CRO/Sponsor

Clinical Trial Supply Chain

Decentralized Clinical Trials

Early Phase Development

Investigative Sites

Protocol Design

Risk-Based Monitoring

Study Start-Up

Trial Design

Clinical Operations & Strategy

Diversity Action Plans

Industry Initiatives

Recruitment

Analytics

Electronic Data Capture

Metrics & Benchmarks

Real World Evidence

Data Management

CRAACO

Enrollment

Integrated Research

Patient Participation

Institutional Review Board & Ethics Committee

Regulatory

Artificial Intelligence/Machine Learning

eClinical

mHealth

Technology

News

Academy

Publications

All Publications

E-Books

Media

Editorial Podcasts

Editorial Videos

Peer Exchange

Practice Academy

Conferences

Conference Coverage

Conference Listing

Columns

All Columns

A Closing Thought

Clinical Trial Insights

View from Brussels

View from Washington

Resources

Advertise

Blogs

Events

Front & Center

Partner Perspectives

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

DE&I

Topic

1rem

Liz Beatty, co-founder and chief strategy officer, Inato, discusses:

The role of technology in improving site/sponsor relationships

How increased operational costs are impacting the industry

Podcasts

In this episode of the Applied Clinical Trials Podcast, Liz Beatty, co-founder and chief strategy officer, Inato, discusses a number of topics around site engagement including community-based sites, the role of technology in improving site/sponsor relationships, how increased operational costs are impacting the industry, and more. 

Improving Relationships and Diversifying the Site Selection Process

With close collaboration between sponsors, CROs, and regulators, this emerging technology has the potential to greatly improve the lives of patients.

Clinical Strategies to Optimize Software as a Medical Device to treat Mental Health

The challenges, opportunities, and strategic outlook for oncology research centers. 

Scaling eSource-Enabled Clinical Trials: Hospital Perspectives

Leveraging artificial intelligence-powered stochastic methods for clinical data review represents a significant leap beyond traditional approaches.

Revolutionizing Clinical Data Management: The Leap from Deterministic to AI-Powered Stochastic Methods

Understanding the benefits and concerns associated with implementing datasets into clinical trial workflows.

The Backbone of Innovation: High Quality Datasets

Addressing data integrity and compliance concerns.

Collaborative Strategies for Technology Integration in Clinical Studies

In this video interview, Thierry Escudier, portfolio lead, Pistoia Alliance, highlights the need for maintaining data privacy in a highly regulated clinical research industry.

Maintaining Regulatory Adherence with Clinical Technology

, Theirry Escudier, Portfolio Lead, Pistoia Alliance, discussed the alliance’s newest initiative to assess the carbon footprint of clinical trials. The initiative aims to answer whether decentralized clinical trials positively or negatively impact carbon footprints. Escudier also discussed how clinical research stakeholders are slowly beginning to adopt more sustainability practices, focusing on reducing waste and costs.

ACT: What would you say to stakeholders who are still unsure of implementing more clinical technology?

I think it's very much beyond, I would say, the technology itself because, as we can see we are able to speak to each other. I think we have, maybe the Atlantic Ocean between the two of us, and we are still able to interact as we were in the same room, so the technology is there. It's more the question of data privacy in particular, I would say, for patients in using those technologies, we have to ensure that the data privacy is respected. In particular, that for the pharmaceutical sponsor, they shouldn't know anything about the patient identity that should be disclosed and things like this, so there is some of the regulatory, ethics, also difference between, I would say, all countries. Even I would say we have the global ICH E6 that is defining the way clinical studies should be run, but each country may have this their own ethics, let's say mindset, as well as data privacy and therefore, of course, there is sometimes also that fear from the pharmaceutical sponsor side is that, if I'm doing something brand new, is it going to be accepted by the regulatory when I will submit my dossier? That's why, very often the technology is very much, I would say, on line, with the technology of daily life, like even you can look to your bank account, I would say, using the web and so on, and you can interact with friends, but then, as you know, clinical trials are so regulated for the sake of protecting the patient and also the quality of data, that sometimes pharma, I think, is a little bit anxious to move towards those technologies until there is maybe some new guidance. As everyone had to deal with the pandemic crisis, with COVID, of course, there was an increasing speed of trying to adopt some technology, because no one was able to travel anymore, even the patients, they were, I would say, less accepting to travel to the to the sites. The monitors were not able to go anymore to the to the sites to review the source documents, so there was some attempt to try to look to the source documents, but depending on the countries, it might be very difficult. Now that we are back in what I would call a normal situation, after, indeed the very high increase of using technology during the pandemic, there was almost not a shift, but okay, let's come back to what we know, what we master, and let's see how the regulatory will help us, so that's why some of the recent guidance, the one from the EMA and the FDA regarding decentralized components is helping very much the pharmaceutical industry, as well as the CRO service provider and the tech provider to be a little bit more comfortable in the way they can think on implementing those new technologies, but yes, clinical research is a specific word, with a lot of concern for protecting patient data and making sure that you have no deviation, that you have a harmony between standardization across all sides, and of course, depending on the country, it might be very different.

Videos

Addressing Clinical Trial Challenges

ACT: What advancements do you foresee for Medable AI and Medable Studio, and how might these innovations change the way clinical trials are conducted in the coming years?

We designed Medable Studio to scale clinical trial approaches across an entire company, enterprise, portfolio of work, and development asset. That’s one of the key ways we see growth happening. Up until now, we’ve conducted many pilot studies—companies would run a single study to test the approach. We’ve done a lot of those, and we’re now seeing the value they bring. We understand that operating trials this way offers significant benefits but scaling it across multiple trials has been a challenge. However, we’re now seeing companies adopt this approach more broadly.

This isn’t something limited to one or two trials or reserved for Phase IV studies—it’s a model that can be applied across all trials. It enables us to scale in ways that weren’t possible before. Traditionally, scaling innovation required significant human resources, almost like a tax or capital investment. Medable Studio eliminates that burden, making innovation more efficient.

AI further enhances these capabilities. We’ve already integrated AI into some of our tools. For example, building eCOA instruments—a process that once took weeks—now takes minutes, sometimes even seconds. That’s a significant advancement, but it only scratches the surface. Once an instrument is in the library, it never needs to be built again.

We’re also tackling translation, which has been a major bottleneck in running global trials. Eliminating that barrier will bring enormous benefits. Leveraging AI-powered translation tools will further streamline the process.

Beyond these efficiencies, AI is reshaping how clinical trials are conducted. It’s not just about collecting data through eCOA—it’s about passive data collection via sensors and wearables, enabling remote, large-scale monitoring. Additionally, integrating with EHR systems and tokenization vendors allows us to gather richer patient data and answer research questions in new ways. These innovations are fundamentally changing the clinical trial landscape.

: Key factors contributing to success include a strong customer value team with expertise in clinical research, not just technology. The team addresses product adoption, therapeutic area strategies, and patient engagement. A critical element for success is designing trials with patients’ daily lives in mind, ensuring that tasks are non-burdensome and easy to integrate into their routines. For example, in a study with patients suffering from extreme fatigue, notifications were adjusted to be more accessible by changing the timing to align better with patient habits.

Additionally, Medable has gained Canal approval for operating in France, overcoming previous barriers like stricter data protection regulations. This approval enhances confidence in using electronic consent (e-consent) across global trials, improving data security and participant benefits. Furthermore, advancements in AI and tools like Medical Studio are transforming trial operations. AI speeds up tasks like building eco instruments, reducing weeks of work to minutes, and offers solutions to challenges like language translation for global trials. With digital platforms, the company enables broader, scalable approaches for clinical trials across various therapeutic areas. This shift from pilot studies to large-scale implementations aims to enhance trial efficiency and cost-effectiveness across entire portfolios, rather than focusing on individual trials.

Lastly, regulatory bodies are adapting to decentralized trials, with the EMA and FDA releasing new guidelines that support the integration of digital solutions. Despite some regulatory discrepancies, such as the stricter Canal regulations in France, the industry is moving toward broader acceptance of decentralized trials, ensuring that digital tools are compliant with data security and privacy standards. This approach promises to reshape clinical trial methodologies, making them more efficient and accessible globally.

Andrew Mackinnon, Executive GM, Medable, discusses how AI-driven innovations are streamlining clinical trials through enabling scalable operations. 

Video Series

Addressing Clinical Trial Challenges Through AI and Scalable Solutions

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, discusses industry’s next steps in being able to maximize the benefits of virtual models.

Executing with Clinical Technology

, Rachael Higgins, chief commercial officer, PicnicHealth, discussed the company’s recently released 

2025 Annual State of Observational Research Report

. She highlighted some of the key findings including the persistence of more traditional research methods as well as how patient retention and incomplete data are creating challenges for the industry.

ACT: Looking forward, what do you think are the next steps for industry in closing the gap between the need for technology innovation and actually being able to execute with it?

I think it all is going to come down to education and getting our customers comfortable with how new models actually work. It is embracing new technologies that are out there, perhaps it's doing a pilot or doing a softer launch of it, but that way to be able to see that. Number one, it's really not that scary. Number one, it's going to solve your data depth issue, it's going to solve your patient retention issue, it's going to solve your budget issues, just giving it a test trial, if you will. I think that that really is the only way that we're going to be able to do it. When I looked at the results of this report, I saw that 61% of them are already using some type of virtual model in AI, and to me, that's a huge opportunity, because, there's 40 something percent of them that haven't, but I think it's because they truly don't understand what they are, but being open to that, really understanding that there isn't just one way to do things, there are so many other ways to do that, to do what it is to get to your final outcome. Then also, I think, working with regulators, so that regulators become more and more comfortable with the ability to leverage AI and some of the other technologies to get to those endpoints as quickly as possible, to again bring medicines to patients, which is what we're looking to do.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, highlights how addressing these challenges can aid industry in moving more towards the future.

Addressing Data and Patient Retention Challenges

ACT: How can industry address some of the challenges holding it back from moving towards the future such as incomplete data and patient retention?

I think for companies, the life science partners that we do have, I think they truly need to not only say that they're open to things like virtual trials, but actually to be able to embrace them and actually take that leap to be able to do more of that, because that really is the only way to truly do things like getting access to the universal patient record by having patients consent directly, allowing you to get access to their medical record. It is a way that's no burden, or less burden to the patient, and then also give something back to the patient. Things like allowing patients to get access to their medical records and to be able to share their medical records, to be involved in the research, things like that are really going to certainly help them be able to scale up in the ways that they need to be able to do. When you think about all of our customers who are out there and the challenges that they have, I think they're all solvable. I think it's just getting them comfortable in the fact that the old way doesn't have to be the only way, right? There are certainly many ways to skin a cat, and I think these new ways certainly have proven to be effective. I think, again, it's just taking that leap. And then certainly, when you think about where the future is actually going to, the R&D costs are rising tremendously year over year. You see it in the news constantly with our life science partners having to make very significant cuts with not only their staff, thinking about their pipeline, what it is they're going to do, so they have to do more with less, and again, leveraging some of these types of models, virtual opportunities, leveraging direct connection to the patients, leveraging AI, that's going to be able to address their problems, which is going to allow them to scale in the future, which is really what everybody wants, which, again, at the end of the day, is going to be able to bring medicines to patients, which is really what we all want.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, talks traditional research methods in clinical trials and why industry leaders remain reliant on them.

Reliance on Traditional Research Methods

ACT: Why do you think so many industry leaders are still reliant on more traditional research methods?

I think about this all the time. I think this is probably the number one thing that people in my space think about. I think it's just comfort. I think people are comfortable with what they know, right? While the industry has mounting pressures to do things differently, and they know this, it's kind of like the devil you know, right? Even though they find they're spending way more money than they need to, things are taking way too long, they're not retaining patients, they’re certainly not getting the data that they need, they're like, “Well, we know this. It's tried and true, so we're more comfortable doing that.” That being said, as we mentioned those stats before, 78% of the folks that we actually interviewed are definitely open to doing things in other ways. I think it's just going to have to be continually talking to them, educating them, explaining to them that while it is different, different doesn't necessarily mean scary, and it could certainly be advantageous for them in the end.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, discusses findings from the report and the identification of current challenges being faced by the industry.

Implementing Virtual Models in Clinical Trials: Results from PicnicHealth’s Annual State of Observational Research Report

ACT: Could you tell our audience a bit about the 

 and highlight some of its most noteworthy findings?

The research report that PicnicHealth ran basically shows that the industry is definitely at a turning point. The stats show that 80% of the leaders that we interviewed are either using or they're open to virtual models. I think the exact number was 78% and I think this is happening because they are number one, getting pressures from the regulators, payers, and patients for number one, real-world data. They also are leveraging AI and tech-enabled solutions to be able to deliver this in a more systematic, efficient way. If I look at all the stats that were out there, I think one of the major stats that came out is data completeness, and this is the industry's biggest hurdle, 64% of them said that incomplete data is their top challenge and if you think about traditional methods, like a site-based study or a traditional chart review, it just isn't able to deliver that data completeness or capture the entire patient record, if you will, which is why they're actually looking for other options for that. Another area, which again, is no surprise, is patient retention, the loss to follow up with any trial, is one of the biggest issues for life science partners, and they are looking for ways to actually solve that, so having a direct connection to the patient is one of the ways that can increase keeping patients engaged, which then, in turn, would, obviously, enhance the retention. Another thing that we highlighted was 60% of leaders actually flagged that long-term follow up studies was a top priority for 2025 and we know that there are so many pressures and demands on life sciences with all of the cost-cutting measures that are happening, so they're looking for innovative ways to do that. Then last, but certainly not least is AI. If you think about some of the releases from JP Morgan, if you think about some of the questions that folks had answers with our survey, they are having a lot of pressure to leverage AI, not because it's the fun thing to do, but really because it is an innovative, efficient way to really be able to hone in on what it is that you're looking for and then get those answers really quickly. I think 61% of them are either using it or open to actually being able to do that.

In this video interview, Rachael Higgins, chief commercial officer, PicnicHealth, discusses findings from the report and the industry's willingness to adopt technology.

Enhancing Patient Engagement

ACT: Medable has achieved impressive results, such as 90% eCOA adherence. How do you ensure such high levels of participant engagement and data accuracy in decentralized trials?

On the customer value team that I run, there are three key pillars. I mention this because all three are crucial to delivering these kinds of results. My team has extensive clinical research experience. While we may not be the technology experts in the company, we deeply understand clinical research.

One of our groups focuses on product adoption, ensuring that our customers can effectively use the technology. Another pillar is therapeutic area strategy, which examines how our platform performs in different types of studies—whether in oncology, vaccines, or respiratory diseases. We consider the unique nuances of each indication and ensure that study designs align with the needs of specific patient populations.

The third pillar is our site and patient engagement team. We operate under the belief that successful studies require both supported sites and engaged patients. If either element fails, issues arise—often in the form of poor patient adherence and retention. Our site engagement team plays an integral role in all our product development efforts.

Recently, we’ve been re-envisioning how sites interact with our platform. This team has spent extensive time consulting with site staff, nurses, and research coordinators to understand their workflows and challenges. By doing so, we design solutions that genuinely work for them. Even though sites aren’t the buyers, they’re a core user group, and we must ensure our tools are intuitive and effective for their needs.

We apply the same level of engagement when working with patients. For each study, we consult members of our advisory council who have the relevant condition or a similar experience. We ask targeted questions: Would this study design present challenges? How does your condition affect daily life? What obstacles might arise in this workflow?

For example, we recently worked on a study for Sjögren’s syndrome, where fatigue is a primary symptom. Our initial design included compliance notifications prompting patients to complete tasks. However, patient feedback revealed that many wouldn’t be awake to see the alerts. Based on this insight, we adjusted the system—sending one notification earlier in the day and another mid-window when patients were more likely to be awake. This change significantly improved engagement.

We take a patient-centered approach, considering how they live, how their condition affects them, and how we can design studies that fit into their daily lives. Additionally, we ensure that notifications are delivered in the most effective format. A quick push notification might be dismissed immediately, whereas an email can be bookmarked and revisited later.

Our goal is to create a seamless, consumer-grade experience that makes participation easy and intuitive. When you combine clear communication with a frictionless user experience, that’s where the magic happens—it’s our "secret sauce." Many dropouts don’t occur because patients don’t want to comply; they drop out because the process is too burdensome. By reducing that burden, we ensure higher adherence and engagement.

Key factors contributing to success include a strong customer value team with expertise in clinical research, not just technology. The team addresses product adoption, therapeutic area strategies, and patient engagement. A critical element for success is designing trials with patients’ daily lives in mind, ensuring that tasks are non-burdensome and easy to integrate into their routines. For example, in a study with patients suffering from extreme fatigue, notifications were adjusted to be more accessible by changing the timing to align better with patient habits.

Andrew Mackinnon, executive GM, Medable, explains how the company ensures high patient participation and data accuracy in decentralized trials.

Enhancing Patient Engagement and Data Accuracy in Decentralized Trials

In this video interview, Cameron Breze, product manager, Inovalon, highlights current trends with decentralization and how a dual approach can ensure flexibility across different therapeutic areas.

Determining the Effectiveness of Decentralization Across Different Trials 

, Cameron Breze, product manager, Inovalon, discussed challenges in patient recruitment for clinical trials. Traditional recruitment methods, such as manual outreach, are now less efficient due to accessibility issues. Breze highlighted technology as a way to address recruitment challenges, which can be leveraged to automate and streamline processes, reducing labor intensity and errors.

ACT: Is the incorporation of decentralized elements and more remote trials helping with enrollment? Why or why not?

The efforts towards decentralized trials and remote patient recruitment are something that has been birthed out of recent changes in technology, but also socially and culturally, with the COVID 19 pandemic in 2019 to 2020, we really reframed, okay, how can we move research forward within particular constraints? I think it's always going to be a matter of what's the best fit. There are certain trials where that remote or decentralized approach might be best suited. You can think of, say, cream or an ointment for a skin condition where you could take a picture of it with your cell phone. There's no risk to your health in the long term. It's just something that might be visually disturbing you or affecting you mentally. Same thing with a lot of mental health conditions, where you could have therapy that's conducted remotely, or some cognitive behavioral combination of the two, plus an intervention. With that said, there are still trials that will essentially never be remote. There are a lot of more complex biologics that are being released on the market, where they're required to be administered through an IV or some other complex administration method where you have to be at a physical research site. It's not as simple as just taking a pill and then they'll monitor you and maintain that clinical connection as you move through the trial. I think it's something that people have in mind, and I think the most forward thinking organizations have a dual minded approach, where there will always be trials that are optimized for that decentralized approach, and then there are trials that will be better suited for powerhouse academic research centers and everything in the middle, because it will be quite a spectrum, and that will continue to evolve as we get new disease indications that are now accessible to treat. I'm very excited with a lot of the computational chemistry and computational biology methods that are coming out, where we can match, more specifically, to a lot of mild to moderate, genetically inspired disease and treat that through something like a biologic. All of that to say, that dual approach is what I think most organizations will take going forward, and it will continue to bear fruit, and we'll pivot and adapt as the industry moves along with us.

In this video interview, Cameron Breze, product manager, Inovalon, discusses the need for accurate information in creating useful clinical data.

The Role of Quality Data in Utilizing Machine Learning Models

ACT: With so many data sources now in the mix in clinical research, how important is the role of quality data in identifying patient populations?

Quality data is something that is top of mind for everyone in the in the data technology space. Many people like to use the age-old adage of garbage in garbage out when it comes to machine learning models and a lot of the data modeling that's available where if you're feeding it with inaccurate information, you're going to get a result that really can't be transposed and moved and translated into anything that's really applicable and that ends up being a waste of institutional resources and not the best way to serve patients. I can share a little anecdote as well on that. I published a research paper with the MIMIC for critical care database, where we looked at resuscitation, so fluid and IV administration in the hospital with organ failure, and found out through lots of computational modeling that essentially, we had a great record of the fluids that were put in, but not a great record of the fluids put out, so the clinical staff were not recording that, not because they were missing it or they were making some error, but in the scheme of making that particular research impactful, if you don't have that information, you can't make designations on that person's fluid status, and seeing that in aggregate across hundreds of thousands of patients, you get to see what a potential impact that could have had, had that policy or procedure been updated or changed, so I think a lot of those decisions help inform the way that site staff are trained and data is collected over time. Beyond the basics of setting up a system that is going to collect quality data and allow the researchers to interact with it, there's a lot of data vetting that has to go through, so relying on subject matter experts and folks with experience in those particular areas, it's an interesting intersection, where sometimes the person who may be best able to speak to the quality of the data might come from a tech background or a healthcare background where you wouldn't expect that to be the case, typically, so combining interests and having that overlap and Venn diagram and cross pollination of ideas is something that inspires me to work every day and have that overlap and really collaborative effort with a lot of people that I work with and a lot of my other peers in the industry.

In this video interview, Cameron Breze, product manager, Inovalon, talks clinical technology and how the industry is working to increase comfortability with its implementation.

Implementing Technology into Clinical Operations Workflows

ACT: How is technology being used to alleviate some of the current challenges in patient recruitment?

I think there's certainly some give and take when it comes to different biopharma sponsors and then clinical research sites trying to navigate their relationship in terms of what does their trial recruitment effort look like, and how is it going to change with the technology and tools that are available. I think there's always a hesitation with doctors, with clinical researchers, who are already overloaded to learn a more complex tool, a more complex software. I think with a lot of the broader, more consumer facing apps, like you think of the main social media apps, very easy to use when you're ordering food delivery, they've done everything possible to make that experience as easy as possible. I think a lot of that does not necessarily extend into healthcare, so sometimes those apps or technology can be quite difficult to use, so I think there's a an institutional hesitation from both sides to incorporate that technology just because it will send things back quite a bit in terms of how much time you need to sync and train and maintain things. That's something that industry is quite focused on in terms of building out these tools. Yes, we want them to make the impact that we know they're technically capable of making. There's also the human element of building things people actually want to use and simplify their lives, so in any way that we can automate or simplify those workflows, I think that's the focus of technology going forward.

Then again, to hit home on the point with the clinical research sites having quite a site burden, where, if you can imagine, back in the day, if you had a trial for it, with two, three, four, five, exclusion criteria with age, demographic, a particular condition, someone can pretty simply read through or query the EHR and find that information, but when you get to a trial that has the complexity of 15, 20, 30 criteria, even just reading through a list and checking off, yes, no, yes, no, yes, no, that's a pretty labor intensive process when you have to do that on a per patient basis. There are many, many opportunities for error. If you think of a big clinical research team where Person A was working on it yesterday, they're out of office this week, and then someone else is picking up the slack and taking care of their responsibilities for the next few days. If there's communication with them, that's great, but things always kind of fall through your cracks. That's sort of how things work, and having technology there protects you and de-risks a little bit and gives you a more standardized and higher quality output in terms of the research product you put forward. I'm very excited to use those automated elements and structure our efforts in a way that are more scalable, reproducible, and streamlined for everyone involved.

Technology

Latest News