AI in Clinical Research Cuts AOVO Workflows to Under Five Minutes
Gold Coast nephrology research facility AOVO uses ORCA Opti Assist to accelerate clinical trial document searches, automate audit trails, and identify tens of thousands of dollars in unclaimed billing items.
AI in clinical research is helping Australian healthcare teams reduce administrative workloads while maintaining access to supporting documentation. Gold Coast nephrology research facility AOVO reports significant time savings after introducing ORCA Opti Assist.
According to AOVO, the AI platform reduced several clinical trial workflows from 30–45 minutes to approximately two minutes. It also shortened new trial evaluations from around 60 minutes to five. Beyond document searches, a single morning’s billing review identified tens of thousands of dollars in previously unclaimed and incorrectly recorded items.
The results highlight how AI could support clinical research administration. However, they also underline the importance of traceable answers, reliable source documents and compliance controls when handling sensitive clinical information.
AOVO, formerly South Coast Renal, operates a private nephrology research facility on Australia’s Gold Coast. It works with commercial sponsors and investigators across multiple studies, including Phase 1–3 multi-centre programmes.
Each study generates extensive documentation, including protocols, laboratory manuals and pharmacy manuals that can contain hundreds of pages of instructions. Staff must search these documents, cross-reference requirements and confirm procedures before making decisions. Every decision must also remain traceable to its source.
These demands create challenges during patient visits, procedural assessments and new trial evaluations. AOVO must also meet Good Clinical Practice (GCP), Therapeutic Goods Administration (TGA), Privacy Act and International Council for Harmonisation (ICH) requirements. As its research portfolio expanded, maintaining these records manually became increasingly difficult.
How AI in Clinical Research Reduced Document Search Times
AOVO first encountered ORCA Opti in 2025. Operations Manager Yupin Robson identified document searching as a major operational bottleneck. Following planning and demonstrations, AOVO began a three-month trial in mid-2026.
The facility initially focused on retrieving accurate answers from clinical trial documents while preserving the evidence supporting each response. The team uploaded protocols, laboratory manuals and pharmacy manuals for three active trials into ORCA Opti Assist.
Coordinators, pharmacists, laboratory staff, and the investigator could then search these documents using everyday language. Rather than manually reviewing hundreds of pages, staff received answers alongside the exact supporting passages.
According to AOVO, the trial produced the following results:
| Clinical Research Task | Previous Time | Time With ORCA Opti Assist |
|---|---|---|
| Answering patient questions during visits | Approximately 30 minutes | Approximately 2 minutes |
| Resolving procedural scenarios | Approximately 45 minutes | Approximately 2 minutes |
| Evaluating new trial opportunities | Approximately 60 minutes | Approximately 5 minutes |
Robson said the benefits extended beyond the time saved on individual tasks.
“That time saving is a really difficult one to answer, because it’s not just an hour. You’re talking about very precious real estate in everyone’s day. And if it saves me 5 minutes, what that 5 minutes possibly could mean is a week’s worth of decision that gets made in that 5 minutes,” said Robson.
The platform also automatically recorded queries, responses, and source references. This created an audit trail designed to support GCP documentation requirements without requiring staff to maintain every record manually.
By the end of the trial, AOVO considered its initial information retrieval problem resolved.
“I feel like we’ve fixed the information for the coordinator. That’s nailed,” said Robson.
Following the trial, AOVO became a paying customer.
AI Billing Review Identifies Thousands in Unclaimed Payments
AOVO subsequently discovered another application for the technology: clinical trial billing reconciliation. Each clinical trial operates under separate contracts, payment arrangements and reimbursement conditions. Staff must compare completed activities against invoices and contractual obligations, which can become time-consuming when several studies operate simultaneously.
Robson began exploring whether ORCA Opti could help identify billing discrepancies. She uploaded invoicing material from one trial into a Knowledge Pack and asked the platform to identify outstanding payments, missing claims, and incorrectly recorded items.
According to AOVO, the review took one morning and identified tens of thousands of dollars in unclaimed and misrecorded items. One discrepancy involved a reimbursement condition that differed from arrangements used across the facility’s other studies.
The platform identified $6,500 in reimbursements that AOVO had not claimed. Staff submitted the invoice immediately, and it entered the payment system. The review also highlighted incorrectly recorded items that had prevented other claims from progressing. Once identified, staff could correct those records.
“Me using ORCA to audit in the finance world has just saved so much time and actually so much confusion,” said Robson.
The billing review demonstrates another potential application for AI in clinical research: comparing operational records against contractual requirements. However, the reported findings come from AOVO’s experience with the platform rather than an independently verified financial assessment.
Expanding AI Into Clinical Research Operations and Compliance
AOVO and ORCA Opti are now exploring additional applications beyond document searches and billing reviews. Their next phase focuses on integrating AI into clinical research operations while linking activities to compliance obligations.
The objective is to reduce repetitive administrative work and automatically capture evidence of completed activities. This approach could help staff maintain more consistent records across different clinical studies.
The organisations are developing several capabilities:
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Patient screening support: Analyse existing clinical correspondence to identify potential research participants who might otherwise be overlooked.
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Milestone and payment tracking: Monitor study milestones and associated payments to reduce manual invoicing work.
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Compliance cross-referencing: Connect TGA, ICH, GCP and Privacy Act requirements with relevant protocol information.
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Glomerulonephritis patient registry: Develop a registry incorporating risk stratification, a clinician review interface, and an append-only audit trail.
The proposed registry addresses challenges in identifying and retaining patients with low-prevalence nephrology conditions. An append-only audit trail would preserve a chronological record of activity without overwriting previous entries.
Such records are particularly relevant in regulated research environments, where investigators must demonstrate how information was accessed and decisions were made. However, these capabilities remain in development and should not be confused with the functions AOVO has already implemented.
Robson said the underlying challenge remains consistent across the different applications.
“If you actually pack the problem up, what is the actual problem that you’re solving? You’re solving the ability to wade through big data very quickly. So the use case is all these different examples, but the problem you’re solving is actually getting through the data,” said Robson.
Why AI Governance and Audit Trails Matter in Clinical Research
Clinical research organisations manage information that requires strict oversight, including patient records, study protocols and financial documentation. Introducing AI into these workflows creates opportunities to improve efficiency, but it also makes accountability and traceability important considerations.
A system that provides an answer without identifying its source can create difficulties when researchers need to verify instructions or demonstrate compliance. ORCA Opti Assist addresses this challenge by displaying supporting document passages alongside responses and automatically logging interactions, according to the company.
These features are intended to help researchers connect operational decisions with documented evidence. Nevertheless, automatically generating an audit trail does not, by itself, establish regulatory compliance. Organisations must still assess their controls, validate relevant processes and meet their applicable obligations.
For clinical research facilities, the distinction matters. Faster access to information offers limited value if staff cannot verify its accuracy or explain how decisions were reached.
Kat Giudes, Founder and Managing Director of Orca Opti, said: “AOVO is the whole idea in one place: connect the documents, get answers in seconds with the source attached, and the audit trail writes itself. No migration, no IT project, just precious clinical time handed back to the team.”
AOVO’s experience illustrates how AI-supported document retrieval and reconciliation can reduce administrative workloads in regulated healthcare settings. The next challenge will be extending those efficiencies across clinical operations while maintaining reliable oversight and documentation.
For more information about ORCA Opti, click here.
About ORCA Opti
Its platform aims to help organisations introduce AI into existing workflows while monitoring their compliance posture against relevant industry standards.