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P. Beckhove

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Editorial Open access Jul 2026

The German National Strategy for Gene- and Cell-Based Therapies: Generating Impact by Employing a Novel Multi-Stakeholder Approach

Gene- and cell-based therapies (GCTs) represent a disruptive and transformative class of biomedical innovations. They address diseases by adding, removing, repairing, or replacing genes and/or by endowing distinct living cells with additional biological functions. Through this plethora of options, numerous conditions—including genetic disorders, cancers, and degenerative diseases—have become potential targets for a curative therapy. Thus, GCTs are considered the “Future of Medicine” as they (i) offer a potential cure, particularly for rare and severe disorders previously considered untreatable, (ii) expand the treatment options for common diseases, and (iii) possess the possibility to complement currently applied conventional treatment options. Recognizing both the scientific promise and translational challenges of GCTs, Germany has launched a coordinated national initiative—the National Strategy for Gene- and Cell-Based Therapies. The Strategy was commissioned by the German Federal Ministry of Research, Technology and Space (BMFTR, formerly the German Federal Ministry of Education and Research [BMBF]) and developed through a multi-stakeholder process. The latter involved more than 150 experts from academia, industry, health care sector, professional associations, and patient organizations, who were nominated by the community and assembled into eight working groups to identify current roadblocks and propose possible solutions. Summarized in the Strategy Paper, which was submitted to the BMFTR and published on June 12, 2024, a comprehensive roadmap was developed in this bottom-up process to accelerate the development and clinical implementation of GCTs in Germany. Although it initially had a national focus, the resulting framework is increasingly contributing to the international GCT landscape through growing exchange with GCT initiatives launched in other European member states and with the European Society of Gene and Cell Therapy (ESGCT). In brief, the initiative is focusing on translation starting from research through all steps to clinical application and beyond. This includes workforce development, regulatory frameworks, manufacturing capacity, patient access, and communication with the general public. Numerous targeted measures have been developed by the participating experts in the working groups and are currently being implemented in this broad, collaborative, and bottom-up multi-stakeholder approach. They encompass, for example, the establishment of a website as central information platform, including the GCT-Atlas, a web-based networking and information tool for stakeholders and actors in the GCT field, tailored communication and outreach formats, a Regulatory Support Unit providing independent regulatory guidance for publicly funded early-stage, nonclinical product development, different funding and entrepreneurship programs offering researchers and clinicians financial, educational, and mentoring support, as well as the establishment of translational infrastructure and exchange formats with investors to specifically foster the necessary scale-up and commercialization. Overall, the main goal of the German National Strategy for GCT is to ensure patient access to advanced therapies while strengthening Germany’s position as an international hub for biomedical innovation. To accomplish this, existing resources need to be coordinated, streamlined, and prioritized to increase efficiency and support the long-term sustainability of the system. These objectives are closely aligned with current emerging European initiatives, including the EU Biotech Act and the Horizon Europe work program 2026, which aim to further optimize the framework conditions for this strategically important field and enhance future European competitiveness.

Christian Gallus, F. Ayuk, P. Beckhove et al. · 0 citations
Open access Aug 2026

Superior precision of clinical predictions after CD3-relativisation to align flow cytometry data

Summary Background Flow cytometry captures subtle changes in immune cell distributions caused by disease, but its full potential in medical decision-making is presently limited by technical variability across instruments, sites and time. To accelerate development of generalisable diagnostic, prognostic or predictive clinical tests, we assembled a benchmark flow cytometry dataset over 20 months using 6 cytometers at 4 independent laboratories in Spain and Germany. Cohorts were amalgamated using a new alignment strategy, CD3-relativisation. Methods Four hundred and eighty-two clinical flow cytometry samples from 381 healthy donors and a further 100 samples from post-surgical patients admitted to intensive care were stained with a 10-colour T cell marker panel. To align data from different cohorts, we introduced CD3-relativisation, a method for normalising fluorescence intensities per-channel against CD3 signals. The quality of data alignment was evaluated using optimal transport distances (OTD), clustering consistency and predictive performance. Findings Our fully annotated data resource (Zenodo 17094078) revealed systematic biases in flow cytometry measurements across time, locations and cytometers. CD3-relativisation minimised these biases without sacrificing biological information. Cell clustering performance and sample-to-sample variability improved after relativisation. Consequently, we were able to predict CMV-IgG serostatus, age and sex with superior precision without relying upon external calibrators, measurement of paired samples, batch definitions or data sharing. Models established in healthy control populations were transferable to a cohort of critically unwell, post-surgical patients. Interpretation Our CD3-relativised benchmark dataset establishes a robust standard for evaluating computational methods in clinical cytometry, especially their stability over time and generalisability between instruments, laboratories and clinically heterogeneous populations. Funding This work was supported by the BMS-Foundation (FA-19-009), BZKF (BF/04/R/Hutch), EU-H2020 (Immutol_101080562, exTra_101119855, PAVE_861190), BMBF (01KD2206I) and DFG (403161218).

Gunther Glehr, K. Kronenberg, Fabiola Arella et al. · 0 citations