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Peer-reviewed article · Philippine FDA · 2025Springer Nature logo
Peer-reviewed article

Philippine FDA’s WHO/TDR-funded pharmacovigilance study used AI thematic analysis

Researchers at the Philippine Food and Drug Administration and Philippine Women’s University, studying why adverse drug reactions go underreported, used Evidano to support the thematic analysis of their focus group data. The study was funded by the WHO-hosted Special Programme for Research and Training in Tropical Diseases (TDR) and published in Drugs – Real World Outcomes in 2025.

The study used Evidano, then published as AILYZE.

4,364
healthcare professionals surveyed in the quantitative strand
11
focus group participants: 5 pharmacists, 3 nurses, 3 physicians
5
thematic categories from the focus group data
4
TDR co-sponsors behind the funding: UNICEF, UNDP, World Bank, WHO
The study

Understanding Underreporting of Adverse Drug Reactions in the Philippines: A Mixed Methods Study

Published open access in Drugs – Real World Outcomes, 12(3): 367–381 (Springer, Adis), 2025. The mixed-methods design combined a knowledge, attitudes and practices survey of 4,364 healthcare professionals, a usability evaluation of the national online reporting system, and focus group discussions with clinicians.

The eleven authors include staff of the Philippine FDA’s National Pharmacovigilance Center and the School of Pharmacy at Philippine Women’s University. Ethics approval was obtained from the WHO/TDR Research Ethics Review Committee and the Philippine Women’s University ethics board, and FDA-employed authors were kept out of running the focus groups.

How Evidano fit the workflow

  1. 1
    Capture

    Focus group discussions with 11 healthcare professionals (pharmacists, nurses, physicians) were recorded and transcribed. Each session ran about 60 minutes, and groups continued until data saturation.

  2. 2
    Analyze

    The team ran a thematic analysis using open, semantic, and latent coding. Evidano was used to manage and analyze the transcript data.

  3. 3
    Validate

    Outputs were cross-checked manually. Two independent researchers compared findings and resolved differences to support inter-rater reliability.

  4. 4
    Publish

    The validated themes, grouped into five categories (knowledge, attitude, practice, barriers, strategies), were reported in a peer-reviewed journal in 2025.

“For data analysis, AILYZE Lite—an online tool for qualitative data analysis—was used.”
— From the publication, Methods, Data Analysis (AILYZE is now Evidano)
“...its use was justified in this study owing to its ability to efficiently manage and analyze a large volume of text data while remaining user-friendly for the research team.”
— From the publication · Methods, Data Analysis
“The tool's output was cross-checked manually by the researchers, and the results were validated by comparing them with the initial coding and through manual verification. This ensured the credibility and accuracy of the findings.”
— From the publication
Built for large text data

The authors describe Evidano as able to efficiently manage and analyze a large volume of text data.

Human oversight by design

In the study, Evidano outputs stayed human-reviewable: cross-checked and validated against the team’s own coding by two independent researchers.

Transparent to disclose

Evidano was named directly in the data analysis section, supporting a clear, reproducible methods write-up.

Ethics-reviewed research

Approved by the WHO/TDR Research Ethics Review Committee and a university ethics board.

About Evidano (previously AILYZE)

Evidano is AI-assisted qualitative data analysis software for interviews, focus groups, open-ended survey responses, and documents. It supports AI-assisted thematic analysis with your own or an AI-suggested codebook, transcription and translation in 100+ languages, clickable quotes and citations, and exportable visual reports. End-to-end encryption, no third-party data sharing, and your data is not used to train AI. From USD 50/month for unlimited analysis.

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