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Pharmacovigilance

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...

Combination Therapies and Personalized Medicine

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

Dosage Regimen: Individualization

Dosage Regimen: Individualization

Individualization in dosing regimens is the customization of medication doses for individual patients. Its necessity arises from the goal of maximizing therapeutic benefits while minimizing risks. This approach is pivotal because human responses to drugs can vary widely; what is effective for one person may be inadequate or excessive for another. Interpatient (intersubject) variability refers to differences in drug responses between individuals, while intrapatient (intrasubject) variability...

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...

Dosage Regimens: Partial Pharmacokinetic Parameters

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...

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Implementation of In Vitro Drug Resistance Assays: Maximizing the Potential for Uncovering Clinically Relevant Resistance Mechanisms

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Transforming Pharmacovigilance With Pharmacogenomics: Toward Personalized Risk Management.

Claire Spahn¹, Nanase Toda², Blaine Groat³

¹Department of Pharmacy, Stanford Health Care, Stanford, California, USA.

Clinical Pharmacology and Therapeutics

|October 28, 2025

Summary

Pharmacovigilance programs should integrate pharmacogenomic data to improve medication safety. Analyzing genetic markers with AI and ML can reveal insights, reducing adverse drug reactions and enhancing patient outcomes.

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Area of Science:

Pharmacology
Genetics
Computational Biology

Background:

Medication safety relies on pharmacovigilance to detect adverse drug reactions (ADRs) post-market.
ADRs lead to severe health outcomes, including hospitalization and mortality.
Pharmacogenetic markers explain idiosyncratic ADRs, but are not yet standard in reporting.

Purpose of the Study:

To review current pharmacovigilance and pharmacogenomic practices.
To advocate for the inclusion of pharmacogenomics in pharmacovigilance.
To highlight the potential of AI and ML in analyzing pharmacogenomic data for drug safety.

Main Methods:

Literature review of pharmacovigilance and pharmacogenomic integration.
Analysis of the role of pharmacogenetics in ADRs.
Discussion of AI/ML applications in pharmacogenomic data analysis.

Main Results:

Pharmacogenomic data can explain and predict ADRs.
Precision medicine approaches using pharmacogenomics improve clinical outcomes.
AI and ML offer advanced analytical capabilities for complex genetic data.

Conclusions:

Integrating pharmacogenomics into pharmacovigilance is essential for enhancing medication safety.
Pharmacogenomic testing provides valuable data for personalized prescribing.
AI and ML can unlock deeper insights from pharmacogenomic data for public health benefits.