Avoiding Common Real-World Pitfalls in Viral Clearance Studies

Viral clearance studies evaluate how effectively a manufacturing process can remove or inactivate viruses. These studies use two categories of challenge viruses defined in regulatory guidance: relevant viruses, which represent agents plausibly associated with the production system (e.g., helper viruses, host-cell viruses), and model viruses, which are well-characterized surrogates selected for their resistance profiles, stability, or structural similarity to potential contaminants. Both types play essential roles in establishing a scientifically justified virus panel.

Viral clearance studies are shaped by two types of uncertainty: the interpretive space created by evolving regulatory guidance, and the real-world constraints of development programs. Timelines, process maturity, facility availability, assay limitations, and the quality of virus stocks can all impact study feasibility and outcomes. These pressures may translate into cost overruns, schedule disruptions, unnecessary rework, or studies that fail to provide the intended level of assurance.

Drawing on decades of biosafety testing and thousands of executed studies, the following sections summarize the pitfalls we most frequently observe across modalities. These insights reflect practical, real-world challenges encountered during study design and execution—and highlight where targeted planning can prevent delays, reduce uncertainty, and support more efficient viral clearance strategies.

A common pitfall—especially for small and mid-sized developers—is being steered toward a fully comprehensive, late-phase “Cadillac” viral clearance study when the program is still early in development. While the underlying science is consistent, an inflexible, all-inclusive package can strain limited budgets, extend timelines, and divert resources from other critical activities. Early clinical and exploratory programs rarely need the full breadth of commercial-scale requirements; what they need is a phase-appropriate approach that generates defensible data without overspending.

Solution: Phase-Appropriate Studies, Flexibly Executed 

The most effective path forward is working with an organization that can right-size study scope to the stage of development—preliminary, Phase 1, or late-stage—while still ensuring regulatory confidence. Partners who take this approach evaluate the needs of the full program, offer flexibility in schedule and scope, and leverage historical data to avoid unnecessary work. This balance of scientific rigor, financial stewardship, and operational flexibility helps developers—especially resource-constrained teams—advance programs efficiently without compromising the needed data.

A persistent challenge in viral clearance planning is timing. Initiating a study too early can force developers to work with immature or incomplete process data, while delaying too long can lead to capacity constraints, rushed decision-making, and pressures that threaten downstream milestones and commercial runway. When timing is misaligned, programs often face incomplete data packages, unplanned rework, or repeated assays. Each adds cost, uncertainty, and avoidable delays.

Solution: Early Planning, Strong Communication, and Flexible Scheduling

The most effective approach is to begin planning well in advance of regulatory submissions and to maintain open communication with the contract organization throughout process development. Developers who share anticipated timelines, evolving process maturity, and potential risks early enable their partners to offer appropriate schedule flexibility while still ensuring regulatory alignment. When both sides communicate proactively and adjust scope based on phase and readiness, viral clearance studies can leverage mature process data, avoid unnecessary duplication, and produce high-quality, defensible results.

High-quality virus stocks are fundamental to viral clearance studies, which rely on spiking defined quantities of virus into scaled-down process steps. Within this experimental design, the purity, concentration, and characterization of the virus stock directly influence the observable performance of filtration, chromatography, and inactivation steps under challenge conditions. When the stock itself is suboptimal, even a well-designed study can yield misleading or non-representative results.

Poorly purified or poorly characterized stocks introduce unwanted impurities that can artificially foul filters, alter resin performance, or interfere with inactivation kinetics—distorting measured log reduction values (LRVs) and obscuring the process’s true clearance capability. Low-titer stocks pose an additional risk: because regulatory guidance caps allowable spike volumes, insufficient titer can lead to an underpowered challenge that fails to meaningfully stress the clearance step, potentially masking performance gaps or underrepresenting performance strengths.

Solution: Use High-Purity, High-Titer, Well-Characterized Virus Stocks

The most reliable studies employ virus stocks that are generated and purified using robust methods and thoroughly characterized before use. High-purity stocks minimize non-viral contaminants that can confound process performance, while high-titer stocks ensure a rigorous infectivity challenge within permitted spike volumes. When paired with step-specific considerations—such as appropriate spike ratios and assay sensitivity—this approach strengthens data integrity and maximizes confidence in LRV outcomes.

ICH Q5A(R2) promises greater efficiency through the use of platform data for well-characterized unit operations (e.g., low-pH inactivation, viral filtration) for mAbs and other well-characterized proteins. However, this guidance is not a “rubber stamp.” The guidance requires substantial prior knowledge and a scientific justification that new process parameters (pH, temperature, filter loading) are comparable. In practice, developers may assume platform data will apply to their molecule, only to discover late in planning—or once a study begins—that their process differs enough to require additional experiments or validation. This mismatch can introduce unplanned cost, expanded scope, and schedule disruptions.

Solution: Evaluate platform data applicability early, supported by robust prior knowledge and documented comparability

The most effective strategy is to assess platform data suitability early—before finalizing study design—using historical data, risk assessment, investigational R&D studies, and process comparability analyses aligned with ICH expectations. Here developers benefit from working with organizations that possess large internal viral clearance datasets and mature assay characterization, which may enable more informed decisions about where platform data are appropriate and where product-specific studies remain necessary.

The sample volume an assay can accommodate places a mathematical limit on the demonstrable LRV in a viral clearance study. If a purification step clears 6 logs of virus but the assay can only measure 4 logs due to volume constraints, the report will underrepresent the process’s safety. As a result, highly effective steps may appear to plateau at lower LRVs.

Infectivity assays are essential because they quantify replication-competent virus, a primary regulatory concern. However, commonly used TCID₅₀ assays may run up against limits due to their format, as well as practical constraints on test volume. These factors may in turn restrict statistical power at low virus concentrations and can cap measurable LRVs below the true clearance capability of a process.

Assay selection more broadly shapes how clearance data are interpreted. Misalignment between assay capability and expected clearance depth can lead to underrepresentation of process performance, unnecessary addition of unit operations, or avoidable repeat studies—outcomes that introduce delay, cost, and uncertainty.

Solution: Pair high-quality virus stocks with assays capable of large-volume testing

A more robust approach is to use well-characterized, high-titer virus stocks together with infectivity assays that can be executed at larger volumes. Increasing the volume of filtrate or eluate tested directly increases the upper limit of quantification, often enabling measurement of LRVs one or more logs higher than small-volume formats allow. Assay strategies that incorporate large-volume testing—such as Large Volume Plaque Assays (LVPA)—may create a a truer picture of a step’s clearance capability and result in a more robust dataset for regulatory submission.

Viral clearance studies are inherently complex, shaped by regulatory expectations, process variability, and practical development constraints. Thoughtful study design—grounded in scientific rigor, phase-appropriate scope, and clear communication—can reduce uncertainty and strengthen the overall data package.

If you have specific questions about your viral clearance strategy, study timing, assay selection, or the applicability of platform data, our scientific team is available to discuss them. A focused, early dialogue can often clarify options and help ensure your study design aligns with both your process and regulatory goals.