Implications Of Inaccurate Forecasting On Biologic Drug Substance Manufacturing

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Source: Patheon
Implications Of Inaccurate Forecasting On Biologics Drug Substance Manufacturing

Author: ORC International
Large molecule drug substance manufacturing and demand forecasting is riddled with complexity. The long cycle time and short shelf life of biologic drug substance makes it difficult to adapt the supply chain with agility, even at the earliest stages of development. As a result, inaccurate demand forecasts can have significant implications for companies developing biologics. And with less industry-wide available capacity for biologic production, it is increasingly difficult to locate capacity to respond to demand changes and ensure products achieve commercial goals.
To better understand the issues that biopharmaceutical companies face when planning for clinical and commercial biologic drug substance manufacturing and supply needs, ORC International conducted interviews with biopharmaceutical executives in North America and Europe who consistently utilize forecasts for drug substance and commercial manufacturing planning for biologics. This research explored the causes, consequences, and potential  solutions to forecasting challenges specifically related to biologic drug substance manufacturing.
This report addresses key themes that emerged from these discussions, highlighting approaches to demand forecasting, implications of inaccurate forecasting, and practices and strategies in place to optimize drug substance development planning and minimize risks.
IMPLICATIONS OF INACCURATE FORECASTING FOR BIOLOGICS
There are substantial costs associated with producing and storing biologics. When companies are forced to throw away a full batch of a biologic, they are faced with considerable losses in investment and delays in the product development timeline.
With such high stakes in the biologics market, the implications are severe when demand is overestimated and companies face unanticipated difficulties upon launch. Take, for instance, the unforeseen healthcare industry response to Zaltrap®1 pricing ($11,063/patient/month): Sanofi and Regeneron discovered, after launch, that oncologists at Memorial Sloan Kettering Cancer Center refused to prescribe the drug when there were far more affordable alternatives available. Demand dwindled and the companies had to cut the price of Zaltrap by half 2.
There’s also a lot on the line when companies underestimate demand. In the case of Abbott’s Humira®3, demand was continuously underestimated as a result of new indications and increasing popularity among prescribing physicians.
Humira exceeded its first-year sales estimates, reaching $1 billion by year three, and the firm had to rapidly develop capacity to meet demand. The drug is now approved for nine indications, with worldwide sales of over $10 billion4. When demand is underestimated in cases such as this, it’s very challenging to modify an existing production process or locate the additional capacity. Many companies tend to overestimate their demand, viewing excess inventory as a lesser risk than falling short of demand and missing growth opportunities.
Capacity constraints are expected to continue into the future. The industry is expected to operate at a 73% utilization rate by 20205, which is viewed as full utilization. Available capacity is often held by CDMOs to respond to demand increases and additional indication approvals for a product. For that reason, many biopharmaceutical companies choose to keep all manufacturing in one CDMO to build stronger relationships and build better processes to enable them to adjust to demand changes. Biopharmaceutical companies are increasingly relying on CDMOs to manage production and help mitigate risks. In fact, $2.6 billion is currently being spent on biologics outsourcing in this space6. Today’s biopharmaceutical companies are developing strategies to anticipate demand and minimize capacity constraints.
FORECASTS INTEGRATED EARLY IN PLANNING PROCESS
Given the implications of under-or overestimating biologic demand, developing realistic forecasts is critical. Because capacity must be reserved well in advance of biologic production, forecasts are developed to inform manufacturing commercialization plans early in development.
Clinical development timelines for biologics last, on average, between 60 and 80 months, and only 11% of preclinical biologic products are ultimately approved7. This study found that biologic drug substance manufacturing decisions are primarily made between Phase II and Phase III clinical trials, which builds in risk for the innovator companies because of the high clinical failure rates. For some therapeutic areas such as oncology, demand estimates are modeled at the end of Phase II in order to be prepared for accelerated approval.
“If you’re contracting out in a Phase III facility, companies that are on tight budgets like to lock in commercial pricing at the Phase III stage. That can be challenging, because if you don’t know your demand, you may be negotiating something that’s totally moot or not to your advantage.” Vice President – Biotechnology Company, North America
Difficulties in forecasting for clinical trials
Forecasting demand for clinical trials has unique challenges relative to forecasting for commercialization. Because clinical trial designs often change and evolve, companies struggle to gain early insight into factors such as the appropriate dosage, frequency of administration, and number of patients. One biotechnology company director notes that changes in clinical plans have “a big impact on inventory and product availability, and that puts a lot of pressure on the operation side to adjust very quickly.” Another common challenge arises when new indications come to light during clinical development, increasing the need for clinical drug supply. Additional trials to test new indications are common and very complicated from an operations perspective.
 

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