Computational Reduction Vaccine for SARS-CoV-2 Fragment Removal

The patent applies preliminary action by using computational methods to predict and identify problematic fragments before actual vaccine development begins. The system pre-analyzes genomic sequences to predict which fragments are likely to cause issues, allowing researchers to focus only on those specific fragments rather than testing all possible fragments sequentially. This preliminary computational screening significantly reduces the time required while maintaining reliability by targeting only the most problematic sequences.

The patent uses computational models and simulations as copies of the actual vaccine development process. Instead of physically testing each fragment removal scenario, the system creates digital replicas and predictions of how the vaccine will perform with different fragment combinations. This allows thorough evaluation of multiple scenarios without the time cost of actual laboratory testing for each case.

The patent applies segmentation by dividing the complex task of vaccine development into distinct computational stages: fragment identification, prediction scoring, prioritization, and verification. The system segments the genomic sequence into individual fragments and evaluates each independently based on specific criteria (frequency, conservation, predicted impact). This segmentation transforms an overwhelming complex process into manageable discrete steps that can be systematically executed.

The patent uses parameter changes by establishing quantitative thresholds and scoring systems to objectively determine which fragments should be removed. The system changes parameters such as fragment frequency thresholds, conservation scores, and predicted impact ratings to prioritize which fragments warrant removal. These parameter-based decisions simplify the complex judgment process by providing clear numerical criteria for fragment selection.