Unified Data Platform-clinical trial

How a Unified Data Platform Improves Clinical Trial Procedures and Outcomes

Once you’ve collected reams of data, what are you meant to do with it? It’s a question being asked across many industries and, fortunately, for those operating in the clinical trial market, there’s a relatively simple answer: continue.

Keep collecting information from as many relevant sources as possible — but ensure it is processed using a unified data platform. Below, we explore what exactly a UDP should do for clinical trial managers and CROs and how best to use it to improve trial processes and outcomes.

Demand for Uniformity

Regulators and sponsors are both looking for more real-world evidence (RWE), say Olivia Cavlan, Sastry Chilukuri, Matthias Evers, and Ann Westra at management consulting firm McKinsey.

The FDA, for example, is pushing for data from EHRs, claims and registries to be integrated for easier monitoring of records and safeguarding patients. The National Institutes of Health has launched a Common Fund to create infrastructure, improve operational knowledge and promote research that uses all the RWE mentioned above.

Real-world evidence will likely lead to better patient care and improved compliance, the researchers explain. But those pushing the adoption of RWE might face resistance from those more familiar with traditional approaches to producing data, such randomized controlled trials. Still, pharma companies with insightful leaders should see the value of RWE and implement a unified data platform to process it to ensure success over competitors.

Pursuing a Unified Data Model

The clinical trial market used to see clinical data fiercely guarded. However, what is considered relevant and competitive data has narrowed in scope and there is increased value in sharing broader datasets and definitions.

The ultimate goal is to achieve a single data model that links clinical operations, technology and data for increased collaboration, argue Elisa Cascade and Claire Sears, Ph.D. at Applied Clinical Trials. This means companies would retain their competitive secrets but share enough information to make them all more efficient when running trials and processing data.

Yet so far, the unified model remains elusive. Cascade and Sears suggest this is due to significant variation in data formats and fields in different CTM systems. Additionally, there have not been any mechanisms in place to ensure the data is consistent across investigators, sites, companies and systems.

Part of this, they explain, is that companies structure their data in different ways, including syntactic and semantic. The former refers to different meanings between sets of data fields, language for data field labels, vocabularies (ICD-9, MedDRA, MeSH) and terminologies. Semantic, on the other hand, refers to different meanings for the same fields and multiple definitions for types of data.

The solution to solve these syntactic and semantic discrepancies is to implement a unified data model that could easily be aligned with individual companies’ internal CTMS.

Unified Data Model-clinical data

Unified Clinical Is a Cohesive Ecosystem

While a UDP refers to the practical acquiring and processing of clinical data on one platform, Jennifer Goldsmith, SVP at software provider for the global life sciences industry Veeva Systems, goes a step further to talk about the unified clinical philosophy. This refers to improved cooperation and collaboration between all trial teams — both internal and external.

Instead of working in isolation, a philosophy of unified clinical has them completing tasks together in a single end-to-end clinical ecosystem.

By using a common clinical language that harmonizes operational data definitions and a universal operating model within a collaborative environment, the various stakeholders can gain better insights from using UDPs. The result is reduced redundancy and improved decision-making.

A UDP Delivers a Single Source of Truth?

When data is coming from many sources, storing and analyzing it on one platform is essential to make any sense of it, according to the team at Periscope Data.

Patient data collected throughout a trial, for example, might come from reports from physicians, lab tests, medical history, EHRs, wearables and drug prescriptions. The UDP, which should be HIPAA-compliant, is able to break down the various data source silos to collate a single source of truth.

A Unified Platform Will Remedy Fragmented Processes

There are two major mechanisms that can end the fragmented processes that permeate the clinical trial ecosystem, Renee Morad at Scientific American writes.

One is that the industry ubiquitously adopts a UDP to eradicate the multiple and duplicated entries of patient data (often the result of using current siloed technologies). With a single platform, patient data will be more accurate, which will result in greater patient safety, she explains.

Once the data is held in one place, the second mechanism can begin, which is to standardize data gathering and processing across the whole clinical trial industry. A UDP will bring about real-world data capabilities, Morad argues, such as improved data monitoring and medical coding. But organizations will need to evolve their processes to manage the regulatory concerns that will arise.

Remedy Fragmented Processes mechanisms

Speed and Quality Drive Demand for UDP

Many life sciences companies use as many as four different data management applications, Jim Reilly, VP of clinical strategy at Veeva Systems, explains. That’s time-consuming and can lead to data inaccuracies. Overcoming these issues is what’s driving the move towards a UDP, Reilly says.

A UDP allows a CRO team to do all of their trial tasks using one platform. The example Reilly offers is that the CRO can generate site monitoring reports directly in its CTMS or study startup system to become part of the eTMF. This enables better collaboration between CRO and sponsor as there is clear visibility of all processes and outcomes throughout the trial, such as the eTMF, site activations and enrollment statistics.

A UDP enables faster study start up by integrating essential documents, data, protocol and reports. This means it’s easier to source any delays in any processes and remedy them more efficiently. Plus closing down studies is also streamlined using a UDP. The time can drop from weeks to days and quality is far more consistent, Reilly adds.

A UDP Streamlines Data Across Sites

The National Health and Medical Research Council Clinical Trial Centre at the University of Sydney has implemented a UDP to bring together all the data from their electronic data capture systems.

According to Lynne Minion at Healthcare IT News, the university will be able to include sensors, real-world evidence, apps and genomics into the UDP, which will improve data quality and reduce randomization risks. The cloud-based platform will also mean that researchers from multiple trial sites will be able to collaborate more easily with streamlined access to data and enhanced reporting capabilities.

Point-to-Point Integration is Insufficient

While point-to-point integration of data from multiple sources has worked in the past for some trial managers, the sheer volume of data in contemporary clinical trials requires additional integration. Without a more comprehensive or unified platform, there is increased risk to data because the data is not presented in a holistic way, explain Vitthal Gouri and Mathias Poensgen at life sciences industry software solutions provider ArisGlobal.

A UDP not only improves standardization of data, it also ensures better security and privacy, they say. Plus, using a unified platform means it is easier to adopt emerging technologies and integrate them with the platform.

By creating a unified or end-to-end approach, a platform upon which data can be standardized and made uniform, users of the system employ a similar approach for different processes. The familiarity results in more efficient operations and reduced training and onboarding time for new staff.

Ordering the Chaos

Real-world data is what everyone wants, but the reality is that it is “massive, messy, and diverse,” Robert Collins at business analytics software and services provider SAS, asserts.

Furthermore, not many life science organizations are equipped to deal with it. The result is the prevailing fragmentation of data gathered from multiple products that do not integrate with one another. A more formalized data platform is needed then when turning data into useful insights, Collins says.

The future will bring with it even greater amounts of data. With improved wearables and technology aimed at conducting virtual trials, patient data will proliferate while trial staff will likely be working together at multiple sites.

Ensuring that the data collected, processed and analyzed is done so in a uniform manner on a UDP will help improve speed of trial procedures and outcomes. However, it’s worth noting that the UDP is just one aspect of a move towards a unified clinical philosophy whereby all involved work within a standardized paradigm to achieve the best results.

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