How Much Is Fragmented Clinical Research Infrastructure Really Costing You?
Clinical research teams don't have a technology problem. They have a fragmentation problem.
A sponsor may use one system for clinical trial management (CTMS), another for electronic data capture (EDC), another for electronic Trial Master File (eTMF), and another for investigator or site management. Essential documents may sit somewhere else. Training records may live in another application. Quality teams may rely on separate tools for risk-based quality management (RBQM) and risk tracking.
All of those systems may work perfectly well on their own.
The problem starts when they have to work together. A site updates its information in the CTMS, but the same information needs to be maintained somewhere else.
Data collection forms are configured in the EDC, while the operational activities and milestones are tracked in the CTMS.
An essential document is uploaded to the eTMF, but the people responsible for the study may need to look somewhere else to understand its status or connect it to a specific site, investigator or study activity.
A quality issue is identified through one system, while the supporting data, documentation and corrective action are managed somewhere else.
None of these is necessarily a major problem on its own.
But multiply them across dozens or hundreds of sites, investigators, documents, milestones and study activities and the operational cost of fragmentation becomes significant.
The Hidden Cost of Clinical Research Technology
When organizations evaluate a new clinical research system, the conversation often starts with the software licence. But the total cost is considerably broader.
A new system can mean:
another implementation project
another integration
another user interface for research teams to learn
another source of data that needs to be reconciled
another vendor relationship to manage
another security and privacy assessment
another system to validate and maintain
another place where information can become disconnected from the broader study record
And these costs don’t necessarily disappear once implementation is complete. They become part of the ongoing operational burden of running the clinical trial.
None of this means specialized clinical research systems are inherently problematic. Many serve important and highly specific purposes.
Does adding another specialized system actually reduce complexity, or does it simply move that complexity somewhere else?
Fragmentation Creates Operational Friction
Consider what happens during a typical clinical trial.
A protocol is finalized.
The study needs to be configured in an EDC. Sites and investigators need to be established in a CTMS. Essential documents need to be collected and maintained in an eTMF or eISF. Training needs to be tracked. Study milestones need to be monitored. Quality risks need to be identified and managed.
In a fragmented environment, these activities may happen across several systems.
The people doing the work may be the same. The study information may be the same. But the systems are not.
That creates opportunities for information to become inconsistent, duplicated or disconnected.
It also creates work that is easy to underestimate: checking, reconciling, exporting, importing, re-entering and verifying information simply to keep different systems aligned.
And the larger and more complex the study becomes, the more important that connectivity becomes.
There is another issue that is particularly important for clinical operations and medical monitors: traceability.
When data, documents, operational activities and quality events are spread across different platforms, reconstructing what happened, and why, can require moving between systems and manually connecting the dots.
A complete clinical trial record should not simply tell you what happened. It should help you understand how the data, documents, decisions and activities relate to one another.
That is the principle behind myLaminin's Trace audit capability: connecting activity across the research environment so that the audit trail is more than a list of isolated events.
ICH E6(R3) Makes the Conversation Even More Important
The move toward Quality by Design (QbD) and risk-based quality management (RBQM) is changing how clinical trials are managed.
ICH E6(R3) places greater emphasis on identifying factors that are critical to trial quality, understanding the risks to those factors, and applying proportionate approaches to trial processes and quality management.
This has an important technological implication.
Clinical research teams need to connect operational activity with the data, documentation, risks and decisions associated with the study. And they need more than visibility.
They need the ability to establish Critical-to-Quality (CrQ) measures and Quality Tolerance Limits (QTLs), monitor them and trigger appropriate action when thresholds are breached
When those pieces are distributed across multiple disconnected systems, maintaining that visibility and oversight becomes considerably more difficult.
The issue isn't simply where the data lives. It's whether the right people can connect the data, documents and workflows when they need to.
What if the Infrastructure Were Connected from the Beginning?
This is the question that led us to build Nucleus, the myLaminin CTMS and the central command or control center.
Rather than building another point solution to the clinical research technology stack, we’ve built a connected clinical research platform in which CTMS, EDC, eTMF/eISF, clinical trial workflows and sponsor oversight can operate together within one unified environment.
The objective isn't to eliminate every specialized technology used in clinical research. It's to reduce unnecessary fragmentation.
One platform. Connected data, documents and workflows.
That means fewer handoffs, less duplication and greater visibility across the clinical trial lifecycle - in real time.
And that connectivity creates the foundation for something more ambitious: Real-Time Clinical Trials (RTCT).
Then we Asked: What Happens When You Add AI?
Connectivity is one part of the equation. The next opportunity is reducing the manual work required to configure and operate a clinical trial.
myLaminin’s AI-Assisted Trial Protocol Generation can take a clinical trial protocol and generate the supporting protocol steps, EDC forms, visitation schedules and RBQM rules for review.
We've now seen what that can mean in practice.
A perfect example of this is we recently onboarded an industry-sponsored cardiac study with an 82-page clinical trial protocol document. In approximately 10 minutes, the AI agent generated the complete protocol steps and all 27 associated EDC forms, ready for CRC review.
The same work would previously have taken a research team approximately a week of manual effort.
That's not about replacing clinical research expertise. The protocol still requires expert review, validation and confirmation.
But the starting point is fundamentally different. Instead of spending days translating a protocol into the operational structure of a clinical trial, researchers can start with an AI-generated foundation and focus their time on review, refinement and the decisions that require human expertise.
We're taking the same approach to clinical trial documentation.
When a document is uploaded to the eTMF or eISF, myLaminin's AI reads it and suggests where it belongs in the DIA TMF Reference Model 3.0. It also picks up the key details an inspector expects, such as document and approval dates, site and country, and offers them as suggestions rather than leaving a blank index form.
Before the document goes into review, an AI-assisted quality check gives it a first pass. It flags files that look misfiled, appear to belong to a different trial, are missing expected attributes or signatures, or contain participant identifiers that shouldn't be in the sponsor file. Each flag comes with a clear reason code.
Nothing is filed or approved automatically. Document specialists still confirm every classification and make the final QC decision, and every AI suggestion, whether accepted, changed or declined, is recorded in the audit trail. What changes is the workload. Instead of hand-indexing hundreds of documents and hunting for missing metadata, teams start from a pre-classified, pre-checked file and spend their time on the exceptions that need human judgement. The result is a more complete, inspection-ready TMF from the moment of upload.
That is where we believe AI can have real value in clinical research: not as a replacement for expertise, but as a way to remove unnecessary manual work and free up more time for patient care.
eTMF and eISF Don't Have to Mean Adopting a Complete CTMS
We've also introduced standalone eTMF, eISF and EDC capabilities.
For some organizations, the priority is modernizing clinical trial documentation without replacing their entire clinical research technology stack.
That should be possible.
A connected platform doesn't have to mean an all-or-nothing implementation. Organizations should be able to adopt the capabilities they need while maintaining appropriate control over their existing environment.
Whether the need is a complete CTMS, an eTMF, an eISF, an EDC, or another component of the clinical trial technology stack, the infrastructure should adapt to the organization, not the other way around.
Federated Clinical Trials: Connecting Without Centralizing Everything
There is another dimension to connectivity that is becoming increasingly important: where clinical trial data is stored.
Global clinical trials may involve sites across Canada, the United States, Europe and other jurisdictions, each operating under its own privacy, security and data-governance requirements.
Connecting those sites does not necessarily mean moving all of their data into one centralized location.
myLaminin is extending its federated data management capabilities to clinical trials, with capabilities planned for market availability in Q4 2026.
The vision is to allow participating sites to retain data within their appropriate jurisdiction while still enabling authorized study participants, sponsors and research teams to work with the information needed to conduct and oversee the trial.
That is a different approach to clinical trial connectivity: connect the research without unnecessarily centralizing the data.
Healthcare research needs infrastructure, not just applications
Clinical research is becoming increasingly digital. But digital doesn't automatically mean connected.
The next stage of clinical research technology should be less about adding another application to an already complicated technology stack and more about asking whether the infrastructure itself can be simplified.
That means considering:
How many systems does a research team need to use to run one clinical trial?
How many times is the same information entered or reconciled?
How easily can a sponsor see what is happening across the study?
Can operational activity, quality oversight and essential documentation be understood together?
And how much complexity has become accepted simply because "that's the way clinical research technology works".
We don't think it has to stay that way and that's the direction we're taking with myLaminin.
One platform for trusted data. Built for compliance.
Our recently redesigned website reflects that evolution, along with significant new capabilities across clinical trials, research data management, document management, AI-assisted workflows and trusted research records.
For healthcare and clinical research organizations in Canada, the United States and beyond, we're building clinical research infrastructure designed not simply to digitize research but to connect it.
Interested in seeing it in action? Contact myLaminin to book a demo.
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Deanne Bassili (article author) is COO of myLaminin, a compliance-first unified Clinical and Research Data Management platform for regulated cross-institution research. With international leadership experience spanning Canada, the United States, and Australia, she writes on research operations, regulatory compliance, digital transformation, and the future of connected research.
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