Author: John Fitts
TLDR
University College Dublin Clinical Research Centre partnered with Vertice to build a patient-led companion app for people living with asthma and Chronic Obstructive Pulmonary Disease (COPD). The app lets patients record their experience in their own voice, in the moment a flare-up happens, and uses retrieval-augmented generation (RAG) to blend that narrative with clinical data and open environmental data such as pollen counts, weather, humidity, and air quality. It was built on Oracle AI Data Platform (AIDP) and taken from concept to a working pilot in a matter of weeks, using fully synthetic patient data and open data sets. As one of the earliest deployments of its kind on Oracle AIDP, it gives patients a way to be heard between appointments and gives clinicians a richer, structured, longitudinal dataset to support better care. The pilot went live in November of 2025, and UCD CRC and Vertice are now scaling the same architecture to further chronic disease and clinical trial use cases.
The UCD Clinical Research Centre and Vertice partnership
UCD Clinical Research Centre was established in 2006 to design and conduct high-quality, patient-centred clinical research. Vertice is an Oracle implementation partner specializing in end-to-end Data & AI solutions, and the two organizations have worked together for several years across a range of research projects. When Vertice gained early access to Oracle AI Data Platform, clinical research was a natural place to start, and UCD CRC’s Executive Director, Colm McMahon, brought Vertice a respiratory care challenge worth solving.
The clinical perspective came from two leading respiratory medicine experts, Cormac McCarthy and Dr Alex Franciosi, working alongside UCD CRC’s respiratory team and its partnership with St Vincent’s Hospital Group. They selected asthma and COPD as the first use case. UCD CRC designed the study and owned the research requirements, while Vertice handled the technical AI-Applied solution design and delivery, allowing clinicians to focus on the nuances of the patient experience.
The Challenge: Capturing the Patient Voice in a 10-Minute Appointment
For someone living with a chronic respiratory condition, the condition is with them every day, yet the window to describe it to a clinician is small. Appointments are often only five or ten minutes long, and weeks or months can pass between them. Compressing months of symptoms, flare-ups, and daily experience into that short window is genuinely difficult. Patients do not always remember the full picture, and clinicians are under pressure to capture as much as possible in the time available.
The result is an information gap. Patients can feel frustrated and unheard, and clinicians work from data that is inconsistent and incomplete. Capturing the patient’s voice accurately and completely in such a condensed setting is the core problem and yet blending that voice with clinical treatment data and environmental factors is exactly what better care depends on.
The Solution: a Patient-Led Companion App Built on Oracle AIDP
UCD CRC and Vertice built a patient-led companion app that captures the patient’s experience naturally, anytime and anywhere, in the moment it happens. Because people are now comfortable talking to conversational interfaces, speaking to the app about a flare-up feels natural. A patient can simply say something like “I felt breathless this morning,” and the app records it.
The app goes well beyond a simple diary. It combines the patient’s qualitative narrative with quantitative open data such as pollen counts, weather, humidity, and air quality. Using retrieval-augmented generation (RAG), it correlates what the patient describes with clinical and environmental data held in the platform, and offers personalized, real-time guidance. For example, it might explain that air quality was good locally but the pollen count was higher than normal, suggest staying indoors until conditions improve, and share a trusted resource such as the asthma action plan from the Asthma Society of Ireland.
This creates a complete and clinically useful picture of a patient’s health over time, blending the human experience of living with the condition with the clinical and environmental context around it.
Why Oracle AI Data Platform Was Key
Vertice chose Oracle AI Data Platform because the solution needed both breadth and depth: a conversational, agentic experience for patients, blended with clinical treatment data and several sets of environmental data, all under proper governance. AIDP brought several things together that made the build possible in the timeframe.
The platform’s AI tooling accelerated development of the chatbot and the analysis and reporting functionality. Its open framework let the team standardize diverse data types using common data models, which matters when you are combining spoken patient narratives with structured clinical and environmental data. Its lakehouse foundation unified that structured and unstructured data in one governed place. And because the work involves sensitive patient information, the security and governance built into AIDP, running on Oracle Cloud Infrastructure, gave the team a trusted platform to build on and to scale.
How the Oracle AIDP Deployment Was Delivered
Vertice managed the governance and compliance aspects of the platform and prototyped a working demonstrator within a number of weeks. The pilot used fully synthetic patient data alongside open data sets, which allowed the team to develop a genuine decision-support tool that can later scale in a fully governed and compliant way once real patient data is introduced.
The application was built on the underlying Oracle AI Data Platform, before the dedicated Oracle Life Sciences AI Data Platform variant was announced. That makes it one of the earliest deployments of its kind, and reflects Vertice’s position as the first to implement Oracle AIDP at scale. The story was featured on Oracle TV at Oracle AI World 2025.
The Impact: Empowered Patients, Better Care
For patients, the app provides a way to be heard between appointments and to take a more active role in managing their own condition. They can capture their experience as it happens and bring a fuller, more accurate account to their clinicians.
For clinicians, the value is a rich, structured dataset. The app converts conversational input into structured data in a common data model, which means the spoken records of many patients can be brought together into a unique dataset of patient-reported outcomes. That complements clinical data and supports longitudinal analysis, helping clinicians track the bigger picture over time, spot patterns, trends, and anomalies, and ask questions of the data in natural language to inform care pathways in chronic disease.
The longer-term impact extends to how clinical time is used. By understanding how patients can be supported in the community using this data, the model supports a shift toward community-based care for chronic conditions, while keeping clinicians connected to what is happening in patients’ real lives. In Colm McMahon’s words, it is all about a better standard of care for patients.
Scaling The Solution: Further Chronic Disease and Clinical Trial Use Cases
The pilot is live and the partnership is ongoing. UCD CRC and Vertice are now scaling the solution and building out an innovation library of reusable use cases. Respiratory disease is the first use case, and the same architecture and framework can be applied to many other chronic conditions and to clinical trials, where capturing the patient experience during a trial is a recurring challenge. Every one of those future use cases relies on the same governed AIDP foundation the partners have already built.
Oracle AIDP for Life Sciences: Use Cases and Faster Time to Value
This project was delivered on the underlying Oracle AI Data Platform, which Oracle launched in October 2025. In January 2026, Oracle announced the Oracle Life Sciences AI Data Platform, a version shaped specifically for pharmaceutical, medical device, clinical research, and healthcare organizations, pre-populated with more than 129 million de-identified longitudinal real-world data records.
For organizations starting out now, that pre-built foundation changes the economics of getting going. Because the Life Sciences platform arrives with curated healthcare datasets, established clinical ontologies, industry-specific tooling, and fully managed infrastructure already in place, much of the groundwork that a team would otherwise build from scratch is ready on day one. That shortens proof-of-concept timelines and speeds up time to value, so a project like the one UCD CRC and Vertice delivered on the underlying platform could move from idea to working use case even faster on the Life Sciences variant. If you want to understand what that platform is, what it does, and what it changes for clinical research, pharma, and MedTech leaders, our plain-English guide explains it in full: What is Oracle AIDP for Life Sciences?
Frequently Asked Questions
What did UCD Clinical Research Centre and Vertice build?
They built a patient-led companion app for people with asthma and COPD. It lets patients describe their symptoms and flare-ups in their own voice, then blends that narrative with clinical data and open environmental data to give patients real-time guidance and clinicians a richer, structured dataset over time.
How does the companion app work?
A patient speaks to the app about their experience, for example noting that they felt breathless that morning. The app uses retrieval-augmented generation to correlate that input with clinical and environmental data such as pollen counts, weather, humidity, and air quality, then offers personalized guidance and trusted resources, and stores the input as structured data for clinical analysis.
What data was used in the pilot?
The pilot used fully synthetic patient data alongside open data sets. This allowed the team to build and prove a working decision-support tool while keeping the path open to introduce real patient data later, under full governance and oversight, as the solution scales.
Why was Oracle AI Data Platform chosen for this Life Sciences use case?
AIDP combined the AI tooling needed to accelerate development of the chatbot and reporting, an open framework for standardizing diverse data with common data models, a unified lakehouse foundation, and the enterprise-grade security and governance required to handle sensitive patient data as the solution scales.
What are other use cases for Oracle AIDP in life sciences?
Other potential use cases of Oracle AIDP for Life Sciences include label expansion, health economics and outcomes research, synthetic control arms, post-market safety monitoring, and regulatory submission support, plus open-ended hypothesis generation through AI agents. The asthma and COPD patient companion app that UCD Clinical Research Centre and Vertice built is a live clinical-research example of the platform in action.
How long did it take to build?
The team took the concept from idea to a working pilot in a number of weeks, prototyping a demonstrator quickly thanks to the AI tooling and managed infrastructure in AIDP.
About John Fitts
John Fitts is a senior business strategist with 25 years translating between the boardroom and the technology stack. As US Vice President for Vertice and CEO of Fairfax Intel, he partners with C-suite leaders on the question most AI and data programs skip: not how, but why.
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