researchportalcentral.com Page 1 | 6 Cells amaze us by showing remarkable resilience to some serious disturbances, while being surprisingly sensitive to minor changes. Creating a digital twin of a cell, a virtual copy of it, will allow different treatments to be tested on a computer before they are used. This will be particularly revolutionary for the treatment of early-stage pre-clinical diseases. Doctors will be able to simulate how different combinations of drugs that might affect a particular pre-clinical disease might affect, potentially avoiding harmful side effects and finding the most effective treatment faster. Detecting early-stage pre- clinical diseases at the molecular level using virtual cells with artificial intelligence is a hot international interdisciplinary research project. This mammoth project requires collaboration across disciplines, industries and countries. Creating virtual cells requires unprecedented collaboration between biologists, computer scientists, mathematicians and many other specialists. The process starts at the molecular level, creating detailed artificial intelligence models of the interactions of DNA, RNA and proteins. These will then be integrated into larger models that show how entire cells function, and eventually scaled up to show how cells work together in tissues and organs. Medical data is collected to identify specific prenosologies at the molecular level. Molecular micro diagnostics are developed and implemented to collect medical data on prenosologies. Solutions are found to neutralize prenosologies using synthesized virtual cells with artificial intelligence. The functionality of synthesized virtual cells with artificial intelligence is formed on the basis of medical data. Medical information is quite specific. Its main feature is the heterogeneity of data, which can be represented as both quantitative (numeric continuous or discrete) and qualitative (categorical ordinal and nominal) variables. Another feature is the long shelf life of medical data. It is also worth noting that the task of storing medical data is complicated by several aspects: the legal significance of the information, its large volume, heterogeneity and complex structure. Health Level 7 (HL7) — the standard for the exchange, management and integration of electronic medical information works with seven levels of open system interaction (OSI). The organization of the medical data storage system begins with the approval of the concept of creating synthesized virtual cells and their modeling, which is decisive in the choice of software and hardware. The creation of synthesized virtual cells will allow identifying diseases at the earliest stage, collecting the necessary data on the state of organs and the body as a whole, making smart analysis, conducting intelligent micro diagnostics and carrying out molecular and genetic healing. prenosology; virtual cell; artificial intelligence; molecular micro diagnostics Abstract Proceedings of the International Academy of Sciences OPEN ACCESS Review Article Early-Stage Detection of Donozology at the Molecular Level Using Virtual Cell with AI Evgeniy Bryndin Interdisciplinary researcher of the International Academy of Education, Russia, Novosibirsk. Introduction to the Problem At the intersection of bioimaging and proteomics are fundamental aspects of human cell biology. It is necessary to determine how human proteins are distributed in time and space, and how variations and biases in localization may contribute to cell type specificity and disease. Compartmentalization of biological processes is a fundamental principle of eukaryotic cells, allowing several processes to occur in parallel. Compartments are specialized for a particular cellular function and contain the molecules necessary for its execution. Defects in compartment organization or protein mislocalization underlie many forms of human disease. Despite a large number of studies, fundamental questions about the spatial organization of many proteins and biological processes remain unanswered. Using computational image analysis, variations in spatiotemporal patterns of protein expression at the level of individual cells are studied in relation to the cell cycle or other deterministic factors. Researchers are creating artificially intelligent virtual cells (AIVC) to replicate the behaviour of real human cells and their components. This innovative concept is transforming biomedical research, personalized medicine, drug discovery, and cell engineering [1-2]. Creating AIVC artificially intelligent virtual cells for early-stage pre-clinical research requires a multi-scale approach. Starting at the molecular level, the system will use AI techniques such as transformers and neural networks to learn representations of DNA, RNA, and proteins from sequence data. These molecular representations will then be integrated into cellular-scale models incorporating data from various experimental techniques such as RNA sequencing How to cite this article: E. Bryndin. (2025). Early-Stage Detection of Donozology at the Molecular Level Using Virtual Cell with AI, Proceedings of the International Academy of Sciences, RPC Publishers, 2(1); DOI: https://www.doi.org/rpc/2025/rpc.pias/00150 Copyright license: © 2025 Evgeniy Bryndin, this is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. *Address for correspondence: Evgeniy Bryndin, Interdisciplinary researcher of the International Academy of Education, Russia, Novosibirsk. Email: Submitted: January 05, 2025 Approved: January 30, 2025 Published: February 08, 2025