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Make It Easy or Lose Them: The New Standard for Patient Retention

6 min

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Discover how Medable's 1:1:1 vision, 1 day startup, 1 day enrollment, 1 year conduct, uses agentic AI to accelerate clinical trials and drug development.

Blog posts

The 1:1:1 vision: Reimagining clinical development

1:1:1

6 min

"The scarcest resource in clinical trials is the time of the highly qualified people running the clinical trials. We need to free up their time to bring more meaningful innovation to patients."

- David Hyman, Chief Medical Officer, Eli Lilly

Since the year 2000, the pace of drug approvals has remained stubbornly slow, with the FDA approving roughly 50 new treatments per year. This pace is in spite of massive increases in R&D investment. It’s well known that clinical trials take 10-12 years on average to complete all four phases. But what if clinical trials didn’t take weeks to start, months to enroll, and years to complete?

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Blog posts

Medable’s Agentic AI connectors and MCPs

Agentic AI

6 min

Medable’s clinical trial platform leverages a robust network of connectors to integrate seamlessly with the systems that power study execution, from EDC and CTMS to collaboration and data platforms. These connectors enable AI to operate across workflows in real time, unifying data, automating processes, and improving coordination across team

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By Asad KhanThere's a particular kind of energy at the World Vaccine Congress that's hard to describe unless you've been in it. Hundreds of scientists, executives, policymakers, pharma leaders, CRO teams, and site networks, all in one convention centre, all sitting with the same fundamental tension. We know how to make vaccines that save lives. So why does getting them to patients still take so long?I spent three days in Washington this week as part of the Medable team. Washington in late March meant that the cherry blossoms were just past their peak but still stunning, and catching them along the Tidal Basin between sessions was one of those small, unexpected gifts that a busy conference week doesn't always make room for.For the conference, I came in with a clear intention. I wanted to reconnect with partners I respect, listen more than I talk, and have honest conversations about where this industry is and where it needs to go. What I didn't fully anticipate was how much the week would reinforce something I already believed but needed reminding of.The urgency is real. And it's shared.The mood in the roomThe congress opened with a keynote from senior US government leadership on federal strategy for public health and pandemic preparedness. The fact that the speaker lineup was still being confirmed close to the event said something in itself. The policy ground under the vaccine industry is shifting, and nobody in that opening session pretended otherwise.Nicole Lurie from CEPI was direct about it during the pandemic preparedness plenary. "We have a long way to go to rebuild trust, not just in the US but globally." That landed with weight in the room. Because the trust deficit isn't just about public perception of vaccines. It runs deeper, into data sharing, into international cooperation, into whether countries will report surveillance information when there are real social and economic consequences for doing so. No platform fixes that. It's a human problem before it's a technology problem.What I kept noticing alongside all of that was a stubborn determination to keep going. Scientists presenting new data, site networks sharing what's working, regulatory specialists wrestling with AI governance frameworks in real time. Nobody was waiting for the policy environment to sort itself out. That resilience is one of the things I find most compelling about this community.The AI conversation nobody's fully figured out yetThomas Waite, Deputy Chief Medical Officer at the UK Department of Health, said something that hasn't left me. "Maintaining public trust when deploying AI surveillance agents is challenging." He also raised the point that if you're training AI on datasets where certain populations are over or underrepresented, you risk making existing inequalities worse. It's not just about what AI can do. It's about how you do it and who it serves.In almost every conversation I had at the congress, excitement about AI's potential existed right alongside genuine uncertainty about whether it can be trusted and governed responsibly. I think both of those things are true at the same time. The potential is real. So is the responsibility. The companies that'll matter in five years are the ones holding both of those thoughts without letting one crowd out the other.The question the whole congress was really askingCristina Cassetti from CEPI and WHO framed something that stuck with me. "How do we weave all responsibilities into one unit? When there's an outbreak, it's always chaotic." The argument from the main stage was that you can't build rapid response infrastructure in the middle of a crisis. It has to already exist.That felt directly relevant to everything I think about in my day job. The systems, processes, and partnerships that let trials move at the speed the science demands have to be in place before the pressure arrives. You can't retrofit speed into something built that is slow.COVID proved that when urgency is real and barriers are genuinely removed, trials can move at a pace nobody thought possible. The question I came to Medable to work on is why that should require a global emergency to unlock. Every unnecessary delay in trial startup or enrollment or conduct is a delay in patient access to therapies that could genuinely change or save lives. That's not a commercial point. It's a human one.What we shared over dinnerOn Tuesday evening Medable hosted an intimate dinner at Ocean Prime for a group of vaccine development leaders. There were small tables, honest exchanges, no polished presentation competing with the actual conversation.Our guests came from right across the clinical trial ecosystem, pharma, biotech, site networks, and CROs. Chief executives, chief medical officers, regulatory leaders, portfolio directors, and clinical operations specialists. People who design trials and people who run them at scale and people who are responsible for the vaccines themselves. The whole ecosystem around one table.I shared Medable's 1:1:1 vision, one day to start a study, one day to open enrollment, one year to complete study conduct. Not as a pitch. As an honest articulation of what we're genuinely building toward and why it matters.What surprised me was how it landed. The response wasn't just polite interest. It was recognition. Immediate and consistent, regardless of where people sat in the ecosystem. Every person in that room had felt that friction from their own angle.My colleague Toai then gave a live demonstration of some of the technology behind that vision. Watching the room engage with it, the questions people asked, the connections they drew to their own programmes, reminded me why showing something real matters so much more than describing it. One result I shared made that concrete in a way no slide ever could. A recent vaccine megatrial we supported delivered 100% cohort enrollment within five days, at a scale where weeks or months would've been completely normal. That study became a blueprint, that blueprint became a programme, and three additional vaccine trials launched immediately after. Nobody needed me to explain what that meant. They'd all lived the alternative.The conversation that mattered mostHowever, the most memorable part of the evening came up naturally around the table and it's stayed with me more than anything else from the week.The people in that room care deeply about what they do. They're genuinely invested in vaccine development, they live the science,and they want to get safe and effective vaccines to the people who need them. That passion was unmistakable.Yet, almost every person there described being held back by the same things. Manual processes. Paper. Operational friction that really shouldn't exist in 2026. Systems designed around how trials used to run rather than how they need to run now.What came through just as strongly was a real fatigue with vendors. Not with technology. With a particular kind of vendor relationship where someone sells you a solution without ever truly understanding your problem, where the pitch is confident but the partnership is thin. Where you end up feeling like a number rather than a partner.That hit me hard, because I think it's the most honest thing the industry is trying to communicate to technology companies right now. Better tools aren't enough on their own. Real partnership combined with the right technology is what'll actually shift the status quo. You can't have one without the other. It's also the standard I try to hold myself to, and a conversation like that one is a reminder of why it matters.What I'm taking awayThe policy environment is genuinely uncertain and the congress didn't try to dress that up. The questions around AI governance and trust are real and unresolved. But what I felt most strongly across the whole week was something much simpler. The people in this industry are committed to getting it right. The challenge isn't will or capability. It's the infrastructure and the processes and the weight of how things have always been done.The work is urgent. The community doing it is serious. And what'll move it forward isn't technology on its own. It's technology in the hands of people who've taken the time to genuinely understand the problem they're there to solve.That's why I do this. A week in Washington reminded me not to take it for granted.‍‍

Blog posts

From the Congress floor to the dinner table: A Week in Washington that reminded me why this work matters

Vaccines

6 min

There's a particular kind of energy at the World Vaccine Congress that's hard to describe unless you've been in it. Hundreds of scientists, executives, policymakers, pharma leaders, CRO teams, and site networks, all in one convention centre, all sitting with the same fundamental tension. We know how to make vaccines that save lives. So why does getting them to patients still take so long?

I spent three days in Washington this week as part of the Medable team. Washington in late March meant that the cherry blossoms were just past their peak but still stunning, and catching them along the Tidal Basin between sessions was one of those small, unexpected gifts that a busy conference week doesn't always make room for.

For the conference, I came in with a clear intention. I wanted to reconnect with partners I respect, listen more than I talk, and have honest conversations about where this industry is and where it needs to go. What I didn't fully anticipate was how much the week would reinforce something I already believed but needed reminding of.

The urgency is real. And it's shared.

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White papers, Case studies & reports

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White Papers, Case Studies, Reports

From three meetings to one removing bottlenecks with AI-enabled eCOA

eCOA

6 min

Discover how AI-enabled eCOA and agentic workflows reduce clinical trial startup time, translation cycles, and meeting overhead—cutting eCOA build timelines from 16–20 weeks to under 8 weeks.

White Papers, Case Studies, Reports

Case study: Scaling global vaccine mega-trials for a top-5 pharma

Vaccines

6 min

Learn how Medable enabled a top-5 pharma to scale vaccine mega-trials with near-100% enrollment, real-time safety data, and >90% diary compliance.

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White Papers, Case Studies, Reports

Case study: ICON and Medable drive 85% eConsent adoption in U.S. menopause study

eConsent

6 min

How do you drive adoption in a complex women’s health study? See how ICON and Medable reached 85% eConsent uptake across 1,200+ participants with a smarter, site-first approach.

On-Demand Webinars

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Webinar cover image for The AI Pilot Trap and How Clinical Trial Leaders Can Escape It

Webinars

The AI Pilot Trap and How Clinical Trial Leaders Can Escape It

6 min

Most AI pilots in clinical trials fail to scale beyond proof of concept. Learn practical strategies for moving from isolated experiments to enterprise adoption.

Webinar cover image for Harnessing AI for more efficient clinical trials

Webinars

Harnessing AI for more efficient clinical trials

6 min

Explore how AI is transforming clinical trials, from accelerating data analysis to predicting trial outcomes.

Webinars

If patients withdraw, critical data Is lost: Rethinking long-term follow-up in C&GT Trials

Cell and Gene Therapy

6 min

This session explores a digital-first approach to long-term follow-up designed to sustain participant engagement, reduce attrition, and maintain scientific and regulatory rigor for cell and gene therapies.

Scientific Research

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Research

Assessing the financial value of decentralized clinical trials

Decentralized Clinical Trials

6 min

Deployment of remote and virtual clinical trial methods and technologies, referred to collectively as decentralized clinical trials (DCTs), represents a profound shift in clinical trial practice. To our knowledge, a comprehensive assessment of the financial net benefits of DCTs has not been conducted

Research

Development of a mobile health app (TOGETHERCare) to reduce cancer care partner burden: Product design study

eCOA

6 min

Research looking at mobile apps and how they may provide a meaningful access point for all stakeholders for symptom management.

Guides

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Guides

The best AI tools for remote patient monitoring in clinical trials

Remote Patient Monitoring

6 min

AI-powered remote patient monitoring (RPM) is transforming clinical trials by enabling continuous data collection, real-time insights, and decentralized participation. This ecosystem spans wearables, AI analytics, data platforms, and decentralized clinical trial (DCT) infrastructure.

Additionally, agentic AI is fundamentally reshaping remote patient monitoring (RPM) in clinical trials by shifting it from passive data collection to proactive, autonomous decision support. Instead of simply aggregating data from wearables and patient-reported outcomes, agentic systems can continuously analyze multi-source trial data, identify emerging risks, and take action, such as prioritizing at-risk patients or sites, triggering alerts, or recommending interventions, without waiting for human input. This significantly reduces delays in detecting safety signals or protocol deviations. Just as importantly, agentic AI introduces workflow automation at scale by handling routine monitoring tasks, coordinating communications, and maintaining audit-ready reasoning trails. The result is a more adaptive and responsive RPM model where clinical teams move from manual oversight to strategic supervision, enabling faster, safer, and more efficient trials.

Below is a structured overview of the leading vendors, tools, and providers enabling AI-driven RPM in clinical research.

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Guides

eCOA, AI, and Agentic AI: A practical overview and guide

eCOA

6 min

Combining artificial intelligence (AI) and agentic AI with electronic Clinical Outcome Assessment (eCOA) systems fundamentally enhances how clinical trial data is collected, interpreted, and acted upon. At its core, eCOA captures structured data directly from patients, clinicians, or observers, such as symptom severity, quality of life, or functional outcomes. Modern platforms expand this further by supporting a full range of assessment types, including electronic patient-reported outcomes (ePRO), clinician-reported outcomes (eClinRO), observer-reported outcomes (eObsRO), and performance outcomes (ePerfO).

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Guides

eCOA vs ePRO: Understanding the differences in clinical trials

eCOA vs ePRO

6 min

Digital data capture has become essential to modern clinical research. Sponsors and research organizations increasingly rely on electronic outcome assessment tools to collect high quality patient data, reduce manual errors, and improve regulatory compliance.

Two terms appear frequently in this space: eCOA (electronic Clinical Outcome Assessment) and ePRO (electronic Patient Reported Outcome).

These terms are closely related. However, they are not interchangeable.

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