Clinical trials have always been burdensome on sponsors, but in the current biotech landscape, the pressure to execute trials promptly, efficiently, and in a cost-effective manner may be more intense than ever. Even companies with comfortable budgets report feeling resource-constrained, and for early-stage companies, executing a trial with limited funding has become a make-or-break challenge. Investor caution, shrinking pipelines, and rising operational costs have forced teams to do more with less, without compromising speed, scientific rigor, or patient safety.
Across the industry, teams are rethinking how they approach trial design, recruitment, and execution in this constrained environment. In this blog, we pull from our learnings and experiences with customers, along with industry data, to offer practical strategies for delivering clinical trials in a capital-constrained environment.
The cost of underestimating
Phase II trials generally cost $7–20 million, while Phase III trials cost $20–100+ million. Even in earlier phases, costs can balloon due to poor feasibility assumptions, screen failure, and extended timelines.
One of the most persistent challenges in trial planning is optimism bias, which involves systematically underestimating how long recruitment will take and how many patients can be enrolled. As Muench’s Third Law puts it: researchers should assume they will accrue approximately one-tenth as many participants as they initially intend to recruit. Many teams don’t discover feasibility problems until after trial infrastructure is already in place. But by that point, a misstep in recruitment can extend timelines by quarters or even years. Every day of delay can cost sponsors an estimated $40,000 in lost value or additional overhead.
Patient-finding deserves earlier investment
Approximately 80% of trials fail to reach their target number of participants on time. Accordingly, a recurring theme in successful trial execution is early, proactive patient-finding. While this often seems like a downstream operational task, it’s one of the most valuable forms of de-risking – especially for genomics and rare disease trials.
Some of the most effective programs start patient engagement and genetic pre-screening months in advance, gathering both quantitative and qualitative insight. For instance, in our work with a trial sponsor recruiting patients with alpha-1 antitrypsin deficiency (AATD) who carried a specific rare genetic variant for a precision trial, early engagement and pre-screening allowed Sano to successfully deliver 90% of the referral target (58 participants) within the first 4 weeks of the agreed 4-month recruitment period. This helps prevent delays to trial initiation while also revealing feasibility issues before they become roadblocks.
Even lightweight programs that may depend on digital recruitment, outreach through registries, and recontacting patients with relevant test results can expose feasibility constraints early, giving teams the option to adjust rather than scramble.
Smarter trial designs stretch budgets further
When budgets are tight, trial design matters. Flexible and adaptive protocols, such as platform or basket trials, enable sponsors to test multiple hypotheses within a single structure. This not only saves costs, but also enhances efficiency and accelerates the process.
Real-world data can also help trial teams optimize their designs. Pfizer, for example, avoided a $600 million clinical trial by leveraging real-world evidence instead, underscoring both the scale and financial efficiency this approach can offer. AI-driven models and synthetic control arms have been used to reduce patient enrollment targets while maintaining statistical power. These methods can be especially useful where recruiting control patients is ethically or practically challenging. Even in standard trials, adjusting inclusion criteria based on real-world datasets can reduce screen failures and improve accrual without compromising safety or scientific rigor.
Collaboration can cut operational costs
One of the underappreciated ways to reduce trial spend is through thoughtful collaboration. Industry-academic partnerships, shared infrastructure models, and pre-competitive data sharing initiatives are increasingly being used to pool resources and streamline execution.
Especially in rare disease trials, sharing recruitment pipelines and protocols through consortia or research networks can reduce duplication and improve trial speed.
Avoiding the hidden costs of over-outsourcing
Outsourcing can accelerate timelines, but it can also introduce communication delays, misaligned incentives, and spiraling costs when not managed carefully. This is especially true in early-stage or rare disease trials where site relationships and protocol nuances are critical.
Teams that maintain close relationships with investigators and stay deeply involved in trial execution tend to avoid the pitfalls of over-reliance on CROs. When sponsors rely heavily on outsourcing without the experience of managing those relationships effectively, they often end up overpaying for execution that may fall short.
Build infrastructure that fits your trial
Beyond recruitment and design, much of trial cost comes from operational fragmentation resulting from disconnected vendors, manual logistics, and disjointed data systems. Many trials are slowed not by science, but by scheduling errors, bottlenecks in lab processing, or delays in patient communication.
Especially in precision medicine trials, infrastructure matters. Integrating consent, testing, monitoring, and data flows allows teams to maintain speed and control costs.
Plan for the end from the start
Resource-constrained companies are increasingly realizing the need to prioritize smarter and earlier. Before moving a candidate toward the clinic, sponsors should be asking not just whether the science holds up, but whether the market, population, and regulatory expectations do too.
When done correctly, this kind of strategic planning saves millions. It avoids launching trials that are unlikely to recruit, gain approval, or secure reimbursement. It also helps sponsors make more informed trade-offs across programs.
Grounding trial plans in patient realities
Even when the science and strategy are strong, many trials do not go to plan because they underestimate the lived experience of patients. Sponsors often move forward with assumptions about willingness to participate, disease burden, or how meaningful a treatment might be without validating those assumptions with real-world data or direct community input. For example, a therapy that shows promise in the lab may not be seen as worth the risk or effort by patients unless it meaningfully improves quality of life in ways they care about.
Incorporating surveys, interviews, and patient advisory boards early in the design process can expose practical and emotional barriers to participation. Understanding what trial participation actually looks like for patients can also help shape more inclusive and feasible protocols. When companies build around real patient experience, they not only de-risk execution but also improve the chances of generating data that’s relevant and persuasive in the real world.
Running lean trials doesn’t mean cutting corners. With early planning, smarter prioritization, and targeted patient engagement, it’s possible to achieve the same quality of outcomes for a fraction of the cost. In today’s environment, the most resilient teams are proving that clinical excellence doesn’t require unlimited resources – just thoughtful strategy and the right operational foundation.
