Designing Literature Search Strategy

This blog features:

1. Literature Search Strategy
2. Building an Effective Search Strategy
3. Best Practices

Introduction

A weak literature search strategy rarely fails loudly—it fails quietly. It may miss an important case report, overlook an emerging safety signal, or leave critical evidence undiscovered until an auditor, inspector, or regulator identifies the gap.

In pharmacovigilance and clinical research, the literature search forms the foundation of evidence generation. Whether you are preparing a Periodic Safety Update Report (PSUR/PBRER), conducting routine literature monitoring, writing a systematic review, or evaluating a potential safety signal, the quality of your conclusions depends on the quality of your search strategy.

A well-designed literature search should be systematic, reproducible, transparent, and defensible. This article explains how to build an effective literature search strategy for pharmacovigilance and biomedical research.

What Is a Literature Search Strategy?

Millions of biomedical publications are available across numerous scientific databases, including PubMed, Embase, Scopus, Web of Science, and many regional literature sources. Finding relevant evidence requires more than entering a few keywords into a search box.

A literature search strategy is a structured plan that defines:

• The research or safety question
  
• The databases to be searched
  
• Search keywords and controlled vocabulary
  
• Inclusion and exclusion criteria
  
• Filters and limits
  
• Screening methodology
  

Documenting these elements before conducting the search ensures that the process can be reproduced and justified during audits, regulatory inspections, or peer review.

For pharmacovigilance, a search strategy should consistently identify relevant publications while minimising irrelevant results.

Defining the Search Question

Before constructing a search query, the research question should be clearly defined.

For clinical evidence reviews, the PICO framework is commonly used:

• P – Population
  
• I – Intervention
  
• C – Comparator
  
• O – Outcome
  

However, pharmacovigilance literature monitoring often follows a different structure because the objective is not to compare interventions but to identify potential safety information.

A typical pharmacovigilance search may focus on:

• Drug or active substance
  
• Adverse event or safety concern
  
• Patient population (when applicable)
  
• Study type or publication type
  

This approach allows safety professionals to identify adverse drug reactions, emerging safety signals, and relevant case reports more effectively.

Building an Effective Search Strategy

A robust literature search combines multiple search techniques to maximise sensitivity while maintaining acceptable specificity.

The most effective search strategies generally include:

1. Primary Search Terms

Start with the official drug name, active substance, medical condition, or adverse event.

Example:

ibuprofen

2. Boolean Operators

Boolean operators combine search concepts logically.

Examples:

ibuprofen AND hepatotoxicity

ibuprofen OR naproxen

ibuprofen NOT veterinary

Boolean operators are supported by virtually all major biomedical databases, making them the foundation of literature searching.

3. Controlled Vocabulary

Many databases provide controlled indexing terms.

Examples include:

• MeSH (Medical Subject Headings) — PubMed/MEDLINE
  
• Emtree — Embase
  

Controlled vocabulary helps retrieve articles that may use different terminology while discussing the same concept.

Example:

A publication may mention “heart attack” while being indexed under the MeSH term Myocardial Infarction.

Combining controlled vocabulary with free-text keywords significantly improves search sensitivity.

4. Synonyms and Alternative Terms

Different authors often use different terminology.

For example:

(paracetamol OR acetaminophen)

Similarly,

(myocardial infarction OR heart attack)

Including synonyms reduces the risk of missing relevant literature.

5. Phrase Searching

Quotation marks ensure that words are searched together as an exact phrase.

Example:

"drug induced liver injury"

instead of

drug induced liver injury

which may retrieve less relevant results.

6. Wildcards and Truncation

Many databases support wildcard or truncation symbols.

Example:

pediatric*

may retrieve:

• pediatric
  
• pediatrics
  
• paediatric
  
• paediatrics
  

The exact wildcard symbol and behaviour depend on the database being searched.

7. Database Filters

Most biomedical databases allow searches to be refined using filters such as:

• Publication date
  
• Language
  
• Species (Human/Animal)
  
• Age group
  
• Study design
  
• Article type
  
• Author
  
• Journal
  
• Country or affiliation (where supported)
  

These filters help reduce irrelevant results without unnecessarily restricting the search.

8. PICO-Based Search Strategy

When conducting systematic reviews or clinical evidence assessments, the PICO framework helps build highly structured search strategies.

For example:

(Population)
AND
(Intervention)
AND
(Outcome)

This approach is particularly valuable when answering focused clinical questions.

Choosing the Right Search Strategy

There is no single search strategy suitable for every project.

The best approach depends on:

• The objective of the literature review
  
• The type of evidence required
  
• The database being searched
  
• Regulatory expectations
  
• Available indexing and search functionality
  

For routine pharmacovigilance literature monitoring, Boolean operators combined with controlled vocabulary and free-text keywords often provide the best balance between comprehensive retrieval and manageable screening.

For systematic reviews, broader search strategies with validated protocols are generally required.

It is also important to remember that not every literature database supports the same search syntax. While Boolean operators are almost universally supported, features such as proximity operators, field tags, truncation symbols, and controlled vocabulary vary between databases.

Understanding the capabilities of each database allows you to design more effective and efficient search queries.

Best Practices

An effective literature search strategy should:

• Begin with a clearly defined objective.
  
• Combine free-text keywords with controlled vocabulary.
  
• Include relevant synonyms and alternative spellings.
  
• Use Boolean operators appropriately.
  
• Apply filters carefully to avoid excluding important evidence.
  
• Document every search query for reproducibility.
  
• Validate the strategy using known relevant publications whenever possible.
  
• Review and update the strategy periodically as new terminology, products, and safety concerns emerge.

Conclusion

A literature search strategy is only as strong as its weakest documented step. The choice of databases, search terms, Boolean operators, controlled vocabulary, filters, screening criteria, and documentation all contribute to the quality and reproducibility of the final evidence.

A well-planned strategy not only improves literature retrieval but also strengthens regulatory compliance, inspection readiness, and confidence in pharmacovigilance decision-making. By investing time in designing a structured, documented, and validated search strategy, organisations can improve the quality of their literature screening and ensure that important safety information is identified, evaluated, and reported effectively.