Impact Of Incorrect Forecasts On New Drug Product Launches

Manostaxx
Pharmaceutical companies around the world are under tremendous pressure – from regulators, legislators, payers, and patients – to reduce the cost of drugs. In response to the outcry for cost-cutting, pharmaceutical company leaders are examining every aspect of their business to determine where they can derive savings, particularly when planning for the launch of a new product. Pharmaceutical company marketing executives have become more accurate in positioning their new product in the marketplace, profiling prescribers, and understanding and responding to the reimbursement landscape. What is still a quagmire for pharma companies is predicting the actual demand for products and the timing of that demand.
In today’s drug manufacturing environment, demand forecasts provide critical input that ultimately affects pharmaceutical companies’ decision-making processes1. Pharmaceutical companies utilize drug forecasts to design clinical programs, position sales force resources, allocate geographic resource distribution, and obtain company or licensing assets2. However, achieving accurate forecasts is extremely challenging, especially for new drug launches. Although drug forecasts combine an assortment of scientif­ic, clinical, regulatory, and commercial data, it is difficult to capture a new drug’s potential with a single numerical value because countless factors influence and contribute to that drug’s demand3. Each new drug is susceptible to variations in the external environment, the uncertainty of drug development, and the unpredictable actions of competitors4. As a result, drug forecasts are often significantly inaccurate5.
This implies that many companies depend on inaccurate forecasts for in-house production of product, hoping that they can manage fluctuations in demand. For those companies relying completely on outsourcing manufacturing, it means procurement of “too much or too little” capacity. One study found that greater than 60% of drug forecasts over- or underestimated peak revenues by more than 40% of the actual peak revenues6. In fact, a substantial number of forecasts were overly optimistic by more than 160% of the actual peak revenues of the product7. Other studies find that about two-thirds of the new drugs fail to meet prelaunch consensus expectations for their first year on the market8. Moreover, drugs that fall short during their first year on the market continue to fall short for the following two years9.
When Lipitor launched, its peak sales were forecasted at $800 million per year10. However, the drug generated $12.8 billion peak sales, making it the highest-selling drug of all time11. Sanofi and Regeneron set the price for their colorectal cancer drug, Zaltrap, at $11,063/patient/month12. But the company was forced to cut the price in half when oncologists at Memorial Sloan Kettering Cancer Center refused to pre­scribe Zaltrap because cheaper alternatives already existed13.
Incorrect forecasts have serious consequences for operational efficiency and for the bottom line. When a company is unable to meet demand, the lack of inventory can result in loss of sales, product risk, and overworked employees. It’s estimated that a delay in launch costs an average of $15 million per drug, per day14. The variance in peak sales estimates was still 45% versus actual peak sales 6 years after the drug has launched, reflecting continued uncertainty even as new information becomes available.
On the other hand, overestimating demand results in mis­appropriating capital15. Manufacturers may be forced to mark down the price of the product, destroy inventory and/or close plants and lay off employees. This means that a company would lose the roughly $500 million it cost to acquire its pharmaceutical plant. In each scenario, worker morale is low, product quality suffers, and reputation is damaged16.
Pharmaceutical companies will launch some 400 new products in the next three years, up 146% from 200517. Inaccuracies in demand forecasting, combined with increases in complex manufacturing processes, are driving the need for more choices in manufacturing solutions. In fact, 60% of new compounds entering development need unique manufacturing processes due to their formulation or delivery system18. These growing demands demonstrate that there is a fast-growing market in need of alternative, more flexible manufacturing options.
To better understand the issues that pharmaceutical companies face when it comes to forecasting accuracy, we conducted both phone and online surveys with 50 pharmaceutical executives who consistently utilize launch forecasts to predict manufacturing planning and volume. The surveys aimed to address current processes around forecasting, key issues that arise from inaccurate forecasting, and how forecasting needs will change over the next few years due to evolving organizational needs.
Demand forecast is a primary decision-driver
The single most important factor that influences manufacturing decisions is demand forecasting. Almost all respondents agree that the demand forecast influences manufacturing decisions regarding capital cost and outsourcing for product commercialization a great deal. There is broad recognition that failure to appropriately predict demand has real consequences on a firm’s reputation and bottom line.
“Launching a new product requires a fully defined approach and strategy, for which we need to address unfulfilled needs in a disease area, which is a challenge. Secondly, we need deep insight into the customer in order to differentiate in the market. To execute in both of these ideas, we need accurate information on market demand, which is really difficult because we are not sure whether our product will be approved, and if it is, to what extent it will be accepted by doctors and consumers.”
 Director – Marketing, Large Pharmaceutical Company, United Kingdom
Variable factors in predicting demand
A number of factors influence and contribute to a drug’s demand. In order to accurately forecast demand, pharmaceutical companies need to feel comfortable with and confident in the data they have for all of the variables used to calculate demand. In speaking with industry professionals, it was apparent that there is a split in how they view different demand-driving variables.
Manufacturing: Predictable costs, unpredictable processes
Certain hard costs, like manufacturing expenses and raw material costs, are fairly easy to predict. Respondents also felt confident in their understanding of their unique products, from the formulation processes to pricing structure. These areas represent costs with little expected variation, and are mostly in the control of the business as they can seek lower-cost ingredients or other raw materials. Companies can also look to alternative formulation processes or consid­er insourcing or outsourcing their manufacturing. However, options can be limited in such a complicated environment.
“I would say that the manufacturing cost that would be incurred during the whole process is the most predictable one, and one can expect to have the least amount of variances here. But as you know, it’s a very complex thing and we solely don’t have control over it, so sometimes it has become uncontrollable in the past.”
 Associate Director – Global Business Development, Large Pharmaceutical Company, United States
While the overall cost of the manufacturing process is relatively easy to ascertain, predicting the exact levels of active pharmaceutical ingredients (API) and general manufacturing capacity needed are more challenging variables to address. It can take a significant amount of time to acquire and test the quality of an API prior to launching production. Lead time is also a struggle to predict, as manufacturing sites need some notice to be able to have the capacity to incorporate the production of a new product, and companies will generally need to place orders before seeing actual market demand.
Without knowing the overall market appetite for the product or the rate of growth it will experience, it can be tremendously difficult to appropriately budget time and resources for manufacturing the product.
Market uptake is erratic
The variables that tend to be most difficult to forecast are more intangible predictions around the levels of market uptake, physician propensity to prescribe, and out-of-pocket costs for patients. These are areas where companies have struggled to develop new thoughts on how to broach the calculation challenge, as historically most have relied on using the incidence of a particular disease in a region and applying a potential market share to estimate the potential demand. This method fails to accurately gauge the acceptance rate among physicians and patients.
“You’d expect a certain type of doctor to use a product, but you find out in the end that doctors don’t really want to prescribe it, because they are committed to using the alternate drug for something … Companies obviously do a lot of research to see what kind of doctors they should be going after for prescribing things, but sometimes there’s an unknown and that’s just that certain doctors are trained to do certain things, and they see value in the amount of training that they have, and they may not want a simple alternative.”
 Senior Director of API Manufacturing, Mid-Size Pharmaceutical Company, United States
In estimating demand, companies must be cognizant of the willingness of the market to adopt a product, but also of what their competitors are doing in the marketplace to realistically predict their potential market share with a new product. Pharmaceutical companies are participating in a highly competitive market. Competitors can respond to new product launches in different ways that can be difficult to predict, especially because of the lack of structure in today’s reimbursement environment.
Integrating demand forecasts into production plans – adaptability is key
Many companies have developed strategies to deal with the hurdles to accurately predicting demand. When they feel comfortable with their estimates, they face their next challenge – incorporating the demand forecast into their full commercial production plan.
As demand forecasts are made during the initial phase of drug development when there is little clinical information to base sales projections and reimbursement strategies on, companies need to be prepared to make adjustments to their expectations as new data comes to light and as they face variations in supply chain patterns. It is best to look at the production process as a balancing act between chang­ing demand forecasts and real manufacturing capacity. As one Operations Director put it, there “… should be perfect coordination and communication between manufacturing and products team in alignment with the forecasting team so that we are updated on the demand in market.”
Respondents often cited difficulty in coordinating different teams to meet timelines, but failing to do so can directly affect market share and brand reputation. Again, a long lead time is necessary for production to develop appropriate plans, allocate resources efficiently, maintain schedules, and minimize waste. Some respondents noted that it takes about two years to completely develop a product after electing to move forward with its production.
This level of planning and lead time can be managed, but it is hard for many companies to be agile enough to adapt their practices and make adjustments as demand forecasts change. This often leads to situations of overestimating or underestimating demand.
“The biggest challenge is being able to meet the demand forecast. So obviously when you do your annual projections, everyone’s very optimistic at the beginning of the year, but once you start to realize your sales, it may be 35, 40, 50% of your forecast and you have to make adjustments, so that was the hardest thing.”
 Former Senior Manager of Global Supply Chain Operations, Specialty Pharmaceutical Company, United States
When facing these challenges, companies have to evaluate the benefits of producing their new product in-house versus outsourcing manufacturing, based on their demand forecasts. This is simplified if a company has a good sense of its future sales volumes and can clearly determine whether production can fit into an existing contract manufacturer. If capacity seems inadequate within an existing structure, a company would need to decide if a capital acquisition would be worthwhile and cost-effective versus finding an alternate partner. It can be time-consuming and costly to alter manufacturing processes, so it is imperative that demand forecasting be as accurate as possible.
Forecast overestimation or underestimation is the norm
Pharmaceutical respondents surveyed report high rates of overestimation and underestimation with demand forecasts. Companies err on both sides of actual demand, both underestimating and overestimating the uptake of a new product, leaving them to deal with a distinct set of consequences on either end. When a company is unable to meet demand, the lack of inventory can result in loss of sales, product risk, and overworked employees, while overestimating demand results in a misappropriation of capital.
“If you’re preparing for a big launch and then it looks like the launch didn’t go as well as planned, then the question is, do you end up having to reduce your manufacturing capability because you just don’t need what you’re doing so far? And then the flipside is, if you don’t get the forecast right and you don’t have enough product for launch, you don’t want to stock out, because it’s a problem that ruins companies’ credibility, and the FDA really doesn’t like it.”
 Senior Director of API Manufacturing, Mid-Size Pharmaceutical Company, United States
The majority of companies are over- or underestimating demand by up to 25%, though instances over 50% were reported. Respondents cited that they often overestimate demand when there is greater market volatility or when they were overly optimistic in their forecasting. Generally, underestimating resulted from not having enough background data to support forecasting information. One respondent speculated that the therapy area served could also contribute to the variation between forecast and actual demand.
“Depends on the product in the portfolio. Primary care, which is more generics, I think there’s a little bit of overestimation, and for other fields, where there is like an orphan indication, I won’t say underestimated, but appropriately estimated because those are a little easier to predict since the population is much smaller than for something more generic.”
 Associate Vice President – Research & Development, Mid-Size Pharmaceutical Company, United States
Incorrect forecasts have serious consequences to operational efficiency and to the bottom line. As stated, adverse effects of over- or underestimation often center on reputational damage. Particularly in cases in which demand was underestimated and production fell short, a company can face a fair amount of backlash both internally and externally. Investors and employees often lose trust in management, while suppliers and customers face disappointment with not having a new therapeutic option.
If companies lose market share as a result of their estimation error, that too can damage their credibility, as competitors take advantage of the position and bolster their own reputations.
Operationally, there are costly consequences of poorly estimating demand. When adjusting production to new sales forecasts, companies can lose days of production. This may force them to change orders to their suppliers and waste available capacity at manufacturing sites.
“I’ve paid penalties. Some of my CMOs have had lost days of production that they had planned and committed to us that they had to cancel, and couldn’t find someone else to fill the slots. In my previous company we had biologics that had really long cycle and lead times that had commitments that were way out and it’s hard to rebook that time in the short term if it’s already committed. So yeah, there’s been production time loss with forecasts.”
 Director – Supply Chain, Specialty Pharmaceutical Company, United States
In many cases of overestimation, companies have to destroy inventory when either their raw materials or their completed products surpass their shelf lives.
“We had a few product lines that had long lead times so we didn’t have to produce them as often, but as a result of that, sometimes we would have to destroy expired material.”
 Former Senior Manager of Global Supply Chain Operations, Specialty Pharmaceutical Company, United States
Overall, overestimating and underestimating demand are costly misjudgments that are too common in the industry. They can regularly impact a brand’s reputation. Avoiding layoffs and negative patient health outcomes as a result of demand forecasting is essential to reputation preservation. While neither of these issues transpire as often, the occurrence of either resonates longer with a broader population, sometimes leaving irreparable brand damage.
“I’d say one of the challenges is getting the forecasting right. So if it’s a brand new product and there’s nothing else like it on the market, then at least in the experience I’ve had so far, we’ve tended to over-forecast, and as a result, that means that for manufacturing, at least in one case, the increased staff to prepare for launch and launch didn’t, just didn’t have the uptake that was originally forecasted, and as a result, a year later, we underwent layoffs. So that to me is probably the worst that I’ve seen so far.”
 Senior Director of API Manufacturing, Mid-Size Pharmaceutical Company, United States
Combining insourcing and outsourcing for optimal efficiency
To address forecasted demand for a new product, most companies will first consider their in-house capabilities. It allows more control over production standards and mitigating changes if the projected demand does not exceed the production capacity.
Companies will outsource for a number of reasons. If they do not have in-house capabilities, they will need to locate an alternative site. The costs to build and maintain manufacturing facilities are significantly higher and riskier than working with an outsourcing facility. More commonly, companies outsource because they do not have enough available capacity in their own sites to include a new product.
“It actually depends on the product because sometimes we have the facilities in-house, or even if we don’t, we tend to build a facility and repurpose the existing lines. But in the case when it’s hard to maximize the facilities, then definitely we go for outsourcing.”
 Associate Director – Research & Development, Specialty Pharmaceutical Company, United States
For that reason, a large number of companies are using a mix of both in-house and outsourced production to maximize their options. It is fairly easy for some companies to extend their lines to include similar products that do not require entirely unique supplies, equipment, or skills. Outsourcing for these companies is generally reserved for the products that would have too many associated costs to begin production or instances when there is simply not enough capacity to produce in-house.
There are a number of factors to consider when deciding where to produce a new product.
“This decision is made after considering various aspects, like the facilities, resources, capabilities, equipment, cost etc. and also uncertainty regarding demand and market size. On the basis of all these factors, we tend to outsource the manufacturing.”
 Associate Director – Marketing, Large Pharmaceutical Company, United States
Forecast uncertainty drives outsourcing
One of the biggest motivators to outsource is a higher degree of forecast uncertainty. In fact, more than three-quarters of respondents noted that the less certainty they have about demand, the more likely they are to outsource, even if they do have the capacity to produce the item in-house. As demand forecasting remains a significant hurdle, nearly all respondents claimed to have unused or underutilized facilities in their network, though underutilization was generally kept below 25%. The decision to outsource is made at a high level to mitigate risks from incorrect demand forecasts.
Various departments and roles collaborate on the decision to….
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