Robust outsourcing strategies to help you meet submission timelines with smart resourcing, strong technology plans, and ultimately data readiness at every stage.
Introduction
In the past two decades, the growth of the biotech industry has been phenomenal with unique business models emerging. “Big pharma companies have been increasingly sourcing new IP from a variety of small biotech firms that specialize in drug discovery with innovative pipelines. Small biotech firms are responsible for nearly 70% of new drug approvals in the US and are much better at seeing results from it. A Deloitte report suggests that they can generate a return of 9.3% on R&D compared to 1.9% for multinational pharmaceutical firms; this shows an obvious comparative advantage over Big Pharma.”- World Bank article on cultivating economic growth in biotechs.
Small to mid-sized biotechs can range from being virtual where each step of the development process is managed externally, to a clinical-stage biotech in the early stages of clinical development. Typically, clinical-stage biotechs aim to collaborate with big pharma or are focused on commercializing independently, which can be a daunting journey.
Clinical strategy over data strategy
As emerging biotechs embark on their clinical development journey, they could be partnering with a variety of CROs ranging from niche early-phase providers to large global CROs. At this stage, the clinical development strategy tends to demand more attention, leading to the data strategy taking a back seat.
The lack of a data strategy and execution framework may save a dime today, to spend a dollar later. As submission timelines get closer, the study data could be spread across multiple CRO and technology partners, in diverse structures and formats, making submission management both expensive and time-consuming. Success in submissions is strongly driven by how robust the data strategy is.
Patterns observed
Early days: The decisions of insourcing versus outsourcing tend to heavily depend on the financial dynamics of the biotech and the development stage they are in. In early development, outsourcing is clearly preferred with a focus on budget efficiency and defined rate cards. At this stage, building capabilities in-house goes against the fundamental need to be a lean organization. A well-aligned CRO partner who ensures quality with efficiencies, tends to be the obvious choice.
Building in-house talent: As development progresses to Phase III, the questions around submission start to loom. How does one bring all the data together, and ensure it is standardized and consistent for insight generation? Since Phase III studies are almost always outsourced, biotechs tend to think about building capabilities in-house at this stage to ensure there is sufficient oversight.
Data standards: Another area typically overlooked is data standards. The absence of adequate data standardization can have a significant impact on how fast data can be leveraged for critical decision-making. Hence, investing in data standards early on and building a lean resource pool that oversees and maintains this across programs, can be game-changing.
As an early biotech, while it may be tempting to look at short-term success, it is critical to ensure that plans until submission are well laid out. Clinical data strategies should define the balance of insourcing and outsourcing throughout. While identifying vendor partners, the ability to support with expertise and scale as per need should be the primary premise of evaluation. No matter how many partners are involved in clinical development, two questions must always be addressed-
- How does the data come back together?
- Is the data enabling you to make critical decisions throughout the development cycle?
Conclusion
Ultimately, the decision on what, when, and how to outsource can be critical in driving successful clinical programs. Based on the underlying strengths of internal teams, it is important to involve experienced data strategists right from the start to ensure submission readiness. A robust data strategy will also help you meet submission timelines ahead with smart resourcing strategies, strong technology plans, and ultimately data readiness at every stage. This will significantly expedite clinical and regulatory outcomes, ultimately reducing time to market.
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