DIGITWINS

Digital Twins and Pharmacokinetic Modelling for Precision Radionuclide Therapy: Optimizing Theranostics with Tb-161, FAPi and GRPr

Project objectives and goals

In radioligand therapy, a digital twin is a computational representation of an individual patient that integrates imaging, physiological, and radiopharmaceutical-specific data to predict treatment response and outcomes. These virtual models use physiologically based pharmacokinetic (PBPK) or mechanistic compartmental modelling to predict the biodistribution of therapeutic radiopharmaceuticals prior to therapy. Leveraging pre-therapeutic PET/CT scans enables the prediction of tumour uptake and organ dosimetry. Subsequent therapeutic SPECT/CT scans reduce uncertainty in model predictions and improve predictive performance. Predicting biodistribution, clearance, and radiation dose deposition enables precise treatment planning. This approach supports patient-specific optimization of administered activities to minimize toxicity while maximizing therapeutic efficacy. This data-driven framework transforms radionuclide therapy from a one-size-fits-all approach into a personalized, safer, and more effective treatment strategy for cancer and other diseases.

Based on this concept, the project aims to develop a digital twin framework combined with compartmental models to optimize emerging radionuclide therapies using novel radionuclides such as Tb-161 and molecular targets such as FAP and GRPR:

1. Development of a digital twin framework for personalized radionuclide therapy

a)    Develop patient-specific digital twins by integrating pre-therapeutic PET/CT data to model the biodistribution of novel radiopharmaceuticals (e.g., Tb-161-labelled FAPi).
b)    Incorporate AI-driven models to accelerate and simplify the prediction of therapeutic response, enabling optimization of radiation dose delivery to tumours while minimizing dose to organs at risk (OARs).

       2. Compartmental and dosimetric modelling of emerging theranostic agents

a)    Refine and validate compartmental models using therapeutic SPECT/CT data acquired for the investigated radiopharmaceuticals.
b)    Quantify organ-specific uptake, clearance, and radiation dose to tumours and organs at risk, including uncertainty estimates, to optimize treatment efficacy while minimizing toxicity.
 

Name of the PhD student

PIANOFORTE partner leading the PhD project

Weibo Li (BfS, Germany)

University where the PhD thesis will be defended

Uni Rostock, Germany