# Social Media Mining for Pharmacovigilance

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2021 · $338,435

## Abstract

Project Summary
Drugs undergo extensive testing in animals and clinical trials in humans before they are marketed for
widespread use. Pre-market testing produces reasonably high quality information about the efficacy of the drug
as a treatment for the condition for which it was approved, but gives a very incomplete picture of the
drug's safety. It is only after a drug is marketed and used on a more widespread basis over longer periods of
time that it is possible to identify other effects, such as rare but serious adverse effects, or those that are more
common in the special subgroups excluded from the trial (such as pregnant women), or effects of long-term use
of the drug, among others. Despite the increase in research in the past years exploring social media data for
pharmacovigilance, and the evidence that it indeed can bring forward the patient perspective, there is no
systematic approach to collect and annotate such data for research purposes. This renewal builds on our prior
research and natural language processing (NLP) methods for social media mining in pharmacovigilance to
make the collection of social media data about medication use precise and systematic enough to be useful to
researchers and the public, alongside established sources such as the FDA's data and other public collections of
drug adverse event data. It presents innovative methods to automatically collect and analyze longitudinal
health data, piloting methods for interventions through the same media that can inform the public and help
validate the automatic methods. As validation, we include a comparison to an existing reference standard for
adverse effects that integrates FDA's data and HER data, as well as specific case studies focused on (Aim 3.1)
the use of NSAIDs and anti-depressants in pregnancy and (Aim 3.2) factors for non-adherence.

## Key facts

- **NIH application ID:** 10409053
- **Project number:** 3R01LM011176-09S2
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** GRACIELA GONZALEZ HERNANDEZ
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $338,435
- **Award type:** 3
- **Project period:** 2012-09-10 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10409053

## Citation

> US National Institutes of Health, RePORTER application 10409053, Social Media Mining for Pharmacovigilance (3R01LM011176-09S2). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10409053. Licensed CC0.

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