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 trial staff get approval for their budgets, with forecasts as accurate as possible.
It’s not hard to get forecasting wrong, say Trinity’s Alex Chiang and Adrian Watson. And 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 which 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.
RSTLNE: Improve Forecast Accuracy
There are a few key practices to include when forecasting for clinical trials, writes Chris Chan, executive director, R&D finance at FibroGen. These can be remembered with the acronym RSTLNE, which Wheel of Fortune fans will recognize.
R is for ‘Realistic Forecast’
Trial managers are often fighting to hold onto their budgets, 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 accounting and 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.
Tips for Budget Approval
Obtaining budget approval is a challenge, but there are strategies to improve your chances, notes Kunal Sampat, senior manager of clinical programs at Abbott Vascular. While they can be applied broadly to all budget negotiations, 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, he says.
- 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 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.
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 2 multi-site clinical trial in partnership with a pharmaceutical company to co-develop an oncology drug. The biotech company will run the trial in the US and Central and South America, while the pharma company will run the trials in Europe and the rest of the world.
What happens, the pair asks, when the key investigator site in the US wants to conduct a financial feasibility assessment to calculate the per-patient cost at the site? Questions related to planning, budgeting, study design, 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.
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, IRT manager at Novartis. IRT will help to optimize the supply chain, save time and money, and reduce the risk of low stock.
It’s vital that 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 allows for better predictive powers of future supply needs, Spoto explains.
Determine the Acceptable Level of Inaccuracy
Variance in forecasting predictions is inevitable but, according to the team at Bioclinica, the ideal variance should not exceed 3 percent. Often, though, many sponsors will accept error rates of up to 5 percent; others will consider an error rate of between 5 and 10 percent acceptable. It should be noted, though, that the average variance between forecasted and actual clinical trial costs is significantly higher, at 16 percent.
Of course, the greater the rate of variance, the more costly the ramifications that result from the error. A high error rate can affect ROI, future R&D budgeting, and impact earnings on future reporting periods.
When reconciling variances falls onto an already highly burdened trial team, the challenge becomes overwhelming. Part of this comes down to sponsors choosing a variable rather than fixed-expense model and outsourcing trial management to multiple vendors. The result has been ineffective financial management systems and lack of visibility among vendors. The effect is that trials are more challenging to execute and accurate forecasting is more difficult.
The Bioclinica team says that 80 percent of clinical trials suffer from months of delays costing as much as $35,000 a day, and just 10 percent of trials are completed on time. Indeed only 14 percent of clinical financial planners at pharma companies report that they are confident in their budget forecasts.
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 PFS Clinical. 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.
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