Five Practical Strategies for Accelerating Early Phase Studies

Emerging biotechs today can make decisions much faster than ever before in the early phase given the availability of data, with study designs that can be adapted in real time. Biotechs can not only move faster but reach strategic milestones with the data needed to make better go/no-go decisions while preserving capital and reducing unnecessary risk. In parallel, regulators are increasingly encouraging initiatives focused on early phase trials to drive innovation and reduce the regulatory burden, including the FDA’s recent real-time clinical trial initiative.¹

But practically speaking, how can companies accelerate proof of concept by designing studies around the decisions they actually need to make? How can they generate information early enough to make decisions confidently while a study is still underway, not only after traditional end-of-study processes are complete? We asked our expert panel of Clinical Trialblazers: Jack O’Meara, Co-Founder and CEO of the biotech Aerska; Chris Potts, Chief Business Officer of the investment firm Persephoni; and Francois Burger, head of early phase business at Parexel.

Design the right program 

O’Meara, whose company is developing RNA medicines for genetically driven neurological disease, noted the importance of thinking from the outset about exactly what you’re trying to accomplish. To illustrate, Aerska has developed a platform for targeted brain delivery enabling systemic versus intrathecal administration of medicines, which could feasibly meet a huge unmet need. The company narrowed its focus to subpopulations that are underserved by existing options such as monoclonal antibodies, then took steps to consider the complexities and nuances within this subpopulation. Listening to the patient community, patient advocacy groups and key opinion leaders has shaped the strategy and will inform how the trials are designed.  In short, Aerska devised an innovative approach to get the right data as quickly as possible, doing a lot of the work up front rather than rushing in without the right focus. 

Get the right data sooner

Equally important is to identify all the different audiences who will be reviewing and making decisions informed by that data, and how they will view the problem to be solved in the data being generated. For an early-stage biotech, the tendency is to think about data through the lens of regulatory approval. However, Potts noted that biotechs should keep the business development angle in sight from the outset. That viewpoint encompasses strategic partners that might buy the company or otherwise support commercializing the product, as well as the investor community. Layering in the perspective of these stakeholders and considering the information that will convince them to join as partners can change the calculus. For instance, a traditional trial might be the most logical choice from the regulatory standpoint, while an innovative trial design might be more effective for the data sets to be collected for these other key audiences.

He added, “How will an investment firm view your technology, your company, and your portfolio as they make go/no-go decisions about where their money should go?” 

Investors will think practically about the trial design, considering what the primary and secondary endpoints should be. They look at efficacy as early as possible, as well as safety, of course. For example, how will animal models be structured to elicit evidence of efficacy and safety via primary and secondary endpoints, even with a limited number of patients?

Engage early with regulators and experts

Front-loading the process should also encompass multiple perspectives. Burger advised, “Align the right regulatory, clinical, nonclinical, biomarker, clinical pharmacology, and operational experts early to ensure that the study is designed to answer regulatory, delivery, and development questions.” The objective is to build protocol flexibility that allows changes as data emerges without requiring major amendments. Using the right modelling and simulation tools can help determine those selection or escalation strategies, looking at the right endpoints and the right biomarkers to demonstrate target engagement and proof of mechanism.

He added that today, there are more opportunities to engage early with regulatory agencies to get scientific advice, which can help significantly in de-risking development plans. Expanding on that point, he noted that regulatory input is necessary all along the development lifecycle; as data emerges that requires adaptations, regulatory pathways are likely to shift. The key is to understand how ambitious scientific objectives can be executed successfully. For small biotechs that might lack in-house expertise in regulatory affairs, translational medicine, or clinical pharmacology, for example, “Partner with someone who does.”

Use tools that genuinely improve decisions

As for technology, and specifically artificial intelligence, Potts remarked that biotechs should be the leaders in a conservative industry. “All biotech founders should be AI native and leverage every tool they can find.” Using AI to accelerate proof of concept is crucial from the standpoint of investors, who want to maximize capital. Biotechs are competing for early-stage investment with software firms, for example, that can reach proof of concept in weeks or even days. 

Burger agreed, noting that modeling and simulation tools have made a major impact on how early phase studies are conducted. It helps predict not just the human PK, but also starting doses and escalation as well as exposure response relationships. But the real value of AI lies in how we analyze and interpret the data.

“AI can help us identify patterns in large, complex data sets and help detect trends earlier in the process,” he said. 

O'Meara added that Aerska adopted AI early and broadly. He believes that modeling and simulation will remain the foundation, while AI can add immediate value in extracting insights from those increasingly complex data sets and supporting real-time decision making. “We have integrated AI in everything, from molecule design and target selection through to clinical planning and  day-to-day work,” he said. He estimated a productivity gain of 20% across the organization, which, with access to more inputs and data, will ultimately help them deliver more and better medicines to the clinic faster.

Execute without unnecessary friction

Burger observed that slow decision making is typically responsible for more delays than slow data generation. He advised implementing a rigorous cross-functional decision-governance process, defining the key questions and decision criteria up front and aligning the entire team around those criteria. Establishing a clear framework for how the data will be reviewed and how decisions will be made can accelerate the entire development process. A strong governance process allows the team to interpret the emerging data as it becomes available, make decisions more confidently, and maintain the development momentum.

From the standpoint of a biotech on the front lines, O’Meara explained that his team at Aerska is planning for the recruitment challenge ahead of first patient dosed.  They are building a patient advocacy board and spreading the word within the patient community. Critically, they are earning trust now by describing the mechanism in a way that’s easy to understand and accessible to the people they are trying to serve. The insights gained are already shaping how the company will reduce barriers to engagement, drive recruitment, and streamline operations.

Seeking advice and input from funding sources is also a good idea. Potts used an example of a biotech considering an investigator-initiated trial in China. He recommended talking to investors, who can serve as a valuable resource in conducting due diligence.

More from our experts

For practical advice on how to accelerate proof of concept and improve efficiency throughout the development process, watch our experts in conversation in our one-hour panel discussion. For more insights and perspectives from Clinical Trailblazers, explore our hub.

How does your biotech approach trial design, technology, and operational excellence? The Parexel Biotech team can help you navigate these essential topics and clarify your development priorities. 

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Resources

1. https://www.fda.gov/news-events/press-announcements/fda-announces-major-steps-implement-real-time-clinical-trials

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