Computational Approaches for Logical Biomolecular Complexes Design for Cancer Treatment: A Preliminary Study
: Ngoc, Dzung Lai; Luojus, Maria; Heikkonen, Jukka; Kanth, Rajeev
: Choudrie, Jyoti; Tuba, Eva; Perumal, Thinagaran; Joshi, Amit
: International Conference on Information and Communication Technology for Intelligent Systems
Publisher: Springer Nature Singapore
: 2026
Smart innovation, systems and technologies
: ICT for Intelligent Systems : Proceedings of ICTIS 2025, Volume 13
: 124
: 417
: 426
: 978-981-95-1352-9
: 978-981-95-1353-6
: 2190-3018
: 2190-3026
DOI: https://doi.org/10.1007/978-981-95-1353-6_33
: https://doi.org/10.1007/978-981-95-1353-6_33
The development of cancer therapeutic therapies has made significant advancements in recent years. Numerous innovative solutions have emerged, achieving notable success, including immunotherapy, targeted drugs, and, among them, oncolytic viruses. Oncolytic virus therapy represents the first instance in which humans have employed a biological logic program, rather than a conventional drug, to treat a disease. Despite its promising potential, clinical trials involving oncolytic viruses have not yielded the anticipated outcomes, due to our incomplete understanding of the underlying biological logic and mechanisms. This paper will describe a treatment approach from a biological algorithmic standpoint, encompassing biological logic programs, molecules that carry biological logic (Logical Biomolecular Complexes—LBC), and the existing tools that can be used to design such treatment programs. Our proposal is based on a review of oncolytic virus studies, but the logic framework behind LBCs is tailored specifically for cancer treatment, rather than focusing on replication and spreading. This sets LBCs apart from their viral counterparts and can be considered a new concept.