Strategies for More Accurate

Strategies for More Accurate Clinical Trial Forecasting and Budgeting

Anyone who has had to sell a budget proposal knows how challenging it can be. But with the right strategies to forecast clinical trial requirements and accurately calculate the necessary expenditures, trial managers and sponsors can feel more confident in the process.

 

This post explores some of the best strategies and practices to ensure clinical trial staff get approval for their budgets, with forecasts as accurate as possible.

Forecasting Models

It’s not hard to get forecasting wrong, say Trinity’s Alex Chiang and Adrian Watson. And those errors lead to inaccurate predictions and bloated processes. However, the pair provides tips for successful forecasting models.

  • Keep segments to a minimum. Rather than trying to forecast for multiple market segments, choose simplicity to avoid repetition. Forecasting models work better when they are less granular.
  • Remember that models are not timeless. Forecasting early-stage assets compared with products late in their lifecycle will likely require different forecasting models. The best model is one that solves requirements and displays knowledge at a specific time.
  • Govern data better. With multiple data sources — distributor data, hub data, audit data, claims data, EMR data, ATUs, demand studies, chart audits — integration is not always simple. Trying to make data fit your assumptions will impact your forecast output, Chiang and Watson explain. Instead, set out with a clear data governance plan. Know all the data available and what is best suited to each assumption.

Forecasting has also long been a challenge because many elements related to accurate forecasting, such as effort required, are difficult or impossible to quantify. A 2011 article by Pam James and fellow authors in JNCCN describes an attempt to quantify effort expended at various stages of a cancer-related clinical trial using a digital platform created for that purpose.

The researchers discovered that they learned a great deal about the amount of time clinical trial teams spent on certain tasks but very little about how much effort each particular task required. Some tasks required a great deal of time but low effort; others required relatively little time but a great deal of effort in the form of intense concentration or applied skills. Choosing the right variables to track plays a key role in forecasting accuracy.

RSTLNE: Improve Forecast Accuracy

There are a few key practices to include when forecasting for clinical trials, says Chris Chan at Clinical Trials Arena. These can be remembered with the acronym RSTLNE.

R is for “Realistic Forecast”

Trial managers are often fighting to hold onto their budget, Chan explains. They may have spent only a quarter of their budget during the majority of the trial period and still argue that they need the rest of the budget to spend in the remaining time. For payers, this argument makes little sense.

Trial managers, however, are reluctant to have their budgets lowered as they’d potentially have to deal with the consequences of overspending on a lower forecast. The solution, Chan says, is to divorce realistic forecasting from approval to spend and allow the team to lower their forecast with the provision they can spend the original budget should necessity require.

S is for “Systems Understanding”

Multiple systems are often inevitable. Finance might use different systems for payments, budgeting, and planning, while R&D will use a CTMS with various financial tracking modules. Add to the mix CROs’ benchmarking tools and resource management systems, and you have a lot of systems in play. Training personnel from R&D and finance in using multiple systems, for which they would not ordinarily be responsible, is essential.

T is for “Top-Down Guidance”

Share high-level targets with teams at the outset, Chan advises. This will help with initial forecasting, even if the budget is lowered later on, as forecasting teams can generate alternative scenarios above or below the budget based on various factors.

L is for “Low-Impact Forecast Items”

Don’t waste time on low-impact budget items. Devote an amount of time relative to the importance of the budget item. Site monitoring expenses, for example, require greater time and diligence on forecasting than IVRS costs, Chan says.

N is for “New Trials and Activities”

Do not conflate risk probabilities of unstarted trials with ongoing trials. The former requires a different risk probability factor as there is a different degree of uncertainty.

E is for “Expense Estimates”

Also known as financial accruals, poor understanding of expense estimates will likely result in inaccurate forecasts, Chan warns. Accruals refer to the monthly task of estimating the total value for a certain period of all the clinical trial work completed by CROs, central labs, investigator sites, consultants, and other partners.

However, many of these partner components will adopt certain accrual methodologies, such as straight-line, cash basis, or models-based methodologies, which will impact estimates. Understanding your company’s specific accruals methodology is essential for accuracy.

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Tips for Budget Approval

Obtaining budget approval is a challenge, but there are strategies to improve your chances, notes Kunal Sampat, host of the Clinical Trial Podcast. While they can be applied broadly to all budget negotiations, he says that these strategies will work best when sites are looking to increase their study budget and sponsors or CROs are aiming to control clinical trial costs.

  • Never make up numbers. It sounds obvious, but Sampat says that even if exact costs of specific tasks are unknown, show your reasoning and calculations that helped you arrive at your estimate. Be objective and transparent.
  • Deliver a considered enrollment plan. Budgets are more likely allocated when CROs or sponsors can see how patients will be recruited and enrolled. They need to see that the study will likely be a success. And a comprehensive enrollment plan, Sampat adds, will help you negotiate a higher per-patient grant amount.
  • Ask questions and listen. Find out how the relationship can be mutually advantageous, how disagreements can be resolved, and how better decisions can be made.

Having a budget approved promptly can help minimize or prevent clinical trial delays. Start-up delays are a common problem for clinical trials, note Sandra Smith and Suzanne Caruso at WCG Clinical. By using budgeting best practices and thinking carefully through key questions that will arise at the approval stage, teams stand a better chance of rapid budget approval — keeping a clinical trial on track.

Financial Benchmarking

Benchmarking, generally defined, refers to an organization judging itself against the processes, output, and successes of its competitors. Financial benchmarking, then, requires using internal and external financial data to improve an organization’s finances, cost-efficiencies, and productivity, say Larry Ajuwon and Mathini Ilancheran, at RHIEOS-Ventures and Beroe Inc., respectively.

The pair provide the example of a biotech company planning a phase ll multi-site clinical trial in partnership with a pharmaceutical company to develop an oncology drug. The biotech company would run the trial in the U.S. and Central and South America, while the pharma company would run the trial in Europe and the rest of the world.

What happens, the pair asks, when the key investigator site in the U.S. wants to conduct a financial feasibility assessment to calculate the per-patient cost at the site? Questions related to planning, budgeting, study design, and requirements for regulatory approval can all be better answered if all of the parties can benchmark their pricing and cost data. To enable accurate benchmarking, it’s essential to define the metrics required, such as median, ratios, or indexes, and how financial benchmarking results will be analyzed.

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Keep the Supply Chain in Check

Accurate forecasting depends in part on greater control of the supply chain. And this can be achieved with interactive response technology, writes Francesco Spoto, system and opex manager at Novartis. IRT will help to optimize the supply chain, save time and money, and reduce the risk of low stock.

IRT trial managers design robust but lean forecasting solutions backed by data. Because it fills the gaps between supply production, packaging and distribution, site inventory, and patient engagement, IRT can help either on its own or integrated with other supply chain systems. Using real-time data, forecasting of clinical supplies can be updated regularly throughout the trial to match actual demand.

IRT systems work by running simulations projected from data gathered from previous events, trends, mathematical models and feedback, all built into certain trial-specific parameters. During the trial, IRT reforecasting capabilities allow for better predictive powers of future supply needs, Spoto explains.

Deliver with Detail

Any budgeting forecast requires attention to detail, which is why the pre-study budget and contract negotiations are essential, writes the team at Compliance Online. The more detail, the better the chance of the budget being approved. This includes noting the schedule of events so all study procedures are accounted for. Distinguish between essential and optional procedures within the protocol.

Pre-study periods are also important to make calculated estimates as to what the study will need over time. This includes items such as reimbursement for annual administrative costs, pharmacy use and storage fees, and fees for storing documents. Remember to include a line in the budget for other expenses — the unforeseen and unpredictable (yet often inevitable) costs associated with running a clinical trial.

Planning ahead, paying attention to detail, and harmonizing processes and systems empower trial managers to budget and forecast trial requirements accurately. Plenty can go wrong with these important trial demands, so it’s imperative to place accuracy at the core of all future projections and predictions.

Updated 10/24/22; Originally published 04/02/19.
Images by: rawpixel/©123RF Stock Photo, langstrup/©123RF Stock Photo, fizkes/©123RF Stock Photo

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