For biopharma finance teams, effectively forecasting clinical trial costs is critical to cash management, portfolio prioritization, and strategic decision-making. Yet siloed data, trial complexity, and cost variability make it hard for these teams to produce forecasts they can trust, let alone produce or update them quickly.
In a recent live session, we walked through three common forecasting scenarios that teams are asked to model, and how Auxilius can be used to accelerate speed to insights:
Here is a look at each question, the hidden challenges behind it, and how the right modeling approach solves them.
Long-range planning often begins before protocol details are finalized and without historical cost data, resulting in rough budget estimates built on data inputs that may not fit the current trial design.
How Auxilius Solves It: Auxilius Atlas eliminates planning bottlenecks by leveraging proprietary benchmark data to build future study budget forecasts. Teams input high-level study parameters, such as phase, indication, patient and site counts, start date, and regional footprint, and Atlas automatically builds out the plan using benchmarked costs alongside critical timing drivers like enrollment velocity and standard indication timelines.
Instead of a single lump sum cost estimate, costs are distributed over time based on the expected progress of the study. FP&A teams can also instantly generate portfolio-wide multi-year plans, manipulate variables like patient counts or site numbers, and provide the board with clear budget projections based on different trial scenarios.
Once a study is active, the challenge shifts from initial estimation to ongoing management. Starting investigator budgets rely on average per-patient costs that, even if they were accurate at first, quickly degrade as sites activate, enrollment mix shifts, and protocols change.
How Auxilius Solves It: Auxilius approaches investigator management from the patient visit up using its Investigator Spend Intelligence capabilities. By pairing the protocol's schedule of events with negotiated site costs from CTAs, and pulling actual visit data automatically from EDC systems, actuals and forecasts are all grounded in both the trial design and trial progress. This builds the most complete and comprehensive view of your investigator costs possible.
For unenrolled patients, teams apply configurable pricing rules by country. Conditional procedures like imaging, biopsies, and screen failures are governed by specific rules that update dynamically as real EDC data flows in, keeping forecasts current with limited manual recalibration.
At an enterprise scale, the challenge shifts from single-study precision to portfolio-wide practicality. Straight-lining costs across each study works until an individual study deviates from the plan, leaving finance teams with little insight into the drivers of variance. However, manually assigning detailed forecast drivers to hundreds of line items across dozens of studies is impractical at scale.
How Auxilius Solves It: Auxilius builds every forecast at the trial level based on clinical drivers, and then allows for portfolio-level reporting. This enables reporting at the scale that enterprise organizations operate on, and also provides the underlying detail to answer the “why” behind any variance.
To make this scalable across a large clinical portfolio, Auxilius uses AI-powered intelligent automation to draft initial drivers across your budget, flagging lower-confidence mappings for review while leaving the final sign-off strictly in human hands. Auxilius AI features are calibrated specifically for clinical finance. Enterprise sponsors can also develop portfolio-wide rules so common start-up categories automatically align study after study, delivering program-level accuracy without the manual overhead.
Whether managing a single study or a large portfolio, reliable clinical trial forecasting depends on a unified clinical finance data foundation that is built to scale. FP&A professionals need approaches that work from the procedure-level to the comprehensive portfolio view. By providing accessible cost benchmarks across therapeutic areas, supporting comprehensive investigator forecasts, and enabling portfolio-level reporting, Auxilius accelerates time to insights for FP&A teams as they answer their most pressing financial questions.
Ready to see it in action? Request a demo with Auxilius to explore how to model your clinical trials at all altitudes or reach out to pkinchley@auxili.us for the webinar recording.
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