Abstract
The DOE-NIH Joint Workshop on Computational Modeling to Advance Novel Medical Isotopes for Radiotheranostics, held on September 27, 2024, brought together experts from government, academia, and industry to address critical challenges in radionuclide production and clinical translation. The workshop emphasized interdisciplinary collaboration, particularly between the Department of Energy (DOE) and the National Institutes of Health (NIH), to strengthen the domestic isotope supply, streamline regulatory pathways, and further integrate computational tools into radiopharmaceutical therapy (RPT). Key discussions explored the role of AI-driven modeling, machine learning, and digital twin technologies in optimizing dosimetry, dynamically personalizing treatments, and reducing time to clinical adoption. Advances in predictive computational modeling were highlighted as essential for improving radionuclide yield, purity, and synthesis efficiency. Regulatory considerations and equitable access were central themes, with participants advocating for harmonized global standards, adaptive trial designs, and expanded infrastructure for clinical implementation. DOE computational and production infrastructure was emphasized. Future priorities identified include increased investment in radionuclide production infrastructure, expanded workforce development in radiopharmaceutical sciences and computational modeling, and the creation of robust public-private partnerships. The workshop concluded that continued strategic collaboration and sustained resources will be vital for advancing next-generation radiotheranostics, ensuring safe and effective therapies accessible to all patients.
| Original language | English |
|---|---|
| Pages (from-to) | 75-79 |
| Number of pages | 5 |
| Journal | Radiation Research |
| Volume | 204 |
| Issue number | 1 |
| DOIs | |
| State | Published - May 2 2025 |
Funding
We wish to formally acknowledge the following individuals who assisted in organizing the meeting and/or who spoke at the meeting in order of appearance: Ethan Balkin, Ph.D. (DOE), Jacek Capala, Ph.D. (NCI), Tatjana Atanasijevic, Ph.D. (NIBIB), Juana Mendenhall, Ph.D. (Moorehouse College), Christine Chalk (DOE), Bronson Messer, Ph.D. (ORNL and University of Tennessee Knoxville), Tina Morrison, Ph.D. (FDA), Elena Sizikova, Ph.D. (FDA), Eric Stahlberg, Ph.D. (M.D. Anderson Cancer Center), Paul Macklin, Ph.D. (Indiana University), Martin Tornai, Ph.D. (NIBIB), and Emily Greenspan, Ph.D. (NCI). We would also like to acknowledge the team at the DOE who helped organize and manage the meeting and the team at the NCI who helped organize the workshop s website. This research was supported [in part] by the Intramural Research Program of the NIH, National Cancer Institute. Freddy E. Escorcia, FEE is the co-inventor of NCI patent application US Patent Application No. 63/570,344. Radiolabeled Glypican-3 (GPC3)-specific single domain antibody and use thereof as an imaging agent for detecting GPC3-positive tumors. YKD is a consultant for Novartis; RazeBio; GE HealthCares, and MIM Software. AR is a cofounder of Ascinta Technologies Inc. Funding sources: RWH, NIH 5R01CA245139; SD, Research was supported by the US Department of Energy s (DOE s) Oak Ridge National Laboratory Directed Research & Development (LDRD) Program. The isotopes used in this research were supplied by the U.S. Department of Energy Isotope Program, managed by the Office of Isotope R&D and Production. The MD simulations used resources of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which is supported by the DOE Office of Science of the U.S. DOE under Contract No. DE-AC05-00OR22725. Part of the MD simulations used resources of the National Energy Research Scientific Computing Center (NERSC) a DOE Office of Scientific User Facility supported by the DOE Office of Science under Contract No. DE-AC02-05CH11231; AJK, This manuscript has been authored by UT-Battelle LLC under contract DE-ACO5-000R22725 with the US Department of Energy (DOE). By accepting the article for publication, the publisher acknowledges that the U.S. government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-Access-plan); HV, DOE DESC0023467; FEE, reports funding from the Intramural Research Program at the National Institutes of Health (ZIA BC 011800); HH, DOE DESC0022235; YKD, NCI R01CA289631; NCI R01CA240706; NIBIB R01EB022075; AKJ, NIBIB R01EB031962; NIBIB R01 EB031051; NSF CAREER 2239707.