Examining Socioeconomic and Computational Aspects of Vaccine Pharmacovigilance
Table 1
Computational challenges in analyzing VAE data: vaccine pharmacovigilance activities can be tedious and long lasting for regulatory authority scientists. Integration with additional resources (e.g., molecular data) may provide new possibilities to augment VAE analytics. Using this approach, we reviewed the extent of polypharmacy and drug interference cases in VAERS.
Computational challenges
Description
Type
Reported VAE content
VAE reporting systems may also contain cases for which it is unclear whether a vaccine caused the VAE. Also follow-up is not always possible. VAE data alone cannot be used to determine a cause-effect relationship between a vaccination and an AE.
Qualitative
Large parts of the data come in free text
Examples include narratives regarding patient medications, laboratory results, or disease history. Advanced text mining or other techniques can be employed for feature extraction, semantics, and rule deduction.
Mining unstructured content
One way to structure VAE data is by mapping content to organized dictionaries and/or hierarchies of therapeutic agents (e.g., vaccines and drugs) or phenotypic manifestations (e.g., diseases, medical conditions, symptoms, side-effects, and reactions). These tasks can be complicated, affected by several factors such as the nonstandard nature of the used nomenclature (e.g., country specific names), nonrelevant content, quality of the entity recognition method used, completeness of the underlying dictionary/hierarchy, annotation coverage, and appropriate representation/detection of relationships.
Quantitative
Automated signal detection
While disproportionality metrics are utilized as the main signal detection standard, there is no sufficient (or universal) definition of a threshold for identified signal strength above which a potential relationship should be considered interesting for further investigation. Also, detected signals may sometimes refer to false positive associations.
