Expert imaging access for a more connected biomedical research community

ReDIB enters summer 2026 with a clear signal from the scientific community: demand for advanced biomedical imaging continues to grow, and researchers increasingly need not only access to instrumentation, but also coordinated technical expertise, data support, and translational study design.

The first Competitive Open Access call of 2026, REDIB-2601, closed with strong participation across Spain. A total of 24 applications from 15 institutions are now under independent evaluation, with proposals coming from universities, CSIC research centres, national biomedical research institutes, hospitals, health research institutes, and industry partners.

The scientific scope of the call highlights the breadth of the network. Applications span cardiovascular imaging, neuroscience, oncology, rare diseases, tissue engineering, paediatric sleep medicine, novel PET radiotracer development, and imaging technology innovation. Approximately two thirds of the proposals are preclinical and one third clinical, reinforcing ReDIB's role across the translational imaging spectrum.

A particularly important signal is the high demand for expert assistance. Around three out of four applicants requested full technical support, showing that users value ReDIB not only as a route to advanced equipment, but as an expert-led infrastructure that supports researchers from study design to image acquisition, processing, analysis, and interpretation.

Evaluations for REDIB-2601 are now underway. The next opportunity to apply for Competitive Open Access is expected to open in October through the ReDIB web portal. ReDIB's Competitive Open Access route is evaluated on quality and relevance criteria, including scientific and technical relevance, impact, exploitation and dissemination of results, and alignment with ReDIB strategic priorities.

Strengthening capabilities across the network

The latest contributions from ReDIB nodes show a network that continues to renew and expand its biomedical imaging capabilities. These updates include high-field magnetic resonance and spectroscopy, multimodal imaging, nuclear imaging, radiochemistry support, and new computing infrastructure for clinical and biomedical image analysis.

Taken together, these developments strengthen ReDIB's ability to support studies that combine anatomical, functional, metabolic, and molecular information. This is especially important for translational research, where projects often require not only access to advanced equipment, but also expert guidance on protocol design, acquisition, data processing, and interpretation.

Recent equipment and facility updates across the network also reflect a broader shift in biomedical imaging. Imaging infrastructures are increasingly expected to support integrated workflows, from sample or patient preparation through image acquisition, quantitative analysis, and data integration. ReDIB's distributed model helps make these capabilities accessible through a coordinated national infrastructure rather than as isolated local services.

This continued renewal of capability is important for the scientific community using ReDIB. It helps maintain access to modern imaging technologies, supports more complex multimodal study designs, and reinforces the network's role as a shared infrastructure for biomedical discovery.

Data, AI, and clinical image analysis

Biomedical imaging is also entering a more data-intensive phase. Modern imaging studies generate large, complex datasets, and the value of those datasets increasingly depends on secure storage, efficient processing, advanced analysis, and responsible use of artificial intelligence.

A recent example of this direction is the launch of a new high-performance computing data processing centre dedicated to clinical data and medical image analysis. This infrastructure is designed to support advanced AI model development, accelerate image analysis, improve diagnostic workflows, and help research teams collaborate in a more secure and efficient environment.

For ReDIB, this reflects a broader strategic direction. Imaging infrastructures must increasingly connect advanced acquisition with the computational and data-management capacity needed to extract meaningful biological and clinical insight. The future of biomedical imaging will depend not only on the quality of the image, but also on the ability to manage, analyze, and interpret imaging data in ways that are rigorous, reproducible, and useful for researchers and clinicians.

Read more: La Fe CPD-HPC for medical image analysis and AI.

From access to integrated research support

The REDIB-2601 call reinforces an important point: biomedical imaging infrastructure is no longer defined only by scanner access. Increasingly, high-value imaging studies depend on the full research pathway, including study design, acquisition, expert technical support, image processing, data management, computational analysis, and biological or clinical interpretation.

This is particularly important for complex projects that require multiple modalities, specialized acquisition protocols, quantitative analysis, or integration with clinical, molecular, or pathological information. ReDIB's role is to help researchers connect with the expertise and infrastructure needed to turn those research questions into feasible, high-quality imaging studies.

The strong demand for full expert assistance in the latest call shows that users are looking for more than equipment time. They are looking for a coordinated network that can help move projects from concept to execution.

Looking ahead

The first 2026 Competitive Open Access call shows that researchers continue to look to ReDIB for high-value imaging studies across a wide range of biomedical questions. The current evaluation process will identify projects for access in the coming months, while the next call will provide a new opportunity for research teams to connect with the network.

Looking ahead, ReDIB will continue strengthening its role as a coordinated national infrastructure for biomedical imaging: renewing advanced and multimodal capabilities, reinforcing expert support, improving user pathways from project idea to executed imaging study, and supporting the integration of imaging with data-intensive research.