This year’s Outsourcing in Clinical Trials (OCT): Medical Devices conference, held in Munich, Germany on 28-29 January, was filled with sessions that dug into the minutiae of matters including clinical trial planning, design, and execution, the importance of good data, and meeting compliance requirements for regulation, from the European Union’s artificial intelligence Act (EU AI Act) to achieving CE mark certification.

AI was a frequent theme on the agenda. The conference featured some compelling insights into the technology’s development and applicability towards helping to evolve patient care, along with several use cases of the technology in supporting the overall clinical trial process.

The prevailing impression is that AI is driving the sophistication of medical devices; however, in turn, cybercrime is also growing more sophisticated and will likely pose a greater threat to the medical device space throughout 2025 than in the previous year.

Planning a clinical investigation

Frank Maier, director of project management at RQM+ hosted a session outlining the practical considerations for conducting a successful medical device clinical investigation, splitting these into three areas: study setup, study conduct, and satisfaction.

Maier explained: “You should draft your documents in line with International Organization for Standardization (ISO) 14155 and other relevant standards.

“A proper submission preparation could help you keep the number of queries from the ethics committees and authorities low.

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“And if you’re working at a contract research organisation (CRO), you should assign a knowledgeable and experienced team to your project.”

Maier views study conduct as being all about proper management, with ISO standards adhered to.

“During the course of the study, you should avoid protocol deviations and other non-compliances,” he said.

“Finally, you should enjoy the work. It’s about satisfaction and that you have a collaborative approach between the sponsor and the CRO, which ensures that timelines, milestones, and expectations are met.”

In his closing remarks, Maier advised that those setting up a clinical study should strive for quality, and the development of a robust study design with the right endpoints to boost study success.

“Safety first, you should use all tools to ensure safety during all phases of the study. For the sake of the patients and the sponsor of the study, consider all costs,” concluded Maier.

Frank Maier, director of project management at RQM+, during his presentation. Image credit: Ross Law / GlobalData

Navigating clinical data demands

Another session covered the matter of navigating clinical data requirements and understanding the regulatory expectations towards attaining CE mark certification for a medical device.

In the presentation, Anna Mayer, lead auditor, Non-Active Medical Devices, at TÜV SÜD, also advised making use of ISO 14155. This document is considered the standard for clinical investigations with medical devices and includes guidance around risk management and breakdowns of key process terminology, to ensure everyone involved in a clinical data-gathering exercise is speaking the same language.

Regulatory complexity, the changing nature of regulation, accessing patients for clinical research projects, staff allocation, the use of technology, and the increasing and high costs are all challenging yet critical aspects of clinical research.

“This is the supply chain, let’s say, from the manufacturer of a medical device to the CRO, clinical research centres and the investigation sites,” said Mayer.

“Taking into consideration the sufficient amount and quality of clinical data and the high costs, this should ideally be a field where the process of clinical data generation is harmonised.”

Mayer also touched on balancing data sufficiency and the practical considerations around what can help to bring all the requirements of a clinical data-gathering process together.

“Coming from a Quality Management System (QMS) approach, it’s about the standard operating procedures, the work instruction, the level of detailed description of processes and the definitions of points of decision-making and the allocation of resources, and the training of the participants.

“I would also like to mention that for stakeholders and manufacturers of medical devices who work with CROs, but also with the organisations that do actually collect the patient data. There are of course different roles that are assigned, and manufacturers see the challenge that they need qualified participants and qualified stakeholders to work with them and provide their expertise for these clinical research projects,” she added.

Anna Mayer, lead auditor, Non-Active Medical Devices, at TÜV SÜD, speaking at OCT Medical Devices 2025. Image credit: Ross Law / GlobalData

The applicability of AI in medtech and clinical trials

Several presentations covered AI from different angles. A talk by Andreas Beust, CEO of CRO GCP-Service, discussed the considerations for AI-driven devices from development to market.

“Besides being a CRO and working with a lot of startup companies, we also entertain the idea of investing in medical device startup companies,” said Beust.

“Therefore, we get to evaluate a lot of early-stage medical device companies who bet on AI, and I see a huge difference in how they approach this development.”

With this insight, Beust’s view is that AI is largely driven by how well companies can control the data from the outset.

“With the perfect data, a lot can be replicated down the line [by competitors], and I think a lot of attention needs to be put into that,” he said.

“Where you start is in mapping out the availability, quantity, and quality of the data that you have or need.

“That must be the foundation of your business plan because, for me, the value of developing AI-enabled devices sits in high-quality data.”

Beust concluded that once you have tested and documented the quality of your data, and built a QMS around it, companies can weigh their options for prospective versus retrospective data collection when they clinically validate their device and iterate their products through updates.

Andreas Beust, CEO of GCP-Service, during his presentation on AI-driven devices from development to market. Image credit: Ross Law / GlobalData

A session by Danish Mairaj, principal engineer of medical device design at RESYCA, highlighted the ways in which AI could be used to enhance clinical trial design and efficiency.

Mairaj started by stating that while AI can inform treatment decisions and make predictions about the likelihood of a surgical procedure succeeding, such decision-making AI is not a replacement for doctors.

“They are still the experts, but AI can help them to make more informed decisions,” said Mairaj.

“Previously, everybody used statistical models to take decision approaches. Anywhere a physician would work, like a clinic or hospital, they used to have certain set of rules or flow diagrams intended to offer some assessment and insight into a patient. And that same idea is now augmented using AI.”

Explaining this notion, Mairaj pointed to devices like smart rings and watches that provide real-world data.

He concluded: “This is one of the areas where AI can use a lot of data, but gaining insights from this data is only possible if you have certain use cases being implemented in relevant facilities.”

Day two of the conference also included a session showcasing the AI-powered annotation function of MILO, a software developed by MILO Healthcare that enables users to build, recruit, and monitor a clinical study from a single platform.

Attendees were particularly impressed by a demonstration, which showed how MILO is able to annotate patient-clinician consultations in real-time and provide a summary of the topics discussed. The software also provided insights into potential next treatment steps based on patient information shared.

This year’s edition of the OCT Medical Devices conference shone a light on how AI is continuing to be an indelible part of the medical device space, in areas including the design of clinical trials and the generation of data, and directly in-build into certain devices to offer assistance in various areas of healthcare.

What seems clear, however, is that while AI is clearly here to stay, so are humans, with AI often serving as more of an augmentation, a tool to fulfil existing, human processes, only more efficiently.