The following is a guest article by Lance Hill, Founder and CEO at Within3
Pharmaceutical launches fail at an alarming rate. According to research by market intelligence firm Sedulo Group, 56% of drug launches currently miss expectations, while 73% fail to meet revenue goals. While the industry has made advances in R&D and clinical processes, persistent gaps in data integration, organizational alignment, and trust in emerging technologies continue to undermine launch execution.
Why Pharma Launches Fail
Alternate: The primary reason for launch failures is an incomplete understanding of the market. Without a clear grasp of the target market, organizations may struggle with inaccurate planning, misallocated resources, and other critical challenges. This, in turn, influences how sales representatives and HCPs are educated about new therapeutics, how market access is established, and how that therapy is supplied and paid for.
Failure to understand the market leads to an inability to execute, but gaining that understanding in the first place can be a difficult and time-consuming process. Traditional market research can still unlock valuable insights, but by the time these insights are captured, they’re often weeks or even months out of date. Even when accurate market insights are available, pharma teams often choose not to act on them. In a recent Impatient Health webinar, 42% of respondents claimed that teams simply ignore market signals they didn’t expect to see.
Launch teams are currently forced to make assumptions regarding key strategic decisions, and so launch misfires often have nothing to do with the initial science. The challenge for the industry is whether or not pharma organizations can change this paradigm. To make that happen, we must answer the following questions:
- How can we transform market research from a process that takes months or years to one that takes just days?
- How can we provide teams with the ability and willingness to course correct as market forces dictate?
The Rise of the Specialty Drug Market
The narrower a market opportunity, the more in-depth market understanding is required. Given that 80% of FDA approvals are now considered to be specialty drugs, many launch teams find themselves entering rare disease markets for the first time. For a blockbuster drug such as GLP-1, there’s a large market opportunity, as millions and millions of people struggle with diabetes and obesity. It’s a very different scenario for specialty drugs, personalized medicine, and rare therapies – drugs that are more complicated in the formulary.
Launching into those markets requires a detailed understanding of existing market dynamics: who the patients are, how they’re diagnosed, where they get their treatments, how physicians are educated on existing treatment options, etc. In specialty drug markets, these factors become much more important much more quickly. The narrower margins make launch excellence absolutely critical. It’s all too easy to misunderstand or misread the market, leading you to deploy your therapy in such a way that you miss revenue opportunities or fail to deliver the patient benefits your company’s R&D has worked so hard to achieve.
How Pharma Teams Can Address Launch Failure Rates
Companies that start the process of market understanding sooner generally perform better. Companies that are early adopters of more sophisticated tools have more accurate processes. Their strategies and plans are more likely to be correct, and crucially, they can correct them as market forces change.
Currently, pharma teams might spend three years planning, only to launch a new therapy like it’s a rocket to the moon. They must hope their planning is correct, because by the time they’ve realized it’s not, they’ll have missed the narrow window in which to make any significant changes. The key is to become a real-time reactionary launch force – to position launch teams to react rapidly, rather than follow established ‘set and forget’ launch processes.
What a New Approach to Launch Looks Like
Currently, the different pharma divisions (clinical R&D, medical affairs, commercial, and market access) each have their own tool sets and views of the market. The result is a lot of duplicated effort as an asset progresses along the commercialization function, coupled with a general misunderstanding of the market. According to IDC research, data silos currently cost pharma organizations up to 30% of potential revenue, so it’s critically important to have consolidated tool sets that model the market and are suitable for each of these different departments. Consolidating teams can also help to address interdepartmental silos and eliminate some of that rework.
Best-in-class organizations are already beginning to do this. But there are many aspects of the pharmaceutical industry value chain where AI makes a fundamental difference in outcomes. Leaning heavily into AI and data in this part of the pharmaceutical commercialization process will result in better launch outcomes.
However, these outcomes cannot be achieved with open-source AI tools because they don’t have access to specific healthcare and pharmaceutical data. They’re incapable of integrating external data sources into a holistic data set, or delivering the kind of specificity that would allow an AI system to recognize that the Dr. Jones who sees a lot of patients within a particular disease community is the same Dr. L Jones who’s been working with your competitor.
Consumer LLMs like ChatGPT or Claude are effectively trained with everything that’s on the internet. That gives them a very broad focus, and a much higher potential error rate when addressing complex pharmaceutical queries – either because they don’t have the context, because they can’t understand the language, or because their responses are too high-level. There’s a whole host of reasons why these tools are never going to be much better than they are now at answering detailed healthcare questions.
A purpose-built pharma launch AI might use one of these open-source LLMs as raw horsepower, but must surround that engine with very precise technology, algorithms, and ontologies to provide pharma teams with the levels of accuracy, specificity, and certainty needed to address launch-related queries. So much capital is moving into AI development and adoption that people are quickly developing a baseline foundational experience. The next wave will sweep up those companies that aren’t talking about AI specifically, but are talking about solving problems related to their launch preparations. Whether they’re thinking about it or not, a purpose-built launch AI is the solution to those problems.
About Lance Hill
Lance joined Within3 as Chief Executive Officer in 2007. Under his leadership, the world’s top 20 pharmaceutical organizations and leading medical device companies have come to place their trust in the Within3 platform and value proposition.
“When key healthcare stakeholders – caregivers, patients, scientists, physicians, and policymakers – share ideas, everyone’s healthcare improves,” Lance says. “Within3 is committed to breaking down healthcare communication barriers and driving innovation throughout the industry.”
Prior to joining Within3, Lance served as Vice President and General Manager of webMethods’ worldwide Service Oriented Architecture software business. Previous roles include enterprise engineering and e-business architecture for IBM Global Services and National City Bank.
