Theranostic digital twins for personalized radiopharmaceutical therapies: Reimagining theranostics via computational nuclear oncology.

This work emphasizes that patient data, including images, are not operable (clinically), but that digital twins are. Based on the former, the latter can be created. Subsequently, virtual clinical operations can be performed towards selection of optimal therapies. Digital twins are beginning to emerge in the field of medicine. We suggest that theranostic digital twins (TDTs) are amongst the most natural and feasible flavors of digitals twins. We elaborate on the importance of TDTs in a future where 'one-size-fits-all' therapeutic schemes, as prevalent nowadays, are transcended in radiopharmaceutical therapies (RPTs). Personalized RPTs will be deployed, including optimized intervention parameters. Examples include optimization of injected radioactivities, sites of injection, injection intervals and profiles, and combination therapies. Multi-modal multi-scale images, combined with other data and aided by artificial intelligence (AI) techniques, will be utilized towards routine digital twinning of our patients, and will enable improved deliveries of RPTs and overall healthcare.

Rahmim A ，Brosch-Lenz J ，Fele-Paranj A ，Yousefirizi F ，Soltani M ，Uribe C ，Saboury B ... -  《Frontiers in Oncology》

Theranostic digital twins: Concept, framework and roadmap towards personalized radiopharmaceutical therapies.

Radiopharmaceutical therapy (RPT) is a rapidly developing field of nuclear medicine, with several RPTs already well established in the treatment of several different types of cancers. However, the current approaches to RPTs often follow a somewhat inflexible "one size fits all" paradigm, where patients are administered the same amount of radioactivity per cycle regardless of their individual characteristics and features. This approach fails to consider inter-patient variations in radiopharmacokinetics, radiation biology, and immunological factors, which can significantly impact treatment outcomes. To address this limitation, we propose the development of theranostic digital twins (TDTs) to personalize RPTs based on actual patient data. Our proposed roadmap outlines the steps needed to create and refine TDTs that can optimize radiation dose to tumors while minimizing toxicity to organs at risk. The TDT models incorporate physiologically-based radiopharmacokinetic (PBRPK) models, which are additionally linked to a radiobiological optimizer and an immunological modulator, taking into account factors that influence RPT response. By using TDT models, we envisage the ability to perform virtual clinical trials, selecting therapies towards improved treatment outcomes while minimizing risks associated with secondary effects. This framework could empower practitioners to ultimately develop tailored RPT solutions for subgroups and individual patients, thus improving the precision, accuracy, and efficacy of treatments while minimizing risks to patients. By incorporating TDT models into RPTs, we can pave the way for a new era of precision medicine in cancer treatment.

Abdollahi H ，Yousefirizi F ，Shiri I ，Brosch-Lenz J ，Mollaheydar E ，Fele-Paranj A ，Shi K ，Zaidi H ，Alberts I ，Soltani M ，Uribe C ，Saboury B ，Rahmim A ... -  《Theranostics》

Role of Artificial Intelligence in Theranostics:: Toward Routine Personalized Radiopharmaceutical Therapies.

We highlight emerging uses of artificial intelligence (AI) in the field of theranostics, focusing on its significant potential to enable routine and reliable personalization of radiopharmaceutical therapies (RPTs). Personalized RPTs require patient-specific dosimetry calculations accompanying therapy. Additionally we discuss the potential to exploit biological information from diagnostic and therapeutic molecular images to derive biomarkers for absorbed dose and outcome prediction; toward personalization of therapies. We try to motivate the nuclear medicine community to expand and align efforts into making routine and reliable personalization of RPTs a reality.

Brosch-Lenz J ，Yousefirizi F ，Zukotynski K ，Beauregard JM ，Gaudet V ，Saboury B ，Rahmim A ，Uribe C ... -  《-》

Digital Twins in Radiology.

Pesapane F ，Rotili A ，Penco S ，Nicosia L ，Cassano E ... -  《Journal of Clinical Medicine》

Digital patient twins for personalized therapeutics and pharmaceutical manufacturing.

Fischer RP ，Volpert A ，Antonino P ，Ahrens TD ... -  《-》