Sales forecasting


The life sciences industry operates on timelines that are longer than almost any other industry. It takes years, often decades to bring a new drug to market and there are myriad variables that can slow or complicate that journey. The ability to forecast the future of the pharmaceutical market, patient population and potential pharma sales is critical in ensuring that any drugs that do make it to market are commercially successful. 

Pharma companies do not operate in a vacuum and must constantly evaluate and re-evaluate the market to understand what their competitors are doing, which treatment areas present the most opportunities and which patient populations they can best serve. All of this requires the ability to understand the current landscape but also the future – medium and long term. Managing a drug pipeline, whether it contains dozens of candidates or as single asset is a job with many pitfalls, all of which must be carefully negotiated. 

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What are the areas that impact pharmaceutical sales forecasting?

There are many elements that make forecasting a challenge, but there are several key areas that pharma companies must pay attention to in order to run effective forecasts.


Competitive landscape:

There are several therapeutic areas where competition is becoming fierce, particularly in certain areas of oncology and increasingly in some rare diseases. Any pharma or biotech company needs to manage the constant stream of conferences, press releases, clinical trial results and FDA announcements to understand how the competitive landscape is changing. Your drug may be developing nicely, but if a competitor’s asset gets a complete response letter from the FDA, that’s likely to impact your pipeline (not to mention share price) as well. The sands are always shifting, which makes pharma industry forecasting hard, but you must stay on top. 

Patient Population:

The addressable patient population is your true potential market – is it really the size you think it is? Are you clear on the scale of unmet need in a particular therapeutic area? As science evolves and treatments become ever more personalised, you need to consider patient histories, biomarkers, and differing levels of severity to truly understand the size of your market. All of which impacts your ability to effectively forecast the potential success of your drug. 


For pharma companies with multiple assets in development, a prioritisation strategy is key. Resources are limited, even for the very largest drug companies so it’s important to ensure that you’re diverting your energy (and money) into the drugs with the highest chance of becoming commercially successful. Any new drug comes with an element of risk, so you need to weigh up all the factors that many impact commercialisation before you throw everything at a particular asset. Forecasting is a crucial part of planning your go-to-market strategy, and while you might not have all the data you need, it’s better to be clear eyed about what you do have so you can prioritise the right asset for the right market at the right time. 

Drug differentiation:

Unless your drug or medication addresses a large audience with a completely unmet need, you will face competition. In some cases, from well-established drugs that are trusted by doctors and which payers are prepared to fund. The success of your drug depends on you winning over that audience – so what if your differentiation strategy? Is it based on efficacy? Reduced side effects? Better value for money? Mechanism of action? Whatever it is, you need to understand how willing physicians and payers will be to take your drug over an old favourite if you are going to get your sales forecasting right. 

What else is needed for effective pharmaceutical sales forecasting?

Understanding the market, your competitors and your audience is a great start but there is more to forecasting for pharma companies than that. Forecasting requires input from multiple sources that are constantly evolving – every FDA decision, clinical trial setback (yours or someone else’s), IPO, merger and funding round influences the future of the industry and effective forecasting needs to account for that. 

Consensus Pharma forecasting is one proven approach to managing the complex, interconnected nature of the market. While forecasts from individual brokers are useful, bringing together thousands of forecasts helps provide a more balanced view. Evaluate Pharma provides users with 12,500 consensus forecasts to 2028, and the most comprehensive coverage of drug sales at an indication level with 6,000 worldwide and US consensus forecasts. Our unique historical archive spans 1.5m+ consensus forecasts of 10,000 products dating back to 2003.

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What is the future of pharma forecasting in the life sciences industry? 

However, while consensus forecasts are a great way for pharma companies, biotechs, financial investors and consulting firms to get a clear picture, there are always new approaches being developed. Data science is increasingly providing new ways to create dynamic forecasts which are constantly adapting to changes in the market and providing risk-assessed forecasts. Intelligent forecasting, as the approach is often known, also considers the past, present, and future drivers of commercial and clinical success in real time. As a forecasting methodology, it is powered by machine learning and predictive analytics that allows complex real-world clinical development and commercial questions to be addressed dynamically and with up-to-date information.

Data science and in particular machine learning and AI are often seen as a black box that operates without explanation. While this may seem to be the case, in fact it’s much better viewed as a way of dealing with issues of scale and complexity. Forecasting naturally lends itself to machine learning based on these very elements and it hugely reduces the amount of manual work that must be put into forecasting. For smaller firms with limited resources, forecasting is often a job that can be done sporadically at best, and often only once a year. But with change happening across the industry on a daily basis, this isn’t sufficient and data science provides a clear way for the little guys to play with big pharma on something a little closer to a level playing field.

With the global pharmaceutical market forecast to reach sales of £1.6 trillion in 2028, despite the looming patent cliff, it’s vital that companies across the industry – from big pharma to small biotech, medtech and supply to pharma can get to grips with forecasting effectively.

How does Evaluate help? 

We combine deep industry knowledge and analytical expertise to give you a solid foundation for your strategic decisions.

Over twenty years we have developed methods to smooth out outlying pharmaceutical data points and differing methodologies, transparently and consistently. So, you’ll always be able to understand the data you’re working with and what it means for your business. 

To add to our market-leading pharma intelligence delivered through consensus forecasts, break through the limitations of conventional forecasting with comprehensive and granular coverage of assets, unrivalled accuracy and multi-dimensional analytics powered by machine learning. 

Machine learning takes into account clinical trial and market intelligence data, R&D costs and development timelines to deliver highly accurate predictions of drug development success, both from commercial and regulatory perspectives. 

In addition, we cover the medtech market, looking at device company clinical trials, financial drivers, and drug device company clinical developments. 

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