Behavioral health is emerging as one of the clearest proving grounds for applied artificial intelligence (AI) in healthcare. The need is obvious: Demand continues to rise; provider shortages remain persistent; and patients, clinicians, payors and employers all want more accessible, responsive and measurable care. At the same time, behavioral health is unusually sensitive to issues of trust, safety, privacy and human judgment. That combination makes the field both highly promising and uniquely demanding.

The practical implication is that the market is unlikely to move overnight from traditional care to fully autonomous AI-delivered therapy. The more credible path is a staged one. Today, AI is already creating value in provider matching, patient intake, documentation, risk flagging and between-session engagement. Over the next several years, the center of gravity is likely to shift toward hybrid models in which AI extends clinician reach, supports earlier intervention and improves continuity of care while licensed professionals remain central to diagnosis, escalation and management of higher-acuity needs.

The organizations most likely to shape the next phase of the market will not simply have the most advanced model. They will combine clinical grounding, thoughtful safety design, strong workflow integration, access to relevant real-world data, and the operational ability to fit AI into reimbursement, provider and care-delivery systems. In behavioral health, technical capability matters, but trust is what will determine scale (see Figure 1).

AI is also beginning to reshape not just the care model of behavioral health but the business model. One reason is that behavioral health benefits are often distributed through overlapping sponsored channels rather than a single, exclusive payor relationship. In practice, the same individual may have access to behavioral health support through multiple benefit providers at once — for example, through an employer, an auto insurer or a life insurer — meaning the same underlying “life” can be monetized multiple times across the ecosystem.

Why behavioral health is such a strong use case for AI

Behavioral health sits at the intersection of high unmet need and strong digital suitability. Much of mental healthcare is delivered in outpatient settings, many interactions are conversational and longitudinal, and patients often value the privacy and convenience of virtual access. Those characteristics make the category more naturally compatible with technology-enabled care than most clinical domains.

The access problem is equally important. Demand for therapy, psychiatry and lower-acuity emotional support continues to outpace the available workforce. Wait times remain long in many markets, clinician availability is constrained and geography still shapes access in ways that are not clinically rational. AI will not solve the workforce shortage by itself, but it can help expand effective capacity. That is especially true when it reduces documentation burden, improves triage, keeps patients engaged between visits and supports lower-acuity needs that do not always require a full clinician encounter.

Economic pressure reinforces the same conclusion. Payors want earlier intervention and lower downstream medical spend. Employers want benefits that improve access, reduce disruption and produce usable outcome indicators. Clinicians want tools that reduce administrative friction without compromising therapeutic judgment. Patients want care that is easier to start, easier to continue and easier to fit into daily life. In a category where all stakeholders are asking for some version of greater access and efficiency, AI has clear structural relevance across the system (see Figure 2).

Where AI is creating value today

Despite the excitement around generative AI, the current state of adoption in behavioral health is still more operational than clinical. The most established use cases sit behind the scenes rather than at the center of clinical care. AI is being used to support intake and triage, improve provider matching, generate notes and session summaries, flag signs of risk or dropout, optimize scheduling, and personalize reminders or self-guided prompts. In other words, the first wave of value creation has focused on making the existing care model work better. Increasingly, these tools are also commercial infrastructure; by improving digital triage, self-service engagement and referral conversion, they help vendors capture value at more than one point in the member journey rather than relying on a single reimbursed encounter.

That first wave will be more foundational than it may seem. Better matching can reduce friction at the point of entry. Better documentation can give time back to clinicians. Better monitoring can identify risk earlier and make follow-up more targeted. Better data capture can improve outcomes visibility for organizations that need to understand whether a mental health intervention is actually changing behavior, adherence or utilization. None of these use cases depend on replacing the therapist or psychiatrist. They improve performance by tightening the system around the clinician and the patient.

The market is beginning to move beyond those enabling functions, but cautiously. During 2025 and early 2026, several public examples helped move the conversation from abstract promise toward more concrete evidence and governance. Spring Health released VERA-MH, an open-source evaluation framework for mental health chatbots. Lyra began piloting a clinically designed AI guide with risk-flagging and escalation pathways. Dartmouth College researchers published early clinical-trial results for Therabot. OpenAI convened an Expert Council on Well-Being and AI alongside related clinical advisory work. Those developments matter because they suggest the field is shifting from experimentation toward evaluation, governance and evidence generation. Still, the core message remains the same: Current momentum is real, but broad acceptance for AI-led mental healthcare has not yet arrived.

Why hybrid models are likely to win first

The next chapter is likely to be defined by augmentation rather than immediate autonomy. Hybrid models are more acceptable because they preserve a role for human judgment where the stakes are highest while still unlocking some of AI’s strongest advantages: always-on availability, lower marginal cost, more frequent touchpoints and the ability to synthesize large amounts of behavioral data over time.

In practical terms, that means AI is more likely to succeed first as a copilot rather than as a substitute. It can reinforce skills between sessions, prompt journaling or check-ins, help identify relapse risk, summarize patterns for clinicians, support waitlist management and provide lower-acuity guidance in bounded contexts. Meanwhile, clinicians remain responsible for assessment, diagnosis, high-risk situations, medication decisions and changes in treatment strategy. This model aligns better with current trust dynamics and current reimbursement realities, which still tend to favor clinician-led care even when technology is deeply embedded in the experience.

Selective autonomy may still emerge, particularly for low-acuity support, maintenance use cases or early engagement before a patient enters formal treatment. In those settings, the appeal is obvious: AI can be available at any hour, engage patients who might otherwise defer care, and create a bridge between symptom recognition and more structured support. But autonomous use cases will scale only where safety expectations are explicit, escalation pathways are reliable, and the model operates inside clearly defined clinical and ethical boundaries (see Figure 3).

This distinction matters strategically. The debate should not be framed as “AI therapist versus human therapist.” The more useful questions are: Where can AI safely add value across the behavioral health journey? What level of autonomy can each use case support? What evidence is required before stakeholders will trust it?

What safe scale will require

If the market moves from workflow automation toward more clinically active AI, the gating question will be about safety at scale. In behavioral health, it is not enough for a model to sound empathetic or to generate plausible therapeutic language. It must perform reliably in moments of ambiguity, emotional volatility and potential crisis. That requires a stronger operating model than many general-purpose AI deployments have needed. Unlike many AI applications, failure in behavioral health carries asymmetric risk. Errors are far from just inconvenient; they are potentially harmful, thereby raising the bar for deployment.

A practical way to think about this involves the six conditions for success.

1. Trust: Users, clinicians and institutional buyers need confidence that the system is clinically grounded, transparent and used in ways that are easy to understand.
2. Data strength: The model must be informed by relevant, high-quality behavioral health data and evaluated against real-world outcomes, not just general language benchmarks.
3. Accessibility: The solution must be available in the places where people actually seek support, including payor-backed and employer-sponsored channels, and within a cost structure that makes it broadly accessible.
4. Personalization: Useful mental health support is inherently contextual, so the experience must adapt to the individual rather than delivering generic advice.
5. Safety: Crisis recognition, escalation, boundary management, bias monitoring and auditability are not optional design features. They are core infrastructure.
6. Ecosystem integration: AI must fit within provider workflows, documentation expectations, care pathways and reporting requirements rather than sitting outside the system as a disconnected tool.

Taken together, these conditions suggest that success in behavioral health AI will not come from model sophistication alone. It will come from combining product capability with clinical operations, governance and distribution. This is one reason many early market signals have focused so heavily on safety councils, evaluation frameworks, guardrails and human oversight instead of on raw model performance (see Figure 4).

How the patient journey will change

The most useful way to understand AI’s future role is not by model type but by patient journey. The deeper shift is from episodic care to continuous support. Traditional therapy is structured around discrete sessions. AI introduces a persistent layer of monitoring, engagement and intervention between those moments. At the front end, AI can help people articulate what they are feeling, complete screening and navigate toward the right level of care. AI may also reshape how patients enter care, serving as a low-friction, always-available first touchpoint for individuals who might otherwise delay or avoid seeking help. During entry and triage, AI can collect history, structure symptoms and improve routing. During treatment, it can reinforce skills, prompt reflection, surface changes in mood or engagement, and support continuity between scheduled encounters. After more acute treatment, it can play a role in relapse prevention, maintenance and re-entry into care when signs of deterioration reappear.

These are meaningful changes because behavioral health has always struggled with fragmentation between moments of active care. Traditional models often have limited visibility into what happens between appointments, limited ability to intervene early when symptoms worsen and limited capacity to maintain lower-intensity support over time. AI can help create a more continuous support layer around the formal care relationship. That continuity may prove to be one of the most valuable aspects of the technology, particularly for patients whose needs fluctuate and for clinicians managing larger caseloads.

Importantly, not every stage of the journey carries the same clinical risk, which is why adoption will almost certainly be uneven. Lower-acuity screening, behavioral coaching, journaling prompts and relapse monitoring are more likely to move first. High-risk assessment, crisis response, diagnosis and medication management will continue to require a much higher threshold of oversight and evidence. The market is unlikely to converge on one universal model of AI-enabled behavioral healthcare. It is more likely to segment by acuity, use case and care setting (see Figure 5).

How AI is changing the business model, not just the care model

One of the more important developments in behavioral health is that AI is not only expanding what can be delivered digitally; it is also broadening how vendors get paid. Historically, many behavioral health solutions relied on a relatively simple model: direct-to-consumer subscriptions, employer-paid access fees or reimbursed clinical encounters. That model is becoming more layered. As AI tools are embedded earlier in the patient journey and across more channels, revenue increasingly can be captured at multiple points — at the population level through employer or health plan contracts, at the engagement layer through digital navigation and self-guided support, and at the clinical tier when a member steps up into coaching, therapy, psychiatry or other covered services. These models are not always mutually exclusive at the life level; in practice, the same individual may sit inside multiple sponsored benefit channels at once, so the same covered life may be monetized more than once across the ecosystem.

This is creating a model that looks increasingly familiar to anyone who has followed employee assistance program (EAP) evolution: A broad population may be covered through an embedded or access-based contract, but only a subset engages deeply enough to generate additional utilization, referral or care-management revenue. AI can make that structure more powerful by serving as the always-on front door — identifying need earlier, improving engagement, routing people to the right level of care and keeping members active between visits. In that sense, AI is not only a clinical tool; it is also a conversion, retention and care-navigation layer. The same covered life may therefore be monetized sequentially across multiple offerings, especially when the vendor sits inside the carrier, employer or provider workflow. Rather than a standardized industry rule, this is an inference from how many current offerings are being structured.

The market is already moving in this direction. Spring Health pairs an employer-facing EAP+ model with broader platform services and has also expanded its behavioral health platform to more health plans. Lyra markets a single platform across employers and health plans, combining guided self-care, provider matching, coaching, therapy, medication support and AI-enabled tools. Headspace continues to position itself with health plans through a mix of content, digital support and provider-backed care. Wysa, meanwhile, spans employers, insurers, health systems and primary-care-linked pathways, using AI self-help and navigation to engage users and then route them onward to other services when appropriate. The implication is that the winning business models may be those that combine low-cost, population-level reach with the ability to capture higher-value clinical experiences, navigation assistance and workflow revenue as needs intensify.

For buyers, that makes vendor evaluation more complex. It is no longer enough to ask whether an AI tool “works.” The better question is whether the vendor’s commercial model aligns incentives across access, engagement, escalation and outcomes. Solutions that monetize only at the point of high-acuity clinical use may struggle to justify broad deployment. By contrast, models that combine access fees, embedded distribution, and step-up care revenue may have stronger economics and more room to invest in safety, evidence generation and workflow integration over time.

What could slow adoption

The barriers to adoption are real and should be treated as structural rather than temporary. Clinical risk is the most obvious one. Behavioral healthcare includes situations involving suicidality, other self-harm, trauma, psychosis and rapid decompensation. A system that performs well most of the time but fails badly in edge cases is not ready for broad deployment. Safety, therefore, is not just a product issue; it is a market access issue.

The evidence base is another limiter. Early signals are promising, and formal research activity is increasing, but many stakeholders will still want more proof before they treat AI-enabled behavioral support as clinically interchangeable with human care. Dartmouth’s early Therabot trial is an important indication that more rigorous evidence is starting to emerge, but one encouraging study certainly does not indicate a broad clinical consensus. Payors, in particular, are likely to remain cautious until evidence, practice guidance and payment pathways mature further. Employers may move somewhat faster in lower-risk use cases, especially as more guided-support pilots come to market, but they too will need confidence that innovation is not outrunning governance.

Provider acceptance will also shape the curve. Clinicians are broadly receptive to tools that reduce burden and improve continuity, but many remain skeptical of tools that threaten therapeutic quality, professional responsibility or the therapeutic alliance itself. Their skepticism is not an obstacle to be brushed aside. It is a useful design constraint. The strongest products will be the ones that make clinicians more effective, not the ones that assume trust can be bypassed.

Finally, the policy environment is beginning to move from abstract concern to real governance. As formal frameworks, state-level reviews and best-practice guidance develop, the field will become easier to evaluate but harder to bluff. Utah’s 2026 regulatory experience is one example of how quickly the discussion can shift from general AI enthusiasm to concrete inquiries around disclosures, escalation and consumer protection in mental health settings. That is a healthy shift. In a domain this sensitive, discipline is likely to be a precondition for adoption rather than a brake on it. Beyond clinical risk and evidence, reimbursement remains a gating mechanism. Until AI-enabled interventions are recognized within formal payment models, adoption will remain constrained regardless of technical progress.

What to watch over the next three to five years

The most likely near-term outcome is that augmentation will become the norm before autonomy becomes mainstream. AI will become more common in intake, engagement, measurement, documentation and lower-intensity support. At the same time, a smaller set of bounded autonomous use cases will continue to be tested, especially in lower-acuity settings or in direct-to-consumer channels where the need for always-available support is especially visible.

Several signals will determine whether the market moves faster. One is evidence: More clinical trials, stronger real-world outcomes, and clearer differentiation between low-risk wellness tools and clinical-grade interventions are required. Another is regulation: This means practical standards for disclosure, escalation, documentation and accountability — not necessarily heavy-handed regulation. A third is reimbursement: Once payment models better recognize AI-supported or AI-mediated care, adoption could accelerate meaningfully. A fourth is institutional trust: As more buyers see rigorous guardrails, transparent evaluation and credible oversight, it will become easier to move from pilot to scaled deployment.

For the broader market, the implication is clear: AI will matter in behavioral health, but the issue is not simply whether it works. The real questions ask where it can be trusted, how it will be governed and which organizations can combine product capability with clinical credibility. The market is now moving out of the broad curiosity phase and into the phase of selective proof. That is exactly where serious categories begin to take shape.

A related implication is that the most attractive behavioral health models may be those with multiple monetization layers around the same covered population. In practical terms, that can mean pairing carrier-embedded or employer-paid access revenue with AI-enabled navigation, step-up referral, claims-based clinical care, and in some cases provider-facing workflow tools or analytics. As in EAP, breadth of covered access matters — but the real strategic advantage may come from owning the member journey across multiple points of engagement and escalation.

Conclusion

Behavioral health is one of the clearest real-world tests for AI: Can it improve care in a way that is both scalable and responsible? The need is urgent, the economics are supportive and the digital fit is stronger than in many other areas of healthcare. But it is also a category in which harm, if it occurs, will be highly visible and deeply consequential.

That is why the future is unlikely to belong to the boldest claims. More likely it will belong to the most disciplined models — those that improve access without overreaching, extend clinician capacity without eroding judgment, and create more continuous support without losing sight of safety, evidence and trust. Over the next several years, the center of the market will likely move toward AI-enabled hybrid care. The organizations that succeed will be the ones that treat trust not as a communications issue but as part of the product itself. Over time, the sector’s leaders may be distinguished not only by clinical outcomes and safety, but also by their ability to build resilient, multilayered business models around access, engagement, escalation and longitudinal member value.

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L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC

Price-led growth has run its course

Price increases are no longer driving restaurant growth, and in many cases, they are now suppressing it. In 2026, comparable-sales (comps) performance has shifted back to traffic and frequency, forcing operators to rebuild the guest value equation from the ground up.

The National Restaurant Association expects only 1.3% real sales growth in 2026. Black Box data shows traffic remained negative in both December 2025 and January 2026. The industry continues to grow nominally, but the easy levers are largely gone.

In this environment, pricing is no longer a dependable engine of top-line growth. In some cases, it may now be weighing on traffic and, by extension, comps. Yet the market is not moving in lockstep. A growing set of restaurant brands is outperforming despite the same macro conditions. That widening spread suggests the next phase of comps growth will be driven less by market tailwinds and more by how effectively each brand rebuilds its value equation, especially when serving middle- and lower-income consumers (see Figure 1).

The shift: From pricing power to value clarity

This is not a market that can be powered solely by affluent diners. The value equation has to work for households with total income below $75,000. Circana found that 54% of those households would visit restaurants more often for better prices, but value is rarely defined by price alone.

What is emerging instead is a more disciplined form of consumer behavior. Guests are still willing to spend but only when the food, experience and convenience clearly justify the bill. In that sense, value is less an abstract concept than a simple judgment: Was this worth it?

That judgment is shaped by a combination of factors: confidence in portion size and quality, the ease and speed of the experience, and how clearly the offering stands up against alternatives. What looks like a “flight to quality” is often a flight away from “just good enough.” Consumers will trade up when the value is evident and trade down quickly when it is not.

Differential performance suggests strategy is overtaking sector tailwinds

The spread in reported results is striking. Chili’s, McDonald’s, Taco Bell, Starbucks, Texas Roadhouse and CAVA are all posting strong comps growth, while others have seen traffic-driven declines (see Figure 2).

These brands operate in different segments and serve different customer bases, yet they are exposed to the same macro backdrop. The lesson is not that one segment is structurally advantaged. It is that brands with a clearer and more credible consumer proposition are separating from the field.

At a high level, the distinction is becoming easier to observe. The strongest performers are making value legible through price architecture, product quality, experience and execution, while weaker performers are relying on positioning or pricing that customers no longer find sufficient on its own.

The new restaurant value equation

Based on current performance patterns, six moves are emerging among outperforming brands. Together, they form a more complete definition of value — one that is experienced, not simply priced.

1. Start earning preference, don't just offer low price

Value has to be immediately legible to the guest. The objective is not to be the cheapest option on the block; it is to feel like the smartest purchase. Chili’s resurgence has been built not on indiscriminate discounting but on a combination of competitive pricing, sharper communication, menu clarity and improved operations. Taco Bell’s value architecture similarly establishes a clear entry point while preserving brand distinctiveness. These brands are not just winning one quarter but quarter after quarter, earning customer preference.

2. Deliver value they can see, taste and trust

What looks like a flight to quality is less about premiumization for its own sake than about reducing valueless complexity. Our work suggests that consumers who said dining out was not worth the money most often pointed to food quality and portion size. Brands must conduct disciplined menu simplification. The best operators don’t approach this as cost-cutting but rather as a disciplined review of their value creation equation across three lenses: the customer, operations and economics.

Chili’s continues to benefit from a highly satisfying dine-in experience enabled by its menu simplification and accessible pricing. CAVA is capturing share with bold flavors, customization and a health-forward proposition that still feels attainable. Shake Shack continues to position around high-quality food, warm hospitality and value. By contrast, premium price positioning without equally visible product or experience advantages is becoming harder to sustain.

As Abigail Pringle, Former President, U.S., The Wendy’s Company, puts it, “The guest wants better value and an experience they can consistently trust. Every menu item must earn its place by delighting the customer, strengthening the brand and justifying its operational cost.”

3. Make AI guest-visible and employee-valuable

The most productive applications of artificial intelligence (AI) are increasingly those that customers can feel directly. Voice ordering, improved accuracy, more relevant offers and smoother service recovery all contribute to a better and more consistent experience. In that sense, the return on AI is not just labor efficiency but also improved traffic and customer satisfaction through reduced friction. Leveraging AI in the back of the house (inventory, staffing, scheduling, forecasting) seamlessly creates more opportunity for the restaurant general manager (GM) and crew to focus on the guest experience and simplify the historically arduous and manual work of restaurant operations.

4. Frequency is a loyalty and data problem

Loyalty has become too important to treat as a digital coupon book. Leading brands are investing heavily in loyalty ecosystems and data to enable personalization. McDonald’s generated nearly $37 billion in systemwide sales with loyalty members in 2025 and ended the year with nearly 210 million 90-day active members globally. Starbucks’ 35.5 million active U.S. members reflect a program built not just around discounts but also around utility, tiering and more meaningful redemption. The strongest programs create habit, relevance and identity. The weakest ones simply train customers to wait for the next offer.

5. Operational excellence is a growth strategy, not a secondary consideration

Operational excellence is once again a top-line issue. In this environment, execution is not just about cost control — it is a primary driver of repeat visits. Black Box found that limited-service restaurants with no GM turnover in 2025 saw a 1.0-point traffic lift and a 22-point reduction in hourly churn. Additionally, pickup is gaining while delivery weakens, which makes order accuracy, pickup flow and the handoff experience more important than ever. Chipotle’s own “Recipe for Growth” underscores the point by centering more accurate and more efficient execution as a path back to transaction growth.

A clean dining room, an accurate order, a calm pickup shelf and a faster and more reliable drive-thru are no longer back-of-house details. They are increasingly part of the brand promise and impactful experience.

6. Compete with precision for the right occasion

The competitive set has widened. Restaurants are increasingly competing not only with each other but also with grocers, convenience stores, warehouse clubs and other food retail formats that can provide for the same eating occasion.

This makes precision critical. Winning brands are clear about the occasion they serve — the daypart, the need state, the customer segment — and build their proposition accordingly. Broad, undifferentiated traffic strategies are becoming less effective in a more fragmented competitive landscape (see Figure 3).

Closing perspective

The implication is not that growth has disappeared. It is that growth has become more selective. The industry may continue to point to consumer pressure, but the widening gap between winners and laggards suggests a more important shift.

2026 is a strategy test.

The next phase of comps outperformance will come from brands that can translate value into something the guest can see, taste and feel without eroding economics. This will require sharper menu architecture, clearer product signals, technology that improves the experience, loyalty that builds habit, consistent execution and tighter occasion targeting.

Concepts that rebuild the full value equation for their guests can still take share. This is even more critical among lower-income-focused concepts. Restaurants that rely on pricing alone are likely to find that the lever has lost much of its force. Winning brands will deliver value that customers can immediately recognize and choose again and again.

Note: This Executive Insights was written in collaboration with operator perspectives from Abigail Pringle.

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L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC

Market context: A strategic inflection point in consumer finance

In the evolving U.S. credit card landscape, scale and segmentation have become increasingly critical to long-term competitiveness. Issuers are under pressure to refine their customer targeting, expand product breadth and unlock operational efficiencies, particularly as they approach key regulatory and balance sheet thresholds.

Against this backdrop, a leading specialty finance provider saw an opportunity to expand beyond its core subprime focus into adjacent near-prime segments. At the same time, a large incumbent financial institution was seeking to divest a noncore credit card portfolio, creating a rare opportunity for the first institution to acquire a complementary business at scale.

This convergence of strategic repositioning and portfolio realignment set the stage for a high-stakes transaction, one that would test the acquirer’s ability to integrate a new platform as well as to redefine its trajectory for future growth.

Client situation and objectives: A high-stakes moment of transformation

Our client, a fast-growing credit card issuer with a strong position in subprime lending, was preparing to execute its first acquisition of this scale and complexity. The opportunity was compelling but came with significant pressure:

• Time constraints: The transaction required rapid execution, with tight deadlines imposed by the seller. 
• Operational complexity: The business needed to be transitioned seamlessly, with no disruption to customers. 
• Leadership bandwidth: The client’s senior executives were navigating concurrent challenges, including technology leadership transitions and heightened investor scrutiny. 
• Strategic expectations: The acquisition needed to do more than add scale. It had to expand the client’s product suite, broaden coverage from subprime into adjacent near-prime segments and position the company for growth beyond a critical asset threshold.

At the same time, internal stakeholders, from the CEO to the board, were aligned on one thing: Success in this deal would define the company’s credibility in executing future M&A and scaling its broader platform.

The question was not simply whether to proceed but also how to execute with precision, realize value quickly and build a repeatable model for future growth.

L.E.K. approach: Bringing clarity to complexity

L.E.K. Consulting partnered closely with the client’s C-suite to cut through complexity and define a clear path forward, working side by side with senior leadership throughout the process.

Our approach focused on three critical dimensions:

1. Defining the future-state operating model

We helped the client design its Day 1 and forward-state operating model, including:

• Integration strategy across customer segments and product offerings 
• Alignment of the acquired portfolio within a unified market positioning 
• Transition structures and agreements with the seller

2. Identifying and realizing value

We built a granular, bottom-up view of value creation, including:

• Detailed synergy identification at the initiative level 
• Clear ownership, timelines and execution pathways 
• Communication frameworks for internal stakeholders and the board

This enabled the client to quantify value and also to operationalize it.

3. Enabling seamless execution

We supported the client in navigating critical execution milestones, including:

• Customer migration and experience continuity
• Platform and operational integration
• Delivery against seller commitments within defined timelines

Throughout, we acted as a strategic thought partner to the executive team, helping them anticipate challenges, align stakeholders and make confident decisions in real time.

Impact: Building a platform for sustained growth

Following a successful integration and final conversion, the client emerged with more than an expanded portfolio. The specialty finance provider gained a scalable platform and a new set of institutional capabilities:

• Expanded market coverage, with a strengthened position across both subprime and near-prime segments
• Proven M&A execution capability, enhancing credibility with investors and the board
• Embedded tools and playbooks, including: 
  • Deal execution frameworks
  • Synergy realization methodologies
  • Third-party sourcing and management capabilities

These were not static deliverables, but capabilities fully integrated into the organization’s operating model. As a result, the client is now better equipped to pursue future strategic opportunities with confidence, discipline and speed.

The L.E.K. difference

This case reflects L.E.K.’s ability to combine strategic insight with hands-on execution support. By working directly with senior leadership, maintaining a focused and nimble approach, and grounding every decision in value creation, we help clients navigate complex moments and turn them into lasting competitive advantage.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC 

Periods of market uncertainty can quickly test the strength of client relationships, reshaping priorities around liquidity, risk, flexibility and cross-border financial needs. This special report explores how wealth and asset management firms across the GCC can protect client assets, deepen trust and maintain readiness for selective upside by delivering fast, holistic and highly tailored advice. It highlights the capabilities that matter most in volatile markets, from localized proposition breadth and targeted communication to agile advisor talent, responsive operating models, strong data and hands-on leadership.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC

Japan’s insurance distribution market is undergoing major regulatory change with the 2026 amendments to the Insurance Business Act. These reforms are set to reshape the role of in-house insurance agencies, challenging models built on intragroup transactions and limited independence. As expectations around governance, transparency and competition increase, maintaining the status quo is becoming difficult.

At the same time, this shift is creating strategic pressure for corporate groups and opening opportunities for investors through consolidation and externalization.

This Executive Insights outlines how the market is evolving, the strategic options available and what will be critical for successful execution.

1. A structural inflection point: Why now?

Japan’s insurance distribution market is entering its first major regulatory reform in decades, due to the 2026 amendments to the Insurance Business Act. Triggered by scandals involving ancillary agents and corporate insurance cartels, the reform aims to strengthen customer focus and fair competition(see Figure 1).

Its impact extends beyond prevention to reshaping agency governance, sales practices and distribution structures, prompting a reassessment of in-house agencies.

The reform will roll out in stages: initial rules in June 2026, with key changes like the “specific contract ratio” expected after approximately three years. Given restructuring timelines, delaying action is not viable — affected companies need early, proactive, strategy-aligned decisions.

2. The reality of in-house agencies: An overlooked segment

2.1. What is an in-house agency?

An in-house agency is an insurance agency established either as a department within a noninsurance operating company, such as large manufacturers, trading firms, utilities, telecoms and pharmaceuticals, or as a subsidiary within its group. It serves the insurance needs of the parent company, group companies and employees.

2.2. Scale and characteristics

Within the agency channel, which accounts for about 90% of non-life insurance distribution in Japan, in-house agencies have a distinct presence and unique characteristics:

• Approximately 9,530 entities are recognized as in-house agencies by the four major nonlife insurers (Financial Services Agency working group survey), indicating broad adoption particularly among large corporate groups
• Common in industries with multisite and multientity structures (manufacturing, trading, utilities, telecom), serving functions such as employee benefits administration and centralized group insurance management
• Product mix includes corporate risk coverage (property, liability, auto) alongside employee benefits such as group life insurance'
• Transactions are typically conducted within relationships with specific insurers, often resulting in structurally tied arrangements
• Lean staffing, sometimes only a few employees, with reliance on secondees from insurers
• Unlike independent agencies that compete on sales and service differentiation, in-house agencies are built on organizational proximity to the parent company

Group life insurance is typically embedded in human resources (HR) and payroll as an employee benefit, unlike non-life insurance, where annual reviews and insurer switching are common — an important distinction for regulatory and strategic considerations.

2.3. Structural challenges

In-house agencies face inherent structural challenges rooted in their dual role as both insurer agents and part of the client corporate group:

• Ambiguity of position
  Their dual identity makes it challenging to demonstrate neutrality in recommendations and effectively manage conflict. However, in life insurance, continuity of coverage through internal HR and paroll plans can benefit employees, offering an alternative view where stability aligns with customer interests.
• Limited operational capability
  Lean staffing and reliance on external resources (often seconded from insurers) can hinder effective autonomous management of sales and compliance as an insurance agent.
• Lack of independence
  Dependence on intragroup transactions weakens competitiveness in external markets and raises regulatory concerns, particularly regarding commission structures that may function as implicit premium discounts.
• Distortion of fair competition
  Intragroup transactions often bypass competitive comparison, raising concerns about alignment with fair market conditions.

Historically, these structural challenges were not rigorously scrutinized. Under the new regulatory environment, the key question is whether these agencies can operate as genuinely independent businesses. The reform evaluates whether all these requirements can be met simultaneously.

3. Impact of regulatory tightening on in-house agencies

The regulatory tightening does not simply impose incremental requirements on in-house agencies; rather, it fundamentally reassesses whether they can operate as viable, independent agency businesses. Its impact manifests primarily in the following areas:

• Constraints on intragroup transaction dependent models
  For agencies reliant on intragroup transactions, meeting regulatory requirements — particularly contract ratio thresholds — may be structurally difficult, making a fundamental reassessment of the business model unavoidable (see Figure 2).
• Higher level of operational standards required
  As expectations for solicitation management and compliance rise, baseline operating standards are elevated. Agencies with lean staffing or reliance on insurer secondments may no longer be able to sustain their current operating models.
• Pressure to reassess the business model
  Tighter requirements on comparison, recommendations and conflict management will force a reassessment of models reliant on specific insurers, with even established transaction structures facing greater scrutiny as explainability becomes expected.

These changes do not target isolated issues but instead collectively challenge whether in-house agencies can function as “independent agency businesses.” Consequently, affected agencies will find it increasingly difficult to avoid revisiting their fundamental business models.

It should be noted that these regulations are primarily designed with non-life insurance agencies in mind. However, while group life insurance handled by in-house agencies is not directly subject to these regulations, its treatment becomes a key practical consideration in any restructuring of the agency business.

4.Strategic options

Companies that own in-house agencies are now compelled to make strategic decisions regarding the future of these entities, as maintaining the status quo is increasingly difficult. While each option has its own rationale, the appropriate path depends on alignment with corporate strategy, capabilities and capacity to respond to regulatory requirements.

4.1. Option A: Comply — Restructure to meet regulatory requirements and retain the agency

This option involves maintaining the in-house agency while restructuring its operations to comply with regulatory requirements. In practice, this requires reducing reliance
on intragroup transactions by developing external customer relationships, as well as strengthening solicitation management and compliance frameworks to withstand scrutiny as an independent agency business.

In-house agencies often lack the sales infrastructure, brand recognition and incentive structures typically required to compete for external clients. As a result, transforming the business model requires significant time and investment.

Moreover, the cost of compliance may ultimately exceed the strategic value of maintaining the agency. In addition, regulatory uncertainty, such as potential future tightening of contract ratio thresholds, introduces the risk that required compliance levels may continue to evolve.

4.2. Option B: Divest — Carve out and externalize the agency business

This option separates the agency from the group and transfers it to an external party, with the parent shifting to market-based procurement. It suits cases where the agency is noncore or regulatory burdens are high (see Figure 3).

Carve-outs must address employees, contracts and customer relationships, with continuity and trust critical due to intragroup integration. Buyers will focus on customer quality and revenue sustainability, while timing may affect valuations.

Group life insurance adds complexity, as its integration with HR and payroll limits transferability, requiring clear separation of program design, administration and placement.

4.3. Option C: Expand — Position the agency as a growth platform

Under this option, the in-house agency is repositioned not as an internal support function but as a growth business. This involves expanding insurance provision to external clients and scaling the platform through acquisitions and integration of other agencies, while meeting regulatory requirements.

This path requires a transition from a group-centric model to one that actively serves external clients. It may involve acquisitions, integration efforts and talent development. While resource intensive, it offers potential not only for compliance but also for long-term growth of the agency business.

4.4. How to choose among strategic options

In-house agencies have multiple strategic options — comply, divest or expand — but these are not equally feasible for all companies. The critical question is not which option is theoretically optimal, but which is realistically executable.

Feasibility depends on regulatory requirements and on structural characteristics unique to in-house agencies, particularly in the following areas:

Ability to transfer people (not just contracts)

• In divestitures, the transfer of personnel is a central issue. Many in-house agencies rely on staff who simultaneously perform roles within the parent company, making full transfer difficult. This often results in situations where contracts transfer but personnel do not sufficiently follow.
• Even where staff are transferred, discrepancies may arise between prior workload and posttransfer expectations (e.g., full-time deployment), leading to inefficiencies or mismatches in staffing levels and threats to business viability.
• Therefore, securing dedicated personnel aligned with contract volume is a prerequisite for a viable stand-alone business.

Ability to develop external customers

• Both comply and expand strategies require growth in external business. However, in-house agencies are typically built around internal demand and often lack external sales capabilities, including sales infrastructure, brand recognition and incentive systems.
• Developing these capabilities requires more than incremental changes; it entails building a new commercial function and effectively transforming the business model.

Timing relative to regulatory implementation (investment and lead time)

• Organizational restructuring, talent reallocation and capability building require a long time. Given regulatory timelines, the range of feasible options is constrained by the time available.
• Furthermore, uncertainty around future regulatory changes increases investment risk, particularly for options requiring long-term commitments.

Ability to separate intertwined plans (treatment of group life insurance)

• Group life insurance, often embedded within HR and payroll, is difficult to separate from the parent organization. Even when externalizing the agency, the insurance plan itself typically remains with the parent, requiring a separation between system governance and insurance placement.
• The feasibility and design quality of this separation directly affect not just employees but also relationships with insurers and counterparties, thereby influencing the viability of strategic options.

In practice, while all options are theoretically viable, feasibility varies significantly by company. For many, externalization, including divestiture, emerges as the most practical path.

Given these constraints, it is important to determine the optimal direction for the company by considering both the level of the specific contract ratio and the strategic importance of the agency.

5. Emergence of a buyer’s market: Strategic opportunities for private equity and platform players

The impact of regulatory tightening is becoming increasingly visible, particularly as changes to the specific contract ratio make it difficult for agencies reliant on intragroup transactions to remain compliant. As a result, reviewing business models or pursuing externalization is becoming a realistic option.

Although in-house agencies vary in size and capability, they hold valuable assets, such as corporate client relationships, specialized talent and insurer ties, that are often underutilized on a stand-alone basis but can gain value through consolidation.

With more firms likely to consider externalization, and clear potential for value creation through integration, this creates a meaningful opportunity for investors and platform players.

5.1.  Key buyer groups

Private equity (buyout funds)

An increase in carve-out opportunities creates favorable conditions for roll-up strategies. By acquiring and integrating multiple agencies, buyers can drive efficiency through shared back-office functions, compliance frameworks and information technology platforms, while expanding into external markets. Given the fragmented nature of Japan’s insurance distribution market, the potential for value creation through consolidation is substantial.

Domestic independent agencies and platform players

These players focus on expanding their customer base and enhancing portfolio quality. Relationships with large corporate clients held by in-house agencies are difficult to replicate through organic growth and represent high-value assets.

They may also seek to strengthen risk management capabilities, deepen sector expertise or enhance global service capabilities, while maintaining continuity with existing customer relationships.

Global independent agencies and platform players

Leveraging global networks and specialized expertise, these players pursue acquisitions to strengthen their presence in Japan and enhance service offerings. In-house agencies can be integrated into existing platforms to generate additional value.

The distinction from domestic players lies less in capability than in their approach, emphasizing globally standardized service delivery and expansion into specialized domains.

5.2. Key success factors in acquisitions

Even where acquisition opportunities arise, success depends on postacquisition value creation. Key factors include:

• Activation of customer base and service expansion
  Deepening engagement within existing corporate relationships and expanding service offerings is a practical path to revenue growth.
• Integration of back-office functions
  Consolidating fragmented administrative functions (policy management, compliance, finance) improves efficiency and reduces costs.
• Digitalization and productivity enhancement
  Digitizing processes across sales support, customer management, quoting, contracting and claims can significantly improve productivity.
• Smooth stakeholder transition
  Successful carve-outs depend on maintaining relationships across employees, customers and the parent company. In Japan, employment continuity, stable working conditions and service continuity are critical, making transparent, trust-based transition design as important as the postacquisition operating model for execution and value creation.

It is also expected that group life insurance programs will remain with the parent company, limiting the acquisition scope primarily to nonlife agency functions.

Conclusion: The importance of acting now

The in-house agency landscape is at a structural inflection point driven by regulatory change. Previously tolerated business models are now being reassessed based on the in-house groups’ ability to operate as independent agencies.

Companies face three strategic options — comply, divest or expand — none of which can be pursued passively. Each requires deliberate, strategy-aligned preparation, and given the regulatory timelines, delaying decisions is not viable.

As restructuring accelerates, market conditions may shift, with more sellers potentially impacting deal dynamics and transaction terms.

Ultimately, the priority is to define the in-house agency’s role within the broader portfolio, shaping compliance, competitiveness and resource allocation. Deciding whether to retain, externalize or scale is no longer optional — it is a proactive strategic imperative.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC 

All pharmaceutical franchises must come to an end. Between 2025 and 2030, over $300 billion in prescription (Rx) drug revenues are expected to lose exclusivity. Traditional loss-of-exclusivity (LOE) strategies — including product/patent hopping, authorized generics and brand-for-generic contracting — are well known. However, several emerging trends and policies have added pressure to the drug life-cycle and/or the ability to effectively implement such strategies (see Figure 1).

As pricing policy, payer economics and patient purchasing channels evolve, biopharmaceutical companies need to evaluate whether selected mature assets can preserve value through self-care migration via over-the-counter additional condition for nonprescription use (OTC-ACNU), targeted cash-pay access through manufacturer direct-to-consumer (DTC) platforms or both.

Over the past approximately 12 months, two new significant programs have launched, with the potential to expand value creation from late-in-life-cycle drugs:

• OTC-ACNU, a new option for converting Rx drugs to OTC, which went live in 2Q2025, though no OTC products have been approved through it yet
• DTC platforms, with TrumpRx launching in February 2026 following manufacturer platforms (2024-present) and Most-Favored-Nation (MFN) dealmaking (September 2025-January 2026)

In this edition of L.E.K. Consulting’s Executive Insights, we discuss OTC-ACNU and DTC as potential life-cycle management tools for preserving value.

ACNU: A new option for Rx-to-OTC conversion

In the U.S., medications can be acquired through two routes: Rx and OTC. Rx drugs are dispensed by pharmacies, leaving patient oversight and counseling responsibilities to the clinicians who write the scripts. OTC drugs are sold directly to consumers with standardized “Drug Facts” labeling and usage instructions. They are safe and effective for self-directed use when taken as labeled. Typically, these are high-volume drugs for mass consumption, indicated for non-life-threatening diseases and made available at relatively low price points.

Rx drugs can be converted to OTC, which may help expand their market while adding three years of market exclusivity if supported by the proper clinical studies and filings. After declines since the mid-1990s, there has been recent growth in Rx-to-OTC conversions, which may reflect evolving Food and Drug Administration (FDA) openness to OTC conversions (see Figure 2).

Traditionally, Rx-to-OTC conversions could be executed through a “full switch” or a “partial switch” (designating certain conditions of use to be OTC or Rx), but were limited to drugs that were clearly safe and appropriate for self-selection and self-use.

At the end of 2024, the FDA announced a new option for Rx-to-OTC conversions when paired with ACNU (see Figure 3). This option aims to expand the set of drugs appropriate for OTC use. Previously, OTC designation was focused on drugs that could be safely used based solely on consumer-friendly labeling. ACNU introduces an extra step for self-selection, such as a questionnaire, a required digital video or an automated telephone response system. Unlike traditional pathways, ACNU products can exist as both Rx and OTC, allowing for greater flexibility across patients and providers.

This differs from the partial switch OTC path, which allows for Rx and OTC sales with meaningful differences (e.g., indications, strengths). The ACNU definition is intentionally broad, allowing manufacturers flexibility in tailoring the extra step. This flexibility may prove important as manufacturers balance clinical risk, user experience and preferences across stakeholders (see Figure 4).

While still an emerging pathway with limited precedent and operational uncertainties, ACNU may make OTC conversion more feasible for patient-directed care across a broader set of drugs (e.g., statins, asthma inhalers, migraine medications). With less prescriptive ACNU guidance, there remains significant operational questions open for the initial pathway approvals to tackle. Manufacturers willing to invest in the required studies and market-shaping activities may benefit from extended exclusivity and a new purchasing channel.

For assets with strong safety profiles and straightforward patient use, ACNU may expand the drug life-cycle beyond the Rx years.

TrumpRx: A central platform for DTC sales

The expansion of telehealth, accelerated by the COVID-19 pandemic, together with the strong demand for anti-obesity medications prompted several manufacturers to launch their own DTC platforms. Lilly announced LillyDirect in early 2024, offering a digital pharmacy coupled with access to telehealth and in-person providers and educational information; it’s focused on patients with obesity, migraine and diabetes. Notably, it offers patients the option to self-pay at a discount to list price, outside the traditional insurance benefit. Other manufacturers followed suit, launching their own platforms, including PfizerForAll and NovoCare Pharmacy, through early 2025.

An executive order issued in May 2025 increased focus on DTC, making it one of the four pillars of the Trump administration’s MFN pricing policy. After receiving letters from the administration, 17 pharmas struck deals addressing each of the MFN pillars.

TrumpRx launched on Feb. 5, 2026, with 43 drugs from five manufacturers. The site advertises MFN pricing through GoodRx-powered pharmacy coupons or pass-throughs to manufacturer sites. Diabetes and obesity are the clear centerpiece of the initial portfolio, with the roughly seven indicated drugs representing over 90% of the estimated 2025 worldwide revenues associated with the portfolio (see Figure 5).

Many of the remaining products appear older, with about 80% of these drugs genericized or more than 15 years old and others in competitive classes (see Figure 6). Likewise, brands added to TrumpRx later and brands mentioned for DTC in MFN deals and not yet on TrumpRx largely share similar characteristics: They’re at or nearing the end of their life-cycle or in a competitive class.

For most patients, DTC and TrumpRx are unlikely to be transformative — patients can access their medications or generic equivalents through insurance with a lower out-of-pocket cost. However, this provides a consolidated channel for patients who are uninsured or underinsured or who might prefer branded options. It allows manufacturers to cut out some of the traditional drug channel intermediaries, enabling the discount pricing.

For assets with cash-pay demand, brand loyalty or access friction, DTC may create a targeted late-life-cycle channel even if it does not reshape access for the broader market.

Next steps for biopharmas

Both ACNU and TrumpRx are live, and precedents are still being set, for biopharmas with assets approaching LOE in the next two to five years. Strategic decisions being made over the next 12 to 24 months will determine which companies capture value from these channels and which cede it to generics and intermediaries by default. In planning for LOE, biopharmas should consider the full suite of strategic levers. OTC-ACNU and DTC platforms, such as TrumpRx, serve as two newer methods with different requirements for execution.

If you are evaluating strategies for capturing value for mature and late-in-life-cycle products, including OTC, DTC or other LOE defense strategies, please contact us. For more information on DTC strategies, please see our recent article on the topic. We have also published on consumer health OTC considerations, please see our recent article.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC

It takes 10-15 years and over $2 billion on average to bring a single drug to approval. This is driven by evidentiary requirements — several phases of clinical trials, each requiring greater enrollment of patients — and the failures along the way.

In February 2026, Center for Biologics Evaluation and Research (CBER) Director Vinay Prasad and Food and Drug Administration (FDA) Commissioner Martin Makary published a commentary/opinion piece in the New England Journal of Medicine titled “One Pivotal Trial, the New Default Option for FDA Approval — Ending the Two-Trial Dogma.” The article closes noting that the Food and Drug administration’s (FDA) new default position is “one adequate and well-controlled study, combined with confirmatory evidence, will serve as the basis of marketing authorization of novel products.”

This latest information reflects long-standing debates about trial design efficiency, evidentiary and data sufficiency, and the balance between rapid access and robust evidence for novel medications. Prasad and Makary suggest that this will lead to cost and time savings, resulting in a “surge in drug development.”

Industry response has been generally positive, with reactions ranging from transformative to cautious optimism. However, former Center for Drug Evaluation and Research (CDER) Director Richard Pazdur has called this “very dangerous,” highlighting that “these [end points] may be subject to bias, and sometimes it’s important to have clinical trials and duplications of clinical trials in those areas. My caution is, all that glitters is not gold, one has to be very careful, and I hope the upcoming guidance that is being written on this is cognizant of the differences that would exist between other therapeutic areas.”

With the departures of Makary and Prasad, it is unclear if this will become the new standard. If it does, this change could be seen as a win for biopharma, although uncertainties remain.

In this edition of Executive Insights, L.E.K. Consulting contextualizes the news and provides key questions that biopharma executives should be asking.

How big of a shift is this? What drugs are impacted?

Under Title 21 of the Code of Federal Regulations, FDA approval requires “substantial evidence” of effectiveness. Historically, this has often been interpreted as evidence derived from two adequate and well-controlled studies. However, the statute does not explicitly mandate two trials.

Precedent has allowed approval based on a single adequate and well-controlled study with confirmatory evidence in appropriate circumstances. This distinction is important, and the commentary from Prasad and Makary does not alter the statutory standard but reframes how substantial evidence may be demonstrated in modern development settings.

Looking at approvals over time before the Trump administration, a declining number of therapeutic approvals have required multiple efficacy trials to support approval, with 60%-70% of CDER and CBER new molecular entity (NME) approvals in 2024 relying on a single trial (see Figure 1).

Most of these single pivotal approvals (75%) had an orphan designation and/or were approved through the accelerated approval pathway (see Figure 2). Among those that required more than one efficacy trial, few had orphan designation and none was approved through an accelerated pathway. Approximately 15% of the 2024 NME approvals leveraged repeated trials (i.e., identical designs), which are most likely to be impacted by this new single pivotal option.

What uncertainties remain?

Trial requirements and optionality: The potential cost savings and timeline improvements depend on the characteristics of the single pivotal option (including any differences in postmarketing evidence generation). The Prasad and Makary article frames this shift as modernization rather than as a lowering of evidentiary standards. It emphasizes magnitude of effect, statistical analyses and a range of trial design elements (including end point and comparator selection) as critical building blocks of credibility.

It remains unclear whether the single pivotal option is equivalent to one of the former two pivotal designs or it is more burdensome. Eliminating a second global Phase 3 study could reduce duplicated enrollment, site management and operational costs. However, this change is likely to increase trial design complexity (e.g., sample size, statistical powering, follow-up timing, geographic representation, postmarketing commitments), which may offset part of the theoretical savings. It is unclear to what degree the FDA may enact one trial as the primary path or allow pharma companies to choose to take a multiple pivotal path if they choose.

Comparator risk: If the single pivotal option drives greater focus on active controls and head-to-head trials, it could increase both cost (especially if a branded comparator) and risk. Of the 2024 single pivotal approvals, approximately 80% were either placebo controlled or lacked a control group (see Figure 3). Active control trials were more common among multiple pivotal approvals (roughly 27% vs. 16%). When leveraged, head-to-head trials can provide a clear rationale for drug access and uptake, but a negative result could diminish the drug’s value proposition.

Manufacturer appetite for single pivotal trials: While many companies would likely prefer a single trial for approval, this may not be true across all therapeutic areas as it consolidates risk into a single trial. Hesitance may be more likely in indications with high placebo rates (e.g., psychiatry). If run as a single pivotal trial, it opens several questions: Would the FDA accept a positive single trial for approval? If negative, could a second trial be run? What happens in the case of mixed results?

Postmarketing data requirements: If the single pivotal option shifts more regulatory risk post approval (similar to an accelerated approval), it may lead to more withdrawals from the market if the approval data is not confirmed. For context, of the 278 accelerated approvals from 1992 to 2021, approximately 12% were withdrawn (versus about 50% converted to full approval and about 39% pending at the time the analysis was published). A more recent oncology-focused analysis highlights approximately 22% withdrawn among 2013-17 approvals (versus 63% converted and 15% pending). The FDA may also be stricter in enforcing and monitoring postmarketing commitments.

Regulatory durability: With development programs spanning multiple years, it is likely that they span multiple leadership and/or policy changes. It is unclear whether these changes will hold with future administrations. Likewise, drugs that were targeting a single pivotal approval before Prasad and Makary’s article may also see increased scrutiny from the current administration. This issue has been apparent through recent high-profile FDA actions, which saw differences in opinion on the robustness of end point and comparator decisions (e.g., Disc Medicine, Uniqure). Prasad and Makary’s recent departures raise additional uncertainties regarding the impact of their article.

Global repercussions: Trials are often designed to meet the requirements of multiple global regulatory agencies of other countries, with some countries relying on FDA approval as a key input to their own approval pathways. It is unclear whether this change will impact this relationship, leading to changes in biopharmas’ global clinical development planning.

Physician and payer reactions: With less data generated, physicians and payers (U.S. and global) will need to weigh the strength of new therapies and compare data across competitors. Their reactions might impact the adoption of, pricing of and access to new drugs.

Considerations for biopharma leaders

To prepare for the potential shifts in trial requirements and expectations, biopharma leaders should evaluate development strategy through a structured decision framework:

• What options exist for FDA approval?
• Which option should be prioritized, considering the potential asset or portfolio value across differing timelines, global development costs and commercial scenarios?
• What operational enhancements are required to ensure strong execution and timely pre- and post-approval evidence generation?
• What additional FDA interactions might be required to ensure an aligned registrational trial design?
• What are the broader implications for the portfolio and financing requirements?

Conclusion

The discussion about a single pivotal trial pathway reflects a broader evolution in regulatory interpretation, statistical methodology and development strategy. This may be the culmination of a trend toward majority single pivotal approvals. It does not appear to alter the statutory requirement for substantial evidence, nor does it eliminate alternative evidentiary pathways. A single pivotal trial strategy may offer efficiency in some contexts, but it may also concentrate risk and introduce downstream uncertainty in others. The optimal path will vary by asset, competitive landscape, capital structure and global footprint. 

Strategic advantage will accrue to organizations that rigorously assess both pathways; proactively align with regulators, payers, physicians and other stakeholders across jurisdictions; and embed evidentiary decisions within broader portfolio and capital strategy.

If you are considering optimizing your clinical development plan for this new pathway, contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting LLC