-
Insights from SCOPE | Clinical research is entering a transitional phase of AI adoption — beyond pilots, but not yet autonomous. Explore how modular scaling, human-in-the-loop design, and disciplined governance are shaping the industry’s middle phase and defining what sustainable AI integration truly looks like.
Jun 2, 2026
-
Insights from SCOPE | AI in clinical trials must do more than perform accurately. It must be explainable, traceable, and defensible under regulatory scrutiny. Explore what separates experimental AI from regulatory-grade systems built for trust, transparency, and sustainable enterprise deployment.
May 28, 2026
-
Insights from SCOPE | AI will not transform clinical trials by automating isolated tasks. Real impact comes when workflows are redesigned around structured data, coordinated execution, and built-in governance. Explore how organizations are moving beyond incremental efficiency toward intelligent clinical operating models.
May 26, 2026
-
Insights from SCOPE | Following up on SCOPE X, one message stands out: AI impact depends less on model sophistication and more on data foundations, workflow redesign, governance, and measurable business value. Explore the signals shaping how clinical research is embedding AI responsibly and at scale.
May 21, 2026
-
Insights from SCOPE | AI in clinical development is shifting from experimentation to measurable business impact. Explore where artificial intelligence is truly driving value across startup, enrollment, governance, and portfolio strategy — and why strong data foundations and oversight determine long-term success.
May 19, 2026
-
Insights from SCOPE | Clinical leaders are moving beyond AI experimentation and into real operational decisions. Explore five strategic questions that will shape how artificial intelligence transforms clinical trial design, execution, governance, and human oversight in 2026 and beyond.
May 14, 2026
-
Insights from SCOPE | AI in clinical research has moved beyond pilots. From study startup to risk monitoring and recruitment coordination, real-world use cases are already delivering measurable impact. Explore five practical applications transforming clinical operations before the conversation continues at SCOPE X.
May 12, 2026
-
Insights from SCOPE | Challenges around rare disease recruitment aren't always about patient volume. Precision matters. When eligibility depends on specific mutations or biomarkers, traditional funnels fall short. Learn how mutation-aware outreach and structured data can connect the right patients to the right trials faster.
May 7, 2026
-
Insights from SCOPE | Most recruitment challenges don’t begin when enrollment stalls. They start months earlier in protocol design and feasibility assumptions. Learn how bringing real-world data upstream can prevent downstream delays, reduce screen failures, and improve enrollment predictability before the first patient is contacted.
May 5, 2026
-
Insights from SCOPE | The FDA’s move to pilot real-time clinical trial data access is a signal of where the industry is heading, not a sudden change in direction. For years, clinical operations teams have been working toward faster, more connected ways of generating and acting on data. What’s changing now is who participates in that environment.
Instead of reviewing submissions after the fact, regulators are beginning to explore what it looks like to engage with trial data as it evolves. That shift, from periodic review to continuous visibility, creates an opportunity to rethink how trials are designed, executed, and monitored.
For clinical teams, this is less about disruption and more about alignment with work already in progress.
Apr 30, 2026
-
Insights from SCOPE | CRFs, edit checks, statistical analysis plans, protocol abstractions. Study startup artifacts are highly structured, deeply interdependent, and almost always time-compressed.
They are also repeatable.
Within a therapeutic area, much of the logic behind these artifacts is reused across studies. Visit schedules follow familiar patterns. Edit-check rules draw from established standards. Statistical plan sections mirror protocol language with predictable mappings. Despite this, teams frequently rebuild them manually, adapting prior versions line by line under tight timelines.
That manual rebuild cycle adds weeks to startup and introduces inconsistency that surfaces later during data cleaning or regulatory review.
AI is beginning to change this phase of development, but the real opportunity is not just faster drafting. It is controlled acceleration.
Apr 28, 2026
-
Insights from SCOPE | Artificial intelligence is becoming embedded in more clinical workflows each year. The gains can be real. Time savings are measurable. Repetitive work is reduced. Patterns surface more quickly.
At the same time, a quieter risk is emerging. Low-quality, unverified, or overly trusted AI output can enter regulated workflows unnoticed. In broader technology circles, this phenomenon is sometimes referred to as “AI slop” — content that appears polished and plausible but contains subtle inaccuracies, unsupported assumptions, or contextual errors.
In clinical research, the consequences of that risk are amplified.
Apr 23, 2026
-
Insights from SCOPE | Patient-reported outcomes have come a long way.
What began as paper diaries has evolved into electronic clinical outcome assessments, integrated into study platforms and captured through smartphones and tablets. Each shift in technology brought efficiency gains and, eventually, broader acceptance.
Artificial intelligence now represents the next stage in that evolution.
But applying AI to patient engagement and eCOA requires careful balance. Innovation must be paired with trust, scientific validity, and regulatory confidence.
Apr 21, 2026
-
Insights from SCOPE | For decades, clinical development has followed a familiar pattern. Technology has made each of these steps faster. Electronic data capture replaced paper. Central monitoring improved oversight. Predictive analytics enhanced forecasting.
Artificial intelligence introduces something more fundamental. It creates the possibility of rethinking how evidence is generated across the entire lifecycle, not just how efficiently individual steps are executed.
Apr 16, 2026
-
Insights from SCOPE | Clinical trials run on workflows. Over time, technology has optimized many individual process steps. Automation has reduced manual entry. Dashboards have improved visibility. Predictive models have enhanced forecasting. Yet fragmentation persists.
Most AI deployments to date have focused on improving isolated tasks. The next evolution is different. Agentic AI is shifting attention toward coordinating entire workflows.
Apr 14, 2026
-
Insights from SCOPE | AI pilots are everywhere in clinical research. Small teams test generative drafting tools. Data science groups build predictive enrollment models. Innovation units experiment with workflow automation. Many of these initiatives demonstrate clear potential. Yet a large percentage never move beyond proof of concept.
The gap between demonstrating possibility and achieving production-scale impact is wider than many organizations expect.
Apr 9, 2026
-
Insights from SCOPE | The concept of a “digital twin” has moved from engineering into healthcare. In clinical research, an AI-based digital twin refers to a computational model that simulates how an individual patient might respond under different treatment scenarios. The promise is compelling. Yet digital twins are not a universal solution. Understanding both their potential and their limits is essential.
Apr 7, 2026
-
Insights from SCOPE | Artificial intelligence (AI) has moved well beyond the proof-of-concept phase in clinical research.
Most large sponsors and CROs have experimented with predictive models, generative drafting tools, or automation workflows. Many have demonstrated measurable gains in efficiency within controlled environments.
The real test, however, begins when AI systems move from pilot to production.
In a regulated, global clinical trial environment, production does not simply mean scaling usage. It means operating reliably, audibly, and sustainably under scrutiny.
The transition is not primarily a technical challenge. It is an operational one.
Apr 2, 2026
-
Insights from SCOPE | We all know, clinical research generates enormous volumes of data. And these volumes continue to grow.
Every completed study contains detailed information on endpoints, eligibility criteria, enrollment performance, adverse events, dosing strategies, and operational outcomes. Yet once a trial closes and regulatory submissions are complete, much of that data becomes archival.
It sits in repositories. It is referenced occasionally. It is rarely treated as an active design asset.
This is beginning to change.
Reverse translation, the practice of feeding insights from completed clinical trials back into earlier stages of development, offers a powerful opportunity to improve future study design.
Mar 31, 2026
-
Insights from SCOPE | The first study visit sets the tone for everything that follows.
For patients, screening is their introduction to clinical research. It is where expectations are formed, trust is built, and burden becomes real. For sites, it is often one of the most resource-intensive moments in the trial lifecycle.
Yet screening visits have steadily grown longer and more complex.
Additional laboratory panels, imaging requirements, multiple questionnaires, device training sessions, and layered consent discussions can turn what was once a straightforward evaluation into a multi-hour commitment. In some studies, screening stretches across multiple visits over several weeks.
The impact is rarely neutral.
Mar 26, 2026