In the biopharma industry, financial planning and forecasting are crucial for managing organizational health and strategic planning. Clinical trials often account for a substantial portion of a company's budget, sometimes reaching up to 70-80%. These trials are inherently unpredictable, making accurate forecasting a challenging yet essential task.
Below is short summary of a recent live session on R&D forecasting and strategic planning, followed by an abbreviated transcript:
Biopharma investors are keen to understand when they will get data readouts from trials that indicate if a drug is effective. As a result, they are very interested in how trials are progressing towards previously-communicated milestones. Clinical drivers are critical to forecasting trial progress and its financial implications because clinical trials are inherently complex and unpredictable.
By constructing and updating forecasts based on key clinical trial drivers - such as site activation and patient enrollment that have a disproportionate impact on trial progress and budget - it is possible to get more accurate assessments of how budgets and trials are tracking compared to forecasts.
There are three critical inputs that are traditionally difficult to accurately data on:
To address these challenges, organizations can adopt several strategies:
In the biopharma sector, where R&D and clinical trials are often at the heart of operations, effective financial planning and forecasting are indispensable. By understanding and leveraging clinical drivers, utilizing granular data, and fostering cross-functional collaboration, organizations can enhance their forecasting capabilities. This not only aids in strategic planning but also ensures that resources are optimally allocated to drive innovation and growth.
Introductions (00:00)
About Alkeus Pharmaceutical (04:53)
The role of FP&A in biotech (07:10)
The challenges with forecasting clinical trials (12:31)
Source of truth for patient enrollment (18:40)
How to manage prepaids (25:43)
Bridging the gap between finance and clinical teams (28:00)
Forecasting cadence(34:13)
Automating forecasting with Auxilius (contact us for recording)
Closing questions (40:40)
Hi everyone! We're really happy to have you here for today's live session, where we are delving into clinical drivers that are critical to an organization's financial planning and forecasting capabilities.
My name is Sharon Langan. I head partnerships and community engagement at Auxilius. I joined Auxilius over two years ago. Prior to that, I did some auditing in Big Four and spent 20 years in the B2B world working with finance and accounting leaders within the life science community.
Like many of you, the output of R&D and the innovation that this industry produces from both a trial perspective and a therapeutic breakthrough perspective hit home for me. What I also recognize is that there was an underserved area for finance and accounting leaders from a tool perspective around forecasting clinical trials, which are so important to what we do in this industry. I am so happy to be here today, joined by two amazing experts in this field.
Before we do some quick introductions, I want to give you a little background on why we're here from Auxilius, talking to you today about this topic. You may have heard from Auxilius over recent years or even just in recent months in the webinars we've been doing, but for those new faces, welcome to this session.
Different from past sessions, we're focusing today on the financial planning and forecasting elements and why they are so important organizationally. Of all operational and resource factors that feed into a biopharma company's financial health and ability to strategically plan, R&D and trial costs top that short list because they are disproportionately material, sometimes upwards of 70 to 80%. They're complex, difficult to predict, hard to pin down, and the progress of a clinical trial is paramount to the organization and to investors' interests.
A little bit about Auxilius: we are the biopharma industry's first and principal solution purpose-built to power dynamic driver-based forecasting across a portfolio of clinical trials so that biopharma finance and accounting teams can make informed decisions in a timely manner with full visibility. We are working across 70+ biopharma companies ranging in therapeutic size, scope, and focus. But that's enough about us. If you have questions or curiosity or want to learn more, you can always reach out to me or our team, or visit us at auxilius.co.
With that, I want to introduce our speakers and presenters for today and allow them to do some self-introductions. We'll start with the Auxilius team. Erin, would you like to give a little bit of your background?
Erin Warner Guill: Yes, hello everyone, and thank you for joining. My name is Erin Warner Guill. I'm the President and COO of Auxilius.I've been with the company since we started. My background is at the intersection of healthcare and finance—I am a former investment banker, private equity investor, and have operated healthcare data and analytics businesses before helping to start Auxilius. Relevant to today's discussion, I have built hundreds of models in my career. I'm very passionate about forecasting and modeling and excited to talk about this subject with you today.
Sharon Langan: Awesome. Thank you, Erin. And Robbie Tantoko, it's great to have you here. We appreciate your time in joining us. Robbie, tell us about your background.
Robbie Tantoco: Thank you for having me. I'm Robbie Tantoko, Vice President of Finance at Alkeus Pharmaceuticals. I've been in the industry for about 20 years—it goes by so fast. The first half of my career was spent supporting commercial-stage organizations. I've launched four or five products throughout that experience. Midway through my career, I pivoted to support drug development-stage companies. That's where I started to learn about clinical development, clinical trials, and the intricacies of that work.
Disclaimer: I am by no means an expert in clinical trials and modeling. A lot of my experience comes from on-the-job learning, and I have had a tremendous team under me who have taught me much of what I know today. I hope I can share some of that knowledge with you all.
Sharon Langan: Amazing. Robbie, I think it's hard to be an expert in clinical trial finance, but what’s important is taking that data and using it to make critical decisions in your role as a financial steward and leader within your organization.
Sharon Langan: Before we dive into things, can you give us a quick overview of Alkeus Pharmaceuticals and where you're at in your clinical portfolio and pipeline?
Robbie Tantoco: Sure. Alkeus has been around for a while, but only recently, in the past year or two, have we really started forming a true organization. There's a likelihood that we will file an NDA this year. We are in the rare disease space for ophthalmology, particularly targeting Stargardt disease.
Usually, in rare diseases, the FDA allows you to file based on a Phase 2 study. So we’re hoping to file an NDA this year, and if all goes well, commercialize either later this year or early next year. We are also conducting a Phase 3 study. We're just in the process of getting it started—still working on agreements and everything. Part of today’s discussion is about ensuring we account for the right data ahead of time when setting up these agreements. What kind of data do we need? What level of detail do we want from the CRO? Can they even provide it?
It will be an exciting year for sure.
Sharon Langan: Excellent. We’re excited for you and grateful to have you here with us. For today, we are going to spend the remaining time discussing the role of clinical metrics, how they inform organizational financial strategy, and elements like capital allocation and project prioritization. We will explore best practices and industry insights, and at the end, we will provide a demonstration of how Auxilius can support these efforts.
Before we jump into clinical trials and specific forecasts, we want to zoom out and discuss investor interests. For clinical-stage companies, investors are highly focused on what is happening on the R&D side. They want to see companies meet their next milestone and value inflection point.
The key questions they ask are:
Robbie, as a financial leader in the industry, how do you think about the role FP&A plays in biotech organizations? What does forecasting mean in the broader view, both near-term and long-term?
Robbie Tantoco: It’s a great question. Over the past five years, especially with the economic stress on the pharmaceutical industry, raising capital has become more difficult. This has made the role of FP&A even more critical.
When we speak with investors, especially when starting a study, their main focus is understanding when they will see data that indicates our drug works. We communicate key milestones, such as when we expect the first patient to be enrolled, when sites will be up and running, and when we anticipate an interim readout.
The moment we commit to these timelines externally, we are under increased scrutiny. Investors want to know if we are meeting our commitments. Internally, finance teams must assess whether the company is on track based on our current capital. We need to identify risk areas and determine if our cash resources are sufficient to meet these milestones.
This requires more than just qualitative conversations with the CRO. Often, the devil is in the details, and finance teams must analyze the actual data to ensure milestones are achievable. For example, patient enrollment is a key indicator of whether we will meet our milestones. If enrollment is lagging, the overall trial timeline will be delayed, leading to increased costs. Historically, we relied on CROs for projections, but we've learned that their estimates can be overly optimistic. Having our own independent view of the enrollment trajectory is empowering for financial planning teams.
Sharon Langan: Absolutely. Patient enrollment is a critical indicator, but what other factors make forecasting in clinical trials difficult?
Robbie Tantoco: In addition to patient enrollment, site activation is another major challenge. The ability to get sites up and running quickly is a key cost driver. We need to ensure that the CRO we are working with is the right partner. We’ve seen instances where a CRO struggled to activate sites due to unforeseen challenges, such as COVID-related restrictions or competition for the same patient population. This has led to delays and increased costs.
Another major challenge is investigator payments. These are difficult to predict, especially since investigator sites often invoice late. CROs can only provide information based on what they receive from the sites. We’ve had situations where we were assured that all costs were accounted for, only to receive unexpected invoices months later, which can be financially disruptive. For small companies, unplanned expenses of $500,000 to $1 million can be a significant issue, impacting our ability to allocate capital effectively.
Sharon Langan: That’s a great point. There’s an expectation that all financial information is readily available, but in reality, it often lacks the necessary detail or timeliness.
Robbie Tantoco: Exactly. This is why finance teams need their own data points to push back and challenge CRO estimates. Otherwise, we are simply taking their word for it instead of having an informed discussion.
Erin Warner Guill: That’s a common theme we hear from our customers. Many companies enter the RFP process with multiple CROs, each putting their best foot forward with competitive bids. Optimistic projections are often baked into these proposals. One way to mitigate this is by applying conservative buffers—such as a 10% enrollment buffer—so that when the CRO inevitably requests additional funds, the company is not caught off guard.
Another key issue is investigator site costs. CROs provide an estimated average cost per patient, but in reality, actual costs vary significantly. If most enrollments occur at higher-cost sites, the budget can be significantly impacted. Having an independent forecast based on real-time clinical data can help finance teams manage these discrepancies.
Erin Warner Guill: Robbie, you mentioned the challenges, of having your own view on when you expect site activation to happen, having your own view on patient enrollment. What is your source of truth?
So you talked about not wanting to rely on the CRO, so how do you get independent conviction? What are your sources? Can you talk a little bit about like how you discuss with your clinical counterparts to get that?
Robbie Tantoco: When you don't have a 3rd party system [like Auxilius] your source of truth ends up being what the CRO tells you, but what I end up looking at even more are the actuals and comparing to the forecast that the CRO tells you. And what often happens is that it ends up being like a hockey stick. And you might accept it for maybe the first round, but if it's consistently that way, you go back to your clinical team to provide more insight into why they believe what the CRO is saying. And the reality is that the CROs are often providing a more optimistic view of expected study progress than what plays out in real life.
Erin Warner Guill: I'll give some other observations that we see across our customers. Most of this optimistic viewpoint is coming from a competitive bidding process, where everyone's shaving 10% off their estimates. So how can I be conservative and apply a buffer so that I don't get caught by surprise when the CRO comes back and says "oh, looks like I have more turnover in my staff. Let me supplement the training budget relative to where we expected. We always see that on the investigator side. They say, "Here's the average patient cost" but then your enrollment comes in and it's more concentrated at high cost sites that are quite different from the average patient cost that was cited.
Robbie Tantoco: Also, when you negotiate the MSA, that's the best time to agree on the detail of information provided and processes that you follow. Something as simple as putting in the MSA language that puts maybe penalties if they remove key talent or personnel from a study can make a big different since it's really the talent that drives the study forward. And if you work with a CRO that keeps taking a way key talent that you really enjoy working with, that can become a huge problem.
We also put in processes that allow us to track change orders, and be proactive about what comes in change orders, because a lot of times these studies will happen and something will be needed by the clinical team that is out of scope and a lot of times they'll just email the CRO to do it in the absence of finance because it needs to be done, and the next thing you know, a massive change order comes in and finance is completely thrown off.
So we've since put in processes that allow the clinical team to keep operating without disturbance but still allows a sense of control for the finance team.
Robbie Tantoco: As a small company, cash is king, and you want to keep as much cash as you have so that it's accruing in your bank account. I'm more comfortable negotiating a contract where we forecast every quarter and replenish every quarter. What the problem is with prepaid expenses is that it can be used as a bucket to fund out-of-scope activities, and we don't want that, because at the end of the day you want to understand everything that you're paying for, so we have a practice where we have a regular check-in with our CRO, and we reforecast what out-of-pocket costs we expect there to be.
Erin Warner Guill: This is one of the biggest things our Auxilius customers struggle with, not just prepaids but forecasting exactly what investigator spend is going to be. The CRO is projecting what expected costs are going to be against those prepaid balances, and if you don't have your own view of what is going to happen, escrow is going to be way above what it needs to be. We do this at Auxilius with your own clinical data and your site contract information in real time, so you can have that accurate forecast, but it's a widespread challenge we see in the industry.
Robbie Tantoco: Exactly, having your own information and view of the world is so important.
Robbie Tantoco: There's a question in the chat about how do we minimize the gap between finance and clinical teams to better support operations? The best approach is partnership. When I started at Alkeus, I proactively introduced myself to the head of clinical operations to establish a collaborative relationship. My goal was to ensure they could focus on running trials while I focused on the finances. Non-finance teams don’t want to deal with financial reporting—they want to focus on their operational work. By understanding their challenges and structuring financial reporting in a way that supports their needs, we can work more effectively together.
Additionally, I engage with clinical trial managers directly. They have a hands-on understanding of what’s happening on the ground and can provide valuable insights that might not be visible at higher levels. This allows us to better align financial reporting with actual clinical operations.
When I go to my clinical team. I'm almost storyboarding the numbers for her and trying to make sense based on what's happening because that's where they can really provide value is telling you exactly what's happening in clinical studies and then I'm able to take that and translate it to the numbers. And sometimes I even say "the numbers don't jive with what's happening." I work with my clnical partner and I'm able to take that back to the CRO and say, "tell me where the gap is here. What am I not understanding?"
Erin Warner Guill: We see a lot of similar things across our customer base. Many finance professionals struggle when they approach clinical teams without an informed perspective on what is happening in the study. Asking clinical operations to recount study details without having done your own homework can be frustrating for them. Instead, finance teams should approach discussions with specific, informed questions based on available data available to them. "Does this make sense?" "Should they be charging us for ten site monitoring visits when we've only activated two sites?" It's really important that you're like showing that you have that context and have done your own home work and you're speaking clinical.
Robbie Tantoko: Exactly, and I've actually had better luck getting more context of what's going on on the ground by going directly to clinical trial managers.
Sharon Langan: Absolutely. Now, let’s shift gears a bit and discuss forecasting accuracy. Many companies reforecast on a quarterly basis due to bandwidth and data limitations. If you had access to automated recalibrated clinical trial expense forecasts using real-time actuals, would you reforecast more often?
Robbie Tantoco: Personally, I would. Even if management receives quarterly updates, I like having monthly projections to assess whether the previous forecast still holds or if adjustments are needed. However, this depends on having the right tools—if forecasting requires too much manual intervention, it may not be feasible to reforecast more frequently.
Erin Warner Guill: That’s a great point. We hear that quarterly forecasting is often a necessity due to limited resources. However, with automated tools that refresh forecasts in real-time, finance teams can gain more frequent insights without additional workload.
Sharon Langan: Given these challenges, let’s pivot and discuss how a tool like Auxilius can help automate and improve clinical trial forecasting.
Erin Warner Guill: Great, let’s do that. Robbie and Sharon, feel free to jump in. Robbie has framed the problem well—now, I want to show how Auxilius addresses these challenges.
Now, I'm going to start here at the portfolio level view. The reality is ,and we didn't get into the poll question on the macro-level strategic FP&A challenges, but I think what we would have heard from you, our guests, is that being able to articulate portfolio-level financial planning is critical.
Evaluating new financing options requires a clear understanding of where that cash will be spent going forward. We also hear a strong focus on reducing and streamlining R&D costs. That’s exactly what we’ll explore today. The importance of having a high-level view of everything happening across your portfolio cannot be overstated.
Most sponsors forecast at the trial level because each trial has significant nuances. As Robbie mentioned, factors such as the enrollment curve dictate cost distribution. The Auxilius system is designed to provide answers at the trial level while still allowing for portfolio-level reporting. Today, we won’t go into end-to-end accrual solutions but will focus on specific forecasting use cases.
One of the first things Robbie emphasized is anticipating inevitable changes in a study. Understanding the key drivers of change throughout a trial and getting a strong grasp on initial milestone expectations are critical. Moreover, it's important to have a mechanism in place to assess the impact of milestone changes.
Auxilius is built to capture a contracted view of a trial and create a budget data model based on it. The system indexes new contracts and change orders, allowing users to track how budgets evolve from their initial agreement to the final expenditure.
In this demo environment, we don’t have it built in, but many of our customers incorporate a buffer. FP&A leaders often say, "I hear you, clinical teams, but I know there will be a lag, so I need to build in a 10%enrollment buffer into the trial budget."
Now, let’s look at the key elements displayed. You can see the contracted baseline, actuals to date, remaining budget, and a data-driven forecast. We’ll dive deeper into how this forecast is set, but as Robbie mentioned earlier, actuals serve as the best indicator of what to expect within a study.
Having your own independent view strengthens forecasting accuracy and prepares you for conversations with your CRO. If you don’t monitor what your CRO reports, that’s where cost overruns can occur. Having your own perspective ensures greater control over financial planning.
Now, looking at our vendors across the study—someone in the chat asked about the importance of detail, and Robbie has already highlighted that the devil is in the details. Our system ingests budgets at the most granular level so you can accrue and forecast at the unit level if needed.
Understanding costs at the unit level provides the strongest leverage—not just for forecasting, but also for holding vendors accountable.
So, how do we set the forecast in the system? Forecasting is entirely dependent on the data available and how it’s leveraged for modeling.
From our conversations with hundreds of biotechs, we’ve identified three key forecasting drivers in clinical trials:
By integrating trial-specific timelines, patient curves, and site activity curves, we ensure a comprehensive approach to forecasting.
Returning to a question about granularity, Auxilius allows forecasting at whatever level of detail makes sense for your organization. Larger pharma companies may categorize trial costs into broad groups (e.g., straight-line costs, patient-driven costs, startup costs). However, biotech companies often prefer deeper granularity—especially when managing significant expenditures like a $7 million site monitoring and management budget.
Our system allows users to designate forecasting logic at a granular level. For example, site monitoring costs may be tied to the patient curve, while monthly-incurred expenses are straight-lined. This flexibility allows teams to accurately model cost distribution based on actual expense patterns.
Robbie, from your perspective, what is your approach to forecasting granularity?
Robbie Tantoco: We forecast on a unit basis and get into this level of detail because it allows us to identify cost drivers. Over time, I've learned which areas require close scrutiny. Personally, I prefer having more data because I can always consolidate later, but if I don’t have the data upfront, I’ll have to search for it later.
Erin Warner Guill: That’s a great approach. When teams start with high granularity, they gain the flexibility to adjust as needed.
So, Robbie has set his forecast logic at this detailed level and can now seethe resulting budget in our system. Having actuals and forecasts side by sideallows for a longitudinal view of trial expenses.
One last point—trials change by nature, so it’s critical to track how forecasts evolve. Auxilius captures monthly snapshots, enabling teams to compare past and present forecasts to analyze variance. For example, if CRO costs have increased by $3 million, teams can drill down to identify the specific drivers—such as investigator fees increasing by 59%—to understand what happened and make informed decisions.
Another common challenge in forecasting is investigator spend. CROs initially estimate per-patient costs based on therapeutic area benchmarks, but these estimates often prove inaccurate. Our system accounts for evolving data to refine investigator spend forecasts.
The process begins with CRO estimates. Once site contracts are signed, the system ingests actual contract values to refine cost projections. For example, if initial estimates assumed $50,000 per patient but contracted sites are averaging $75,000, it may be time to recalibrate your forecast upwards based on what you're actually contracting.
The most accurate projections emerge from real-time EDC data. As patient visits occur, Auxilius analyzes trends in visit schedules, invoiceables, and site-specific costs. This enables finance teams to move beyond static projections and use live trial data to refine forecasts continuously.
Our system visualizes patient visit projections and maps them against contractual obligations, ensuring accurate cost forecasting through trial completion.
Another key investigator spend challenge is managing prepaid balances. CROs often hold investigator fees in escrow accounts, but their projections aren’t always accurate. Without an independent forecast, escrow amounts may exceed actual needs, leading to inefficient cash allocation. Auxilius uses site contract data and EDC trends to generate real-time investigator spend forecasts, ensuring accurate financial planning.
Final thing I'll just say on the investigator side, to Robbie's point, understanding actuals is really, really important. And so having a view of the trends across everything that's happening from a patient visit standpoint from the invoiceable standpoint, really important for you to understand as FP&A what are the trends in discontinuation, what are the trends in invoiceables and leveraging that historical data is going to increase your accuracy.
Last thing, for unscheduled visit costs we bring in, there are usually indicators in the CTAs that tell you what you're on the hook for and a lot of times we'll actually bring in the procedure level cost and from the unscheduled visit, what procedures happened at that visit.
The visit schedule projection incorporates all CTA amendments, so anytime we're getting an amendment, we're updating the clinical data model to reflect the latest costs.
Erin Warner Guill: Finally, last question for Robbie: Forecasting pass through costs, and we get this a lot, Robbie, how do you typically forecast pass-through costs?
Robbie Tantoco: We base it on actuals and see how they're doing. It's not a great process, so I'm looking to see what you guys can provide in that regard.
Erin Warner Guill: My answer is going to be it very much depends on the nature of the pass through costs. We see a lot of passthrough costs like a third party lab that's being managed, a lot of those can be described best by the patient curve, and then we can see some that can tie that to either kind of a visit schedule if there is an indication. The actual patient travel usually is pretty well indicated by the patient curve. CROs are putting like a weird printing fee as a pass through cost. Your guess is as good as mine, right? That's one of those like kind of you go back and Robbie's point, you recontract and say stop putting that weird stuff.
Erin Warner Guill: Pass-through cost forecasting varies widely. Some categories—such as third-party lab fees—are best projected based on patient curves. Others, like printing fees, are less predictable. We’ve seen customers use contractual benchmarks and real-time actuals to improve accuracy.
Sharon Langan: Really appreciate everyone joining today, and if there aren’t any more questions, we’ll wrap this up and say goodbye!
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