Artificial intelligence and the future of diagnostic and therapeutic radiopharmaceutical development: in Silico smart molecular design

TL;DR

This paper reviews how artificial intelligence-driven in silico methods are transforming the design and development of radiopharmaceuticals, enhancing personalized medicine and precision diagnostics.

Contribution

It provides a comprehensive overview of AI applications in radiopharmaceutical design, highlighting current approaches, challenges, and practical uses in disease-specific contexts.

Findings

AI accelerates radiopharmaceutical discovery process

In silico models improve target specificity and safety

Challenges include data quality and model validation

Abstract

Novel diagnostic and therapeutic radiopharmaceuticals are increasingly becoming a central part of personalized medicine. Continued innovation in the development of new radiopharmaceuticals is key to sustained growth and advancement of precision medicine. Artificial intelligence (AI) has been used in multiple fields of medicine to develop and validate better tools for patient diagnosis and therapy, including in radiopharmaceutical design. In this review, we first discuss common in silico approaches and focus on their utility and challenges in radiopharmaceutical development. Next, we discuss the practical applications of in silico modeling in design of radiopharmaceuticals in various diseases.