it takes an average of 10 years for a company to achieve peak sales, which, at the point, could potentially reach a mean of $1.8 billion.

As alluded to above, this collective provides actual DCT use and performance outcomes data from recent clinical trials. It was launched summer 2023, receiving funding from both the Regan-Udall Foundation and Medable.

In the first year alone, members have established governance, define consensus definitions so that they are all on the same page in terms gathering and measure the same qualities, including data on the demographic representation of patients enrolled in the studies that needed to be gathered properly.

For year two, the goals revolve around scaling the data set and conducting much more granular analysis.

Getz K. ROI Keynote: Examining Short and Long-Term ROI of DCT Deployments. September 17, 2024. DPHARM 2024. Philadelphia.

Session reveals how organizations can implement DCTs into their clinical trial planning and execution processes.

George Clinical

Articles

Latest Updated Articles