Many organisations in the animal-health sector struggle with significant challenges in veterinary pharmacovigilance, from inconsistent reporting to inadequate species-specific data. These obstacles not only hinder timely risk detection but can compromise animal safety, regulatory compliance and product credibility. By adopting a structured pharmacovigilance framework that addresses these pain points head-on, companies can turn these challenges into opportunities for stronger safety monitoring and lifecycle value.

What are the most persistent challenges in veterinary pharmacovigilance when it comes to under-reporting of adverse events?

In the world of veterinary medicines, one of the most enduring challenges in veterinary pharmacovigilance is under-reporting of suspected adverse events. When products leave the clinical trial phase and enter wide use across many species and breeds, the volume of use grows, but reporting often does not keep pace. In this context, organisations such as veterinary pharmacovigilance service providers specialise in establishing robust workflows and quality-management systems to ensure that adverse events in animals are captured, processed, and escalated in compliance with regulatory frameworks. The lack of timely reporting skews the dataset, reduces signal-detection power and delays identification of emerging safety issues. Regulatory obligations such as those under Regulation (EU) 2019/6 require marketing-authorisation holders to collect and collate all suspected adverse reactions. To mitigate this, companies must build an internal culture of reporting across all user groups (veterinarians, farmers, animal owners) and design easy-to-use reporting tools. Overcoming this challenge means not only improving quantity of reports but enhancing their completeness, accuracy and relevancy—crucial for maintaining animal health, public health and regulatory compliance.

How does the diversity of animal species amplify the challenges in veterinary pharmacovigilance and signal detection?

When a veterinary medicinal product is used across multiple animal species, the complexity of monitoring grows dramatically. At Billev Pharma East, we assist clients to navigate this multifaceted environment by delivering tailored pharmacovigilance and regulatory-affairs support for the veterinary sector. The diversity of species – from companion animals to livestock – means physiological responses vary, dosage regimens differ, and the pattern of adverse events may not mirror those seen in humans or even in other animals. This heterogeneity poses major challenges in veterinary pharmacovigilance: differences in exposure, metabolism, susceptibility and off-label use all complicate signal detection. Furthermore, the statistical tools and monitoring frameworks often developed for human-medicinal-product pharmacovigilance may not readily translate to veterinary contexts. Without species-specific insight, subtle safety signals may be missed, increasing risk of harm or regulatory action. Companies must therefore adopt adaptive surveillance strategies, invest in training for multi-species contexts and implement robust signal-management systems to respond effectively.

Why is causality attribution such a difficult obstacle in veterinary pharmacovigilance systems?

One of the core issues among the challenges in veterinary pharmacovigilance is attributing an adverse event to the medicinal product, rather than to the animal’s underlying condition, species-specific reaction or environmental factor. Animals often have concurrent illnesses, co-medication, varying management conditions or exposure to feed changes—all of which may confound causality assessment. Additionally, veterinary settings may lack the depth of clinical documentation found in human medicine, further complicating attribution. The absence of robust epidemiological data for many species magnifies the uncertainty. As a result, marketing-authorisation holders can struggle to determine whether an event is truly product-related and whether further regulatory action is required. This ambiguity impairs signal assessment, delays corrective actions and might hinder the evolution of risk-minimisation measures.

Navigating causality attribution: a key sub-challenge in veterinary pharmacovigilance

Causality attribution remains one of the most difficult elements of the challenges in veterinary pharmacovigilance because it demands a clear-cut link between a product and an adverse event, which is often lacking in veterinary contexts. Animals frequently present with multiple comorbidities, are treated off-label, or exposed to environmental and management factors that obscure cause-and-effect. According to a recent overview, the methods used for causality assessment (even in human pharmacovigilance) are subject to inconsistencies, incomplete information, and inter-rater variability. In veterinary settings these issues are compounded by species-diversity, limited case data and the absence of validated algorithms for many animal types. The regulatory guidance for veterinary medicines highlights that a “signal” is information suggesting a potential causal association. Without robust causality assessment, signals may be overlooked or falsely attributed, increasing risk to animal health and impeding effective risk-minimisation. Therefore, improving methodologies, investing in better case documentation and expanding species-specific tools are essential to address this sub-challenge.

In what ways does the regulatory framework contribute to the challenges in veterinary pharmacovigilance for veterinary medicinal products?

The regulatory environment for veterinary medicinal products has undergone significant reform—most notably via Commission Implementing Regulation (EU) 2021/1281 and the VGVP guidelines. These changes bring stricter requirements for the collection, reporting and monitoring of adverse reactions. Marketing-authorisation holders must align their systems with updated obligations, maintain a pharmacovigilance system master file (PSMF), and ensure oversight by a veterinary Qualified Person Responsible for Pharmacovigilance (QPPV). While these measures enhance animal safety, they also add to the cost, operational burden and complexity—thus contributing to the broader challenges in veterinary pharmacovigilance. Companies operating across multiple markets must reconcile varying national expectations and resources, and must ensure consistent compliance even when data flow or infrastructure may be constrained. This regulatory pressure can cause smaller firms to struggle with system maturity and resource allocation.

How do data-quality and reporting infrastructure issues hamper effective monitoring in veterinary pharmacovigilance?

High-quality data is the bedrock of an effective pharmacovigilance system, yet one of the significant challenges in veterinary pharmacovigilance lies in the variable quality and infrastructure of reporting. Unlike human medicine where digital systems are often mature, veterinary scenarios may rely on paper-based or semi-digitised workflows, lack standardised terminologies and suffer from inconsistent follow-up. For example, the guideline on VGVP emphasises that suspected adverse event reports must be collected and recorded in a systematic manner. Without accurate, complete and timely data, signal detection is impaired, trend-analysis falters and risk-minimisation decisions may be delayed or mis-directed. Enhancing data infrastructure—harmonised coding, integrated databases across species, and real-time analytics—is essential. Organisations must invest in training, technology and governance to overcome this barrier.

Ensuring data quality and infrastructure resilience among the challenges in veterinary pharmacovigilance

Among the array of challenges in veterinary pharmacovigilance, data-quality and infrastructure issues form a critical sub-category that directly impacts the effectiveness of monitoring and signal-detection. The European Medicines Agency (EMA) notes that poor data quality — such as incomplete adverse-event reports, inconsistent terminologies or missing follow-up information — can impair statistical analyses, weaken signal-detection and undermine the pharmacovigilance system. In veterinary pharmacovigilance the problem is intensified by varied animal species, lack of standardised coding across species, and fragmented reporting infrastructures. For example, the “European veterinary big data strategy” emphasises the need for defined data-quality metrics and clear limitations in transformed or mapped data. Organisations must therefore prioritise robust data-governance frameworks, invest in integrated digital platforms, and establish standardised workflows across species and markets to mitigate this infrastructural sub-challenge.

What role does the lack of global harmonisation in adverse-event definitions play in the challenges in veterinary pharmacovigilance?

Global harmonisation of definitions, terminology and processes is vital for efficient safety-monitoring, yet its absence constitutes a substantial part of the challenges in veterinary pharmacovigilance. For animal health products, different jurisdictions may use varying categorisations of adverse events, inconsistency in off-label use definitions and divergence in signal-management thresholds. These discrepancies hinder comparability of data across markets, complicate cross-border product lifecycles and may obscure emerging safety patterns. Without harmonised frameworks, marketing-authorisation holders must manage multiple parallel systems, increasing cost and complexity. In turn, this may inhibit timely global responses to safety signals and impact both animal welfare and regulatory compliance.

How can organisations overcome the operational and resource-based challenges in veterinary pharmacovigilance to improve safety monitoring?

Addressing the operational and resource-based dimension of challenges in veterinary pharmacovigilance demands a strategic approach. Organisations must build internal capabilities (trained staff, robust SOPs, dedicated QPPV roles), adopt outsourcing models where appropriate and focus on continuous improvement. The investment in efficient reporting platforms, automated workflows, signal-detection tools and cross-functional alignment is key. Partnering with specialised service providers (as referenced in our service descriptions) enables access to experience, best practices and benchmarking. Moreover, embedding a proactive safety-culture—from data-collection to signal-escalation—transforms pharmacovigilance from a compliance burden into a strategic asset. In doing so, animal health products gain greater lifecycle resilience, regulatory risk is mitigated and ultimately animal welfare is enhanced.

Read also:

• How can you distinguish a veterinary adverse event from normal pharmacological effects?
• How can we implement effective signal detection in veterinary pharmacovigilance using spontaneous reporting systems?
• What are the regulatory requirements for QPPV in veterinary pharmacovigilance?

Sources: 1 – European Medicines Agency. (2022, November 18). Guideline on veterinary good pharmacovigilance practices (VGVP) – Module: Collection and recording of suspected adverse events for veterinary medicinal products, 2 – European Medicines Agency. (2023, December 19). Signal management (veterinary medicines) – module of the guideline on veterinary good pharmacovigilance practices (VGVP), 3 – European Medicines Agency. (2022, June 13). European veterinary big data strategy 2022-2027, 4 – European Medicines Agency. (n.d.). Veterinary pharmacovigilance – Pharmacovigilance (veterinary medicines).