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The preCDD Network as a Model for Academic Preclinical Cancer Drug Development in Germany.

Human gene therapy

Authors: Evelyn Ullrich, Katja Weisel, Michael Hölzel, Thorsten Diegisser, David Krones, Michael Hudecek, Stefan Knapp, Hans Christian Reinhardt

Over the past two decades, oncology has achieved remarkable progress, mainly due to the broad implementation of novel generation immunotherapies. Despite the majority of cancer cases nowadays being curable, a significant portion of cancers remains incurable, highlighting the ongoing gap between biological discoveries and clinically applicable therapies. Marked unmet needs for novel drugs are remaining; at the same time, drug development is nearly exclusively performed by the pharmaceutical industry. For academic drug discovery, a major hurdle in the drug development process is the "valley of death"-the transition from preclinical to clinical stages, where promising academic findings often fail to benefit patients due to a lack of infrastructure, expertise, and funding. The preclinical Cancer Drug Development network (preCDD), which is funded through the Deutsche Krebshilfe (German Cancer Aid), is an ambitious and structurally innovative academic response to this challenge. By bringing together three distinct academic research consortia-TACTIC, THUNDER, and CAR FACTORY-under one comprehensive network, preCDD creates an integrated, nationally distributed platform that encompasses small molecule development, next-generation protein engineering, and advanced cellular immunotherapy. This commentary explores the scientific rationale, organizational structure, and translational potential of the preCDD initiative as a compelling model for how publicly funded academic drug discovery can be systematically organized to bridge the gap between discovery science and clinical application. The initiative also makes expertise, technology, and platforms available to other academic groups to more broadly advance the development of new therapies in an academic setting.

PMID: 42947451

Participating cluster members