Smarter bets, stronger clinical trials
Clinical trials are among biopharma’s most significant investments, yet many still advance on internal optimism rather than external validation. In contrast, private equity (PE) firms apply structured due diligence to every major decision by testing assumptions, quantifying risk, and grounding choices in data. This Viewpoint explores how adopting a similar discipline in clinical trial design and governance can strengthen decision-making, accelerate timelines, and improve return on R&D investment.
Clinical trials aren’t solely scientific projects; they are also investment decisions. Trials, especially Phase II and Phase III, are among the most capital-intensive bets a biopharma company can make. Success demands a blend of rigorous scientific insight and something less commonly emphasized in the industry — true investment discipline.
“Why don’t more pharmaceutical and biotechnology companies treat clinical trials as the high-stakes investment they are?” is a question long overdue. PE firms rarely commit capital without engaging external due diligence: commercial market validation, customer insights, competitive intelligence, and execution risk modeling. They do so because they know that internal firm conviction is not always the same as objective, data-driven reality.
In contrast, many late-phase trials in biopharma advance based on internal consensus, optimism around the molecule, and assumptions that go unchallenged until they fail in the real world. The pattern is evident: the protocol proves too ambitious, sites start up late, enrollment underperforms, and timelines slip. It’s time to make clinical trial due diligence a mandatory standard as a discipline of better decision-making.
Biopharma R&D is entering an era characterized as capital-constrained, competitive, and outcomes-driven. Boards and investors are demanding tighter ROI discipline, payers are demanding greater proof of value, and the opportunity cost of a stalled or delayed trial has never been higher.
The cost of a stalled or delayed clinical trial can also manifest in the future, once the asset reaches the market.
For example, Arthur D. Little analysis of first-in-class oncology assets demonstrates that first movers can capture as much as 60% market share within the first two years from launch; when you arrive second, the value capture falls steeply. For curative therapies, the result is even more dramatic. First-to-market entrants often capture the entire market, since assets are effectively one-and-done therapies. In either scenario, there is a significant value that arises from effective timing in the clinical trial phase.
Every Phase II or III trial is a portfolio-defining bet. Yet the rigor applied to approving these investments often trails what’s standard in PE, infrastructure, or even venture capital. The outside-in view is a strategic practice from these industries that can be borrowed and applied to clinical trials, improving clarity, speed, and ROI.
When PE firms consider a deal, they rarely move forward based on internal views alone. Rather, they apply a plethora of analyses to strengthen their confidence, including outside-in market assessments, assumption pressure-testing exercises, competitive mapping and regulatory scans, and structured capturing of decision-ready outputs. These analyses allow for a detailed, data-driven decision, limiting the firm’s overall risk.
Further, these engagements aren’t long-term projects. Instead, they are four- to six-week intensive endeavors that are fast, focused, and hypothesis-driven. The goal is to quickly and effectively reduce uncertainty and build conviction rather than predicting the future. In short, they don’t fall in love with the asset; they proactively interrogate it from every angle.
The same level of rigor can be applied to clinical trial investment decisions. What if every late-phase trial had to pass through a structured, external review process that gave R&D, finance, and portfolio committees a clearer view of execution risk and ROI?
Let’s examine an independent, outside-in case study based on real clinical trial data. Two separate trials, one pivotal neurology and one global oncology, illustrate the strength of externally pressure-tested patient recruitment forecasts (see Figure 1).
In both cases, the externally pressure-tested data-driven model was compared against the clinical study teams’ forecasts. One forecast leaned optimistic, the other conservative; yet in each instance, actual recruitment tracked closely to the external view on a retrospective review. The underlying message: when core assumptions are validated and externally stress-tested, forecast accuracy improves substantially.
This example not only highlights the value of better accuracy, but also the need for an adjacent “assumptions playbook” that captures all core drivers to win across patient, site, protocol, and operations. By aligning on “what must be true” to achieve enrollment targets, teams can monitor early signals and escalate proactively when real-world performance diverges.
Next, consider how a diligence-based, outside-in approach differs from traditional business-as-usual practices (see Figure 2). It highlights key shifts in mindset, data usage, and decision-making rigor that can materially improve trial outcomes and investment confidence.
When done right, a clinical trial due diligence process doesn’t result in a 100-page slide deck. Instead, it results in three to five risk scenarios with clear recommendations; an execution playbook linked to cost and time impact; a visual expected net present value (eNPV) bridge showing how trade-offs affect ROI; a country/site matrix showing where risk is concentrated; and a one-page go/no-go recommendation with logic and limitations. These outputs are not designed for the archives. They’re living documents, designed to be used in the moment, just as PE investment committees use their commercial due diligence reports.
To be clear: outside-in views won’t always be right, and that’s not the point. What they do is reduce blind spots, challenge groupthink, and bring real-world data into conversations often dominated by internal passion and legacy assumptions. That alone is worth the time and investment, especially when the alternative is spending $200 million or more on a trial that stalls or underdelivers.
In PE, consultants and advisers aren’t held accountable for outcomes; the investors are. But the quality of external input directly impacts the quality of the decision. That’s why the best PE firms take this process seriously — not because they have to, but because it works.
When trial design fails the diligence test
A late-stage oncology study (in the past 10years) testing a targeted therapy in newly diagnosed or unfit patients appeared poised for rapid label expansion. Instead, it was halted early for futility and later failed regulatory review. Three diligence gaps drove the outcome:
This case shows how choices in population, comparator, and geography can be as decisive as the science itself — and how early design diligence can prevent costly missteps.
This is not a pitch for external management consulting services. It’s a call for standardization and discipline. Many companies already have access to data, modeling tools, and experience. But they don’t always put it together in a structured, outside-in way — and they rarely make it mandatory ahead of big investment decisions. Imagine if your next Phase III greenlight required a four-week external challenge process. Imagine if assumptions had to be validated, not just debated. Imagine how much stronger your governance, and your confidence, would be.
It’s time we treated clinical trials not only as scientific milestones but as strategic capital deployments. We need to ask:
In a world where capital is scarcer, timelines are tighter, and competition is fiercer, conviction alone won’t cut it. Clinical trials are high-stakes investments — and it’s time we treated them that way. Let’s raise the bar and institutionalize clinical trial due diligence, borrowing the best from PE, venture, and ourselves. By embedding outside-in, data-driven reviews of feasibility, site strategy, enrollment, and ROI, we can de-risk decisions, sharpen assumptions, and increase the odds of success — turning every late-phase trial into the strategic bet it truly is.
By Ben Enejo, Jack Kuczmanski, Salvatore Lupo
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