Unlocking Alzheimer's Progress: Advancing Diagnosis and Treatment Through Interdisciplinary Expertise

What is your role in the PREDICTOM project?

I am representing GE HealthCare as the industry lead in PREDICTOM. We collaborate closely with the project coordinator Dag Aarsland to ensure a successful and synchronized execution towards the consortium's common goals. GE Healthcare is responsible for developing and implementing a platform for the early prediction of Alzheimer’s disease (AD). We do this through integrating data, algorithms, automatically extracted features, and resulting predictions. Leveraging our strong expertise in Magnetic Resonance (MR) imaging, we are also focused on discovering MR imaging-based biomarkers.

Why is GE HealthCare as a partner in PREDICTOM best suited to fulfill this role?

GE HealthCare is a leading global medical technology, pharmaceutical diagnostics, and digital solutions innovator, dedicated to advancing precision care. We provide integrated solutions that enhance hospital efficiency, support clinicians' effectiveness, and improve patient outcomes. Our offerings include advanced imaging technologies such as MRI and ultrasound, patient care solutions, and pharmaceutical diagnostics. With a presence in over 160 countries and serving more than one billion patients annually, we bring a unique infrastructure and deep expertise to address the clinical needs of diseases like Alzheimer's. This enables us to rapidly develop and deliver the right solutions to the market.

What is the benefit from participating in PREDICTOM for you as an industrial partner?

First and foremost, innovation typically occurs at the intersection of disciplines. The PREDICTOM consortium offers unique expertises in diverse subject matters, which would rarely converge outside of such a project. Another critical asset of this project is the data. Developing AI-driven solutions for conditions such as AD necessitates access to large datasets, acquired through high-quality, harmonized protocols that consider all aspects of ethics and data privacy. As a MedTech company, GE HealthCare recognizes that collecting large datasets of this nature is most effectively achieved through international collaboration with clinical partners, such as the one in PREDICTOM.

How is the work in PREDICTOM improved with the contributions from industrial partners?

The industrial partners in PREDICTOM are contributing a rich and diverse expertise in medical technologies and pharma. We provide our tools on existing, sometimes already commercially available solutions in disease areas such as AD. Moreover, in PREDICTOM, we bring a solid understanding of which results are less and which are more complicated to be adapted in a clinical environment.

What is PREDICTOM’s vision and what strategy does the project employ to realize it?

Alzheimer's disease leads to a lot of human suffering as well as staggering costs. While significant recent progress has been made in the search for effective therapeutic interventions, it is clear that treatments are most effective when administered at the earliest stages of the disease. Therefore, there is an urgent need to establish scalable, cost-efficient diagnostic markers, tools, and procedures that can identify individuals at increased risk of developing AD. To this end, PREDICTOM will develop a biomarker screening platform which will allow for general population screening for AD from the comfort of people's homes as well as at the general practitioner's office.  The platform will further aid in developing personalized interventions to prevent or delay dementia.

With PREDICTOM, we aim to facilitate a change in current healthcare practices for the early diagnosis of AD by developing new clinical practice guidelines, based on the evidence generated in our study. We will explore the feasibility of innovative technologies for disease risk identification, including digital technologies and novel MRI, EEG, eye tracking, and blood-based biomarkers. By providing a tool that can easily identify those people with early signs of dementia, we expect to significantly decrease the personal and financial burden of dementia in Europe and globally.

Can you tell more about the data platform that will be developed in PREDICTOM?

A data platform is an infrastructure on which software is executed. However, the platform that we will develop in PREDICTOM will be much more than that. It will support the communication between data, algorithms and users. A variety of data will be included, building on previous acquired data in other related initiatives, new incoming data from body-fluid collection, surveys or sophisticated MRI scans, as well as already processed data. The developed algorithms will then provide solutions to process and extract data or aid in identifying features that can be used as biomarkers. The users will initially be researchers, data providers and/or algorithm developers. After that, the platform can be further developed into a clinical tool that meets the needs of clinical users.

Besides the platform, what are the most important assets to be developed?

The work in each work package in PREDICTOM will lead to important outputs. Amongst the most important results we expect to develop is, firstly, the data - which includes the clinical “raw” data, the extracted biomarker data and the validated biomarkers as predictors. Second, the protocol for early symptoms testing, and last, but not least - the resulting industrial-academic network.

PREDICTOM has been running for about a year now. What are the main achievements so far and what lies ahead for the project?

The project is making great progress on many fronts, and we just spent two days in our 1-year general assembly meeting to review the achievements so far. Certainly, there are a few essential milestones we have reached, amongst which are the finalization of the ethics protocol for PREDICTOM's study, the progress for the data sharing agreement and the agreement on many specifics of the platform solution. There are also other milestones we have achieved in the past year, which are laying the foundations to move from a preparation phase to the execution phase of our work.

With the incoming data obtained from PREDICTOM's study participants, we can start testing and maturing the platform in development. Combined with retrospective data, we expect to extract features with new, advanced algorithms. Ultimately, the project will take us to a more sophisticated study phase, where the significance of new Alzheimer's disease predictors can be evaluated.

What is your opinion of collaborations between public and private partners, such as PREDICTOM?

Coordinating a consortium with 30 partners, as we do in PREDICTOM, is undoubtedly a complex endeavor. Aligning deliverables and milestones, addressing all legal concerns, and establishing efficient operating mechanisms are significant undertakings. However, the effort is absolutely worthwhile. There are few other frameworks where public and private partners collaborate as closely towards a common goal over several years, with predefined milestones and deliverables ensuring the necessary rigor.

You are in the lead for sustainability plans when it comes to further use of PREDICTOM’s results after the project ends. What is the importance of developing a sustainability plan for PREDICTOM?

I think the EU is supporting industry-academic collaborations for good reasons. How can you defend these huge investments of tax-payers money, if you cannot demonstrate a good return on investment to the benefit of society? If research should have an impact beyond academic curiosity, it is very important in an early phase of the project to have a common understanding and awareness of what could and should be done with results after the end of the project. Every partner should be sensitized to identify results for future sustainability activities early on, and to take already during the development phase potential “sustainable-by-design” factors into account.