Forecasting Considerations throughout the Pharmaceutical Product Lifecycle

Forecasting Considerations throughout the Pharmaceutical Product Lifecycle

As published by PharmaPhorum 15th October 2024 Forecasting considerations throughout the pharmaceutical product lifecycle | pharmaphorum

Introduction

Forecasting is a critical component of product management, especially in the pharmaceutical industry, where it plays a vital role throughout the product lifecycle.

As a product evolves from the early development stages to market maturity, the focus of forecasting must shift to accommodate changes in available data, resource allocation, and strategic decision-making . This article explores the various considerations forecasters must take into account as a product progresses through its lifecycle, highlighting the key factors and approaches at each stage.

1. Preclinical Stage: Understanding the Opportunity

During the preclinical stage, the focus of forecasting is not necessarily on the product itself but on the broader opportunity within the disease area. At this point, there is limited information about how the product will perform in humans, and as a result, forecasts cannot be specific or detailed. Looking at the volume / revenue of past and current products within the disease, or conditions with a similar profile, provides useful guidance at this stage.

  • Data Limitations:

    The absence of clinical data means that forecasters rely on understanding the disease's unmet needs and the potential for improvement over existing treatments. For example, if a disease like Hepatitis C (HCV) previously had a cure rate of 60-70%, the introduction of a treatment with a 90-95% cure rate would signify a substantial opportunity.

  • Resource Constraints:

    At this stage, there is minimal resource allocation towards the product, and there is no extensive commercial team. Consequently, the forecasting effort is typically limited in scope and depth, focusing on broader market potential rather than detailed product performance.

2. Early Development (Phase I and II): Refining the Forecast

As the product enters Phase I and Phase II of development, forecasters begin to receive clinical data, although it is still not as granular as what will be available later. This stage marks the beginning of understanding the product’s performance in humans and its potential positioning in the market. At this stage, the general understanding of the market will have evolved as a result of the time taken since the pre-clinical stage activity. For example, competitors may be closer to launch and this intel can be added to the forecasts.

  • Clinical Insights:

    Forecasters start to assess whether the product meets expectations set during the preclinical stage, particularly in terms of performance and safety. This allows for more specific predictions about the product’s potential impact on the market.

  • Market Segmentation:

    Forecasters refine their understanding of the disease opportunity, focusing on specific patient groups and market segments. If the product is targeted at a niche population, this could significantly alter the forecasted potential and influence strategic decisions.

3. Late Development (Phase III): Strategic Forecasting and Planning

Phase III is characterised by a more comprehensive understanding of the product’s potential, as clinical data becomes more robust and detailed. This stage is crucial for developing strategies for product launch and market penetration.

  • Sophisticated Modelling:

    Forecasting becomes more granular and sophisticated, incorporating various scenarios to answer strategic questions about market entry and competitive positioning. Country engagement now begins in order to inform decisions on resource allocation, sales force deployment, and country-specific launch strategies.

  • Internal Strategy Development:

    The focus shifts towards integrating forecasting into broader business strategies, ensuring that the forecasts align with the company's goals for the product. This requires a deep understanding of the key drivers behind the forecast and how different market dynamics might influence the product's success.

4. Pre-Launch and Launch Stage: Short-Term Forecasting

As the product approaches launch, the forecasting focus narrows to shorter time horizons, emphasising the first few years post-launch. This period is critical for finalising commercial strategies and ensuring that the company is prepared to meet market demand.

  • Granularity and Precision:

    Forecasts must now be detailed and precise, as they inform critical decisions about production, supply chain management, and sales strategy. Forecasters work closely with various stakeholders, including manufacturing and sales teams, to ensure that all aspects of the launch are well-coordinated.

  • Scenario Planning:

    With the product close to market entry, forecasters engage in scenario planning to anticipate potential market changes, competitor actions, and regulatory developments. This helps the company stay agile and responsive during the crucial early years of the product's life on the market.

Case Study: The Importance of Competitive Data in Forecasting

Understanding the competitive landscape helps companies anticipate potential challenges and make strategic decisions. Even if there’s no competitive market when you start developing your product, someone else will no doubt join the race later on. This can introduce significant uncertainty, as even a new product that is two years behind in development could leap ahead if your product faces delays or fails to gain first approval.

The case of Biogen’s Alzheimer’s drug, aducanumab (Aduhelm), highlights the risks of pushing to be first-to-market without robust data. Despite receiving FDA approval, the drug struggled due to concerns over its efficacy and safety, ultimately leading to its withdrawal from the market. This example illustrates the importance of not only monitoring competitors but also ensuring that the rush to launch does not compromise the product’s success. A well-informed forecast, supported by competitive data and scenario planning, can help navigate these challenges and ensure long-term market viability.

5. Post-Launch: Monitoring and Adjusting Forecasts

Once the product is on the market, forecasting becomes an ongoing process of monitoring performance and adjusting predictions based on real-world data.

  • Performance Tracking:

    Forecasters analyse sales data, shipment volumes, and market reception to assess how the product is performing relative to expectations. This information is used to refine short-term forecasts and ensure that sales targets are met.

  • Long-Term Considerations:

    While short-term forecasting remains a priority, forecasters also keep an eye on medium and long-term trends that could affect the product's lifecycle, such as new competitor entries, changes in market conditions, or potential regulatory shifts.

6. Maturity and Decline: Lifecycle Management

As the product reaches maturity, the forecasting focus shifts again, often to manage the decline phase and prepare for the end of the product’s lifecycle.

  • Resource Allocation:

    With the product stabilising in the market, resources dedicated to forecasting may decrease, especially as the focus shifts to newer products in the pipeline. However, forecasting remains essential for managing lifecycle events like loss of exclusivity and planning for the impact of generic or biosimilar competition.

  • Lifecycle Management Strategies:

    Forecasters may also be involved in developing strategies to extend the product's lifecycle, such as through the introduction of new formulations or administration methods. Scenario planning becomes crucial here, as companies evaluate the return on investment for these strategies versus the anticipated revenue from extending the product’s market life.

product lifecycle considerations

Final Thoughts

The most effective forecasting is dynamic and evolves as a product moves through its lifecycle. An event-based approach adds significant value and is considered best practice in the pharma market, though many models lack this feature. Key transition points – such as moving from phases 1/2 to 3, and from 3 to 4 etc. – require forecasters to adapt their focus, methods, and level of detail to meet the changing needs of the product and the organisation. A system such as the FC365 cloud-based platform can seamlessly manage these transitions and incorporate best-practice models with transparency and the ability to quickly run scenarios , leading to more effective forecasting.

From the early stages of understanding market opportunities to the detailed planning required for a successful launch, and finally to managing a product’s decline, forecasting remains an indispensable tool for guiding strategic decisions and ensuring the product’s success in the market.

Author

Image of Andrew Ward

Andrew Ward, Head of Implementation at J+D Forecasting.
An expert in the pharmaceutical analytics space since 2002 and leading a consultancy team in delivering forecasting solutions including software application development at J+D since 2014.

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