For example, the component alignment algorithms currently uses the MS1 precursor information to align features across multiple samples while the fragment information also contains crucial knowledge on which features are the same. However, this requires further research on how much information is required to confidently group components from different samples. Meanwhile work is being done to extend and test the algorithms for GC-HRMS data processing. Finally, the predictive models that can use components (i.e., cumulative neutral losses) need to be implemented to use their predicted information during trend analysis (e.g., toxicity) or even alignment (e.g., retention indices).