## 4 EC, DL, IoMT, and Drug Discovery
By utilizing innovative techniques, such as multicolor multicycle molecular profiling (M3P) technology, in conjunction with staining imaging methods, comprehensive research has shown promising results for advancing drug discovery, molecular diagnostics, and gene-expression investigations. The integration of these cutting-edge technologies is a powerful tool for developing effective vaccines and enhancing our understanding of disease mechanisms. With the potential to accelerate the discovery and development of new treatments, this stage holds great promise for improving healthcare outcomes and advancing scientific research [26]. Layer 3 in the framework comprises the experimental phase of the drug-discovery process, and it is specifically focused on the antigens identified in the previous layer. This stage is critical to drug discovery in various ways, as it enables the analysis and assessment of the adaptive immune system's performance. Repertoire analysis is a powerful tool in this phase, providing insights into how the immune system responds to specific antigens and facilitating the development of new treatments and diagnostic methods. One of the key benefits of this layer is the ability to use novel high-throughput approaches to describe antigen receptors and connect these structures to their specifications in antigens. This can inform the design of more effective treatments and vaccines. By leveraging the power of repertoire analysis and other cutting-edge techniques, this layer represents a critical stage in the drug-discovery process, offering further possibilities for improving healthcare outcomes and developing scientific research. Layer 4 plays a crucial role in developing drugs using animal-envenoming therapy by creating protective immunity in animals. However, traditional animal trials may not be effective in producing some highly efficient antibodies, such as broadly neutralizing monoclonal antibodies. This can lead to increased costs and errors. Therefore, the fifth layer in the drug-development process is an intelligent approach that aims to address these weaknesses and overcome the limitations of traditional animal trials. Layer 5 is designed to predict the effects of animal antibodies when combined with drug candidates. Using the CC platform shown in Figure 1, this layer facilitates the use of DL computations to estimate the behavior of antibodies in human trials. However, due to the limitations of traditional ICT equipment, many companies are turning to CC as an effective approach to combine different data-mining methodologies and handle the vast amounts of data generated by animal trials. As a result, this layer is a strong candidate for analyzing the big data produced by animal trials in Layer 4. By leveraging the power of CC and DL, researchers can more accurately predict the behavior of antibodies in human trials, ultimately leading to more effective drug development and faster times to market. Overall, this layer plays a critical role in the drug-development process by enabling researchers to make informed decisions based on the data generated by animal trials. Layer 6 is designed to serve as an automated platform that uses a combination of cutting-edge technologies, including DL, EC, IoMT, and CC, to facilitate the human-trial  
Figure 1: Proposed AI-Powered Strategy for Vaccine Development: A Seven-Layer Approach from Crystal-Structure Modeling to Approval. This schematic diagram illustrates a novel approach to vaccine development that leverages the power of Artificial Intelligence (AI) across seven layers. The process begins with the modeling of crystal structures, which are shown in the diagram to explain how the proposed method works. By using AI algorithms to analyze large amounts of data and make predictions about vaccine candidates, researchers can optimize the efficacy and safety of potential vaccines.