Day 1 at SCOPE 2026 set a clear and human-centered tone for the week. Across opening sessions, fireside chats, and roundtables, the conversations reinforced that while innovation in clinical research continues to advance, the systems supporting patients and execution still demand serious attention.
Patient experience anchored the day in reality. Lindsay Guentzel shared her experience accessing CAR-T therapy for a rare condition—underscoring how transformative the treatment was, and how difficult the path to enrollment remained. Delays in connecting with trial sites, lack of clarity once enrolled, and the financial burden placed on patients illustrated how opaque and fragmented the process can be, even for someone deeply experienced in healthcare. Brad Watts, a patient advocate and CAR-T therapy recipient, reinforced the need for greater access, education, and fewer barriers that patients are still expected to navigate largely on their own. The session closed with a powerful call to action from Jane Myles: participating in a clinical trial should not require a superhuman effort.
Operationally, familiar execution gaps surfaced across sponsors, CROs, sites, and technology partners. While there is broad alignment on desired outcomes—better feasibility, faster timelines, stronger site engagement—many organizations continue to struggle with how to structure partnerships, ownership, and accountability. Phase IV and non-interventional studies emerged as a recurring gray zone: growing in importance, yet often lacking a consistent operating model or clear internal ownership, creating both risk and opportunity.
Data and AI featured prominently in discussions focused on practicality rather than hype. The opening industry roundtable, Using Data and AI to Accelerate Trials, led by Mette Smedegaard Andersen, explored how data-driven approaches are improving protocol design, feasibility decisions, trial predictability, and cycle times. The strongest takeaways emphasized embedding technology to support endpoints, data quality, and patient experience—rather than forcing protocols to adapt to tools.
Day 1 also recognized innovation across the industry during the SCOPE 2026 Awards Ceremony. Ultimately, Day 1 reinforced a consistent message: clinical research still runs on trust, transparency, and follow-through. Technology can enable progress, but alignment, accountability, and a genuine commitment to patient-centered execution will determine whether innovation translates into real-world impact.
Already we are seeing key signals emerge:
The clinical research industry faces a paradox: despite two decades of technological innovation—from EDC to decentralized trials to wearables to AI—the timeline from molecule to market approval remains essentially unchanged. Companies are more productive, but not faster. As the cost of drug development has tripled since 2010 (from $802M to $2.6B), the industry is being forced to confront a harder truth: execution fails more programs than science.
SCOPE 2026 revealed that the path forward requires less innovation tooling and more intentional strategy around people, partnerships, and protocol simplicity. For small biopharma especially, survival depends on ruthless vendor discipline, cross-functional alignment, and honest communication during inevitable disruptions.
This synposis distills real-world examples from SCOPE sessions to offer actionable frameworks for clinical leaders navigating 2026’s market realities.
Scott MeGaffin, CEO of Adiso Therapeutics (small-molecule inflammation company in Concord, Massachusetts), presented the JP Morgan Healthcare Conference outlook at SCOPE. His assessment: 2026 is the “year of the horse”—characterized by “discipline momentum” after years of uncertainty.
Key market signals:
The China Wildcard. MeGaffin warned that Chinese biotech isn’t just catching up to Boston—it’s out-executing it. The real risk isn’t imitation, but innovation sequencing. Using HMG-CoA reductase inhibitors as the case study, he pointed out what U.S. pharma learned the hard way over decades: first-in-class rarely wins. Mevacor opened the door, but atorvastatin and rosuvastatin became standard of care. Chinese developers are applying that lesson from day one—designing directly for best-in-class, accelerated by massive patient access and faster regulatory pathways. The result is a speed and sophistication gap the U.S. can no longer ignore.
Practical Takeaway for Small Biotech:
The industry has conducted thousands of acquisitions. Yet there is no playbook that prevents disruption. Jazz Pharmaceuticals, which executes M&A at least once annually as a core growth strategy, has learned this lesson repeatedly.
James (Jazz Pharmaceuticals) shared that, even with a disciplined approach—focusing acquisitions only on their core therapeutic areas (neuroscience and oncology, specifically sleep and epilepsy)—every integration still surfaces surprises. Jazz’s recent Chimerix acquisition (announced March/April 2025, with an FDA approval deadline in August 2025) illustrates the tension:
The lesson: You acquire for a reason. Disrupting success is counterproductive. Yet most acquirers struggle to resist the urge to “fix” or “optimize” immediately.
Cereval → AbbVie acquisition faced an unexpected 8-month delay (announced December 6, 2023; closed August 1, 2024) due to SEC scrutiny. The acquiring company faced a critical question: How do you keep talented people motivated through prolonged uncertainty?
The answer: Radical transparency. An SVP committed to weekly all-hands updates—even when the update was “we have no news.” The consistency of communication, combined with clear rationale, prevented the typical talent exodus. Staff stayed through the ordeal, and integration post-close was smoother because the team was already mentally transitioned.
Critical Takeaway: When facing M&A uncertainty, over-communicate. People can tolerate “no news” far better than radio silence or conflicting narratives.
Stephanie (small biopharma operations leader) attended a vendor meeting to discover the provider had divested a service line she’d been relying on for months. The vendor hadn’t proactively notified her. She learned it was “no longer part of our portfolio” during the conversation.
This scenario is common but entirely preventable. Competitive intelligence doesn’t exist for vendor capabilities—sponsors must manually track vendor M&A, divestitures, and capability shifts. The workaround:
Historically, pharmacovigilance (PV), biostatistics, data management, and clinical operations have operated independently. Laura Rossetti (Director, Taysha Gene Therapies), Niki Witthuhn (Senior Director, PV Operations, Beam Therapeutics), and Gerry Downey (Statistician, formerly Amgen) presented a different model at SCOPE.
The Traditional Problem:
The Solution in Practice: At Taysha Gene Therapies, Laura integrated PV into study startup activities:
Result: Sites feel more prepared; safety signals are detected earlier; CRAs understand the “why” behind queries.
Real Example from Beam Therapeutics: Niki shared that commercial teams were reporting mild events as “serious” simply because the patient was hospitalized for routine treatment. Rather than issue corrective data queries, PV + operations created a retraining program. The solution wasn’t procedural; it was understanding the difference between hospitalization for care and hospitalization for safety.
Gerry Downey (Amgen veteran) emphasized that biostatisticians can paint narratives from data that regulatory authorities understand. But this requires early alignment:
Actionable Framework:
Shawne Moran (Head of Study Operations, Park KGA/AMD Sereno) presented a sobering reality: Over the past 20 years, the industry adopted EDC, reduced data verification, centralized monitoring, wearables, and now decentralized trials. Yet the overall timeline from molecule to market has not changed.
Why? Because productivity gains have been offset by added complexity and regulatory scrutiny. We’re not accelerating; we’re moving time to different buckets.
Robert Goldman (Global Head Medical Operations, Contraline—the world’s first male contraceptive company) moderated a panel dedicated to lean clinical operations. His core assertion: “Execution really fails more programs than science.” And the path to better execution isn’t more tools—it’s clarity.
Matthew Failor (VP Operations) outlined his philosophy: “Most problems are solved not by innovation breakthroughs, but by retraining a problem.” When asked about the abundance of vendor options in the exhibit hall, he responded: “What are they doing to bring us closer to commercialization? If not, it’s noise.”
Matthew’s Real-World Example: He refuses to bundle contracts for eTMF, EDC, drug manufacturing, and database under a single vendor. Here’s why:
Real FDA Response Letter Example: A company’s entire Phase 3 program failed due to packaging issues—not the science, not the data. The packaging vendor, if also controlling eTMF and database, could hold the sponsor hostage during remediation.
Matthew’s approach:
Cost: Slightly more complex vendor management. Benefit: Control and leverage during disputes.
Alison Billups (Executive VP Client Solutions, ClinLab Solutions Group) explained when functional service providers (FSPs) outperform full-service CROs for small biotech:
For small biotech with limited resources, the FSP model—using 3-4 focused providers rather than one behemoth—often works better because each provider is incentivized to support sponsor success to win additional business.
Michael Hickey (VP Clinical Operations, Processa Pharmaceuticals) shared his framework for vendor management:
The metric isn’t compliance; it’s forward momentum. If a vendor is blocking progress faster than solving problems, the cost of change is lower than the cost of status quo.
Joe Benz (audience member) shared a rare achievement: He ran a trial under an SPA (Special Protocol Assessment) for a tenatus indication without a single protocol amendment.
How? The drug’s indication was so tightly defined in the FDA alignment that any protocol change required formal FDA re-approval. This created enormous friction, but it also created absolute discipline.
Trade-off: Slower adaptability, but ironclad protocol execution. For 98-99% of sponsors, this isn’t practical. But it proves that protocol amendments aren’t inevitable—they’re a choice.
One of the most actionable takeaways from SCOPE was simple: Ask vendors for skin in the game, and they often say yes.
Survey at SCOPE: Only 2 hands went up when asked “Who negotiated a contract where the vendor has equity or risk participation in 2025?”
Yet when panelists detailed their experiences, the room realized it’s far more common than they thought.
Real-World Models:
The Psychological Shift: When a vendor has financial skin in the game, their daily behavior changes. Instead of finding reasons to monetize scope creep, they help solve problems. Why? Because finishing faster means equity payoff or milestone achievement.
Matthew Failor’s Observation: “You’d be amazed how often this works. Even large vendors, when you structure it right, will participate. They believe in you too.”
Kristine Koontz (Global Clinical Operations, Daiichi Sankyo—17,000 employees, Japanese-based) brought 20+ years of co-development experience, including prior roles at AstraZeneca (on BMS diabetes collaboration) and GSK/J&J.
Current Reality: Daiichi has two active co-dev partnerships with large pharma. One came with an uncomfortable surprise: the partner wanted to increase oversight and real-time data access to levels Daiichi couldn’t support (they don’t have the affiliate network).
How It Resolved: Rather than fight, Daiichi increased the budget, escalated to CEO for a difficult conversation, and renegotiated terms so Daiichi could actually deliver. The partner appreciated the honesty and commitment. The relationship strengthened because Daiichi didn’t overpromise and then underdeliver.
Key Lessons on Co-Dev Governance:
Doug Schantz (Head Clinical Operations, AskBio, Bayer’s gene therapy company) faced a CEO question on his first day in July 2022: “What time is the patient being dosed in Cincinnati?”
He didn’t know. Small biotech doesn’t track that level of detail—they trust their teams. But large pharma demands it.
The Challenge: AskBio’s small team was hired for academic rigor, scientific independence, and close site relationships. Bayer brought processes, governance, and structure. How do you integrate without destroying what was acquired?
The Solution:
Real Problem & Fix: Early on, 13 data management people from Bayer showed up uninvited to a clinical ops call. The response: transparent communication. “Don’t do that. Here’s how we’ll coordinate.” Issue resolved.
Ongoing Reality: This remains a change management project. Some team members signed up for small biotech culture and feel the loss. Others embrace the resources. The integration succeeds because both sides acknowledge it’s ongoing work, not a one-time event.
Ann-Marie Hulstine (VP Clinical Operations, Alpheus Medical, formerly a large pharma executive who went to a startup) experienced the opposite: a startup acquired by a larger entity, with the CRO transitioned to a larger provider.
The Problem: Sites noticed. Communication slowed. Responsiveness declined. Sites preferred the smaller vendor.
The Workaround: Rather than fight the transition, she:
Lesson: Sites have choices. Sponsors don’t get to demand loyalty—they have to earn it through responsiveness and respect.
The Merck CMO keynote reframed AI discussion around real problems, not hype:
“Citizen AI” = using AI to make clinical staff’s lives incrementally better, not replacing them.
Real Applications:
Protocol Design Example: One team analyzed social media conversations about cancer patient experiences and discovered that patients avoid cancer centers due to infection fear and the psychological burden of seeing dying patients. This insight drove a strategic shift to subcutaneous and oral medicines and satellite centers instead of mothership hospitals.
Pediatric Example: In Gardasil vaccine trials (women in middle-income countries), enrollment stalled because women had nowhere to leave their children. The solution: Offer daycare centers at trial sites + meal vouchers. Enrollment improved significantly. This came from asking “Why would a patient want to come to our study?”—not from an algorithm.
Dr. Victoria Gamerman (Global Head of Digital Transformation, Boehringer Ingelheim) shared a Boehringer Ingelheim case study from her personal experience:
Challenge: Build a well-phenotyped AND well-genotyped rare disease patient registry for drug discovery acceleration
Solution: Create a semantic layer connecting:
Result: Complex questions answered in minutes instead of months. The “brain” approach—not replacing human judgment, but augmenting it with connected data—proved transformative.
Quant Health.ai and similar platforms now simulate trial outcomes:
Use Case: Before finalizing a Phase 3 protocol, simulate where the trial might land. This allows sponsors to catch IE (inclusion/exclusion) criteria misalignments early. Example: If US sites don’t perform a required test (only done in Europe), you won’t recruit a single patient in the US unless you address it pre-protocol.
Realistic Expectation: Not a crystal ball. But helps sponsors move from tactics (“How do we build evidence?”) to strategy (“Where might this trial land, and what might we miss?”).
Panelists: Sandeep (Head of Data Science at AstraZeneca), Shawne Moran (Head, In-Country Study Operations-Americas, EMD Serono/Merck KGaA), Jared Saul (Chief Medical Officer, Commercial Life Sciences, Amazon Web Services)
Prediction Framework:
Shawne’s Vision: Single sign-on across all studies. One investigator database. All studies locked down, validated, with all vendors and tech integrated.
Reality Today: Sites manage 30+ tablets, apps, and portals, each for a different sponsor/vendor.
Shift Needed: Industry alignment on unified infrastructure. This requires vendor consolidation or radical interoperability. Neither is easy.
Jeremy Goldberg (Arsenal Capital Partners, investor perspective):
This math explains the urgency: Every month saved in development = millions in revenue protection. But the industry hasn’t cracked the code on actually saving months. Productivity gains have been consumed by complexity.
2026 is not the year of breakthrough innovation. It’s the year of discipline, intentional strategy, and honest partnerships.
The clinical research industry has spent two decades optimizing individual functions and adding tools. Yet the molecule-to-market timeline persists. The cost has tripled. And execution—not science—now fails more programs.
The companies that will thrive in 2026 will be those that:
The good news: This is learnable. Jazz Pharmaceuticals, Daiichi Sankyo, AskBio, Adiso Therapeutics, and others are already executing this playbook. Their successes—and hard-won failures—are the map for the rest of the industry.
The acceleration won’t come from another tool in the exhibit hall. It will come from teams that are ruthlessly aligned on what matters.
This executive intelligence brief was compiled from concurrent sessions at SCOPE 2026 Day 2 (February 3, 2026). It reflects themes, frameworks, and real-world examples shared by clinical operations leaders, regulatory professionals, and technology vendors. Distributed to clinical operations leaders, development leaders, regulatory professionals, and clinical strategy executives who attended or want consolidated insights from the conference.
Day 2 of SCOPE 2026 crystallized a fundamental industry shift: Clinical operations are moving from “manage the process” to “orchestrate the ecosystem.” This requires less innovation tooling and more intentional strategy around vendor partnerships, organizational readiness, and patient-centric protocol design.
Three critical inflection points emerged:
The industry has spent two decades optimizing individual functions. Yet the molecule-to-market timeline persists. The path forward requires ruthless vendor discipline, cross-functional alignment, and honest communication during inevitable disruptions.
One of the most actionable data points from Day 2: A sponsor conducted a quality assessment of a Phase 1 eTMF. Results were sobering:
When this was shared with the room, multiple panelists nodded in recognition. One said: “That’s actually consistent with our experience.” Another: “We’re seeing 23-25% across the board. It’s become accepted.”
This consensus—that a ~25% defect rate is somehow industry norm—is alarming for two reasons:
The root causes are operational: manual processes, no real-time validation, no automated checks for missing docs/signatures/naming conventions, and fragmented ownership across sites/CRO/sponsor. Quality issues aren’t surfaced until QC review (months later).
The AI Solution: End-to-End Service
Consensus at SCOPE: AI-powered TMF solutions that automate filing, identify gaps, and maintain compliance are table stakes going forward.
Paulius Ojeras (Perceive Therapeutics Center) presented a real-world agentic implementation: automatic document filing; content checks (missing signatures, dates); gap identification; dynamic expected document lists (reads protocol, flags required documents when investigators are added); and autonomous document collection.
Critical caveat: 95% of AI vendors are selling tools. 5% are selling solutions. If the vendor doesn’t handle implementation, QC, and ongoing service, you’ll need to hire staff to manage it—negating ROI.
Most CRO forecasts don’t account for staggered site startup, variable enrollment by geography, seasonality, regulatory delays, or protocol complexity. They’re often simple linear projections.
The Forecasting Framework
Best practice involves scenario modeling: base case (conservative, realistic), optimistic case (top quartile recruitment), and worst case (30% slower than forecast). This forces early contingency planning.
Tools like Proof Pilot now automate this analysis, but require human judgment about your population, sites, and competitive landscape.
Real-World Impact
Accurate enrollment forecasting upfront prevents budget surprises in Year 2. If you discover enrollment is slower than expected in Month 12, you have time to course-correct. If you discover it in Month 24, you’re in crisis mode. Budget surprises are almost always traceable to forecast failures in Month 3.
Organizations with 3+ concurrent studies face vendor fragmentation that creates burden on sites and teams. Tricia Buchheit (Director, Patient Recruitment, Alnylam) and Jenn Curry (Head of Patient Engagement, Biogen) presented the challenge at different scales.
The common site feedback: “We need ONE place to log in. Not 20 vendor portals.”
The Standardization Strategy
The solution isn’t “use one vendor for everything.” It’s “standardize what sites interact with”:
Why: Sites feel confidence from consistency; training burden reduces; patient experience improves.
The Flexibility Tension
Standardize the HOW (tools, workflows). Vary the WHAT (patient experience, visit cadence) based on regulatory/protocol requirements. Jen Curry: “Standardization gives us the bandwidth to be flexible on what matters.”
Medical monitors spend 40-50% of their time NOT doing medical review—finding data, calling people, raising tickets, reconciling conflicting sources. They should be reviewing for safety/efficacy signals.
Solution: AI agents that present the 5 priority items that need review today, removing the data-hunting equation. Impact: 40% efficiency gain and better signal detection.
Before building agentic AI, establish a “knowledge fabric”—unified data architecture that brings together EDC, labs, ePRO, wearables, PV, and enrollment data, with proper governance and metadata. Biogen identified this as a company-wide priority because “dirty data” is pharma’s #1 barrier to AI adoption.
Key insight: Most organizations are skipping foundational data work and trying to build agentic solutions on fragmented data. It won’t work.
Angela Luca (Biogen) articulated where AI is working vs. aspirational:
Where Adoption is Fastest
Adoption velocity is fastest in study design and startup (lower stakes, faster ROI, regulatory not involved). Adoption stalls in execution and regulatory submission (higher stakes, regulatory implications, sites and patients involved).
Implication: Start with design/startup use cases, not execution.
The Organizational Readiness Bottleneck
Technology readiness ≠ organizational readiness. Blockers: fear of job displacement, muscle memory, lack of experimentation culture. Solution: “Citizen AI”—empower frontline staff to experiment with AI for their own pain points. When 50% of employees shift from “doers” to “architects,” that’s when you get efficiency and value.
Paulius Ojeras (VP, Clinical Operations, Perceive Biotherapeutics) shared a compelling case study of agentic TMF automation. The journey illustrates both the opportunity and the execution complexity.
Why TMF as the First Use Case?
When Perceive Therapeutics Center separated from a CRO, they faced a backlog of documents and known quality issues in the ETMF. They considered multiple automation opportunities:
Why did they pick TMF? Four factors:
The Pilot: Phase 1 eTMF Audit
Perceive Therapeutics asked their AI vendor to run a quality assessment on a Phase 1 eTMF. Results:
This benchmark—that 25% defect rate is apparently “normal”—was shocking. The vendor’s recommendation: AI can improve this to 25% better overall (so ~18-19% defect rate). Still not perfect, but meaningful improvement.
The Full Agentic Solution
The vendor implemented a complete agentic TMF system:
What it does:
Operational result: Documents flow end-to-end with minimal human intervention. Quality improves. Audit trails are complete.
The Critical Lesson: End-to-End Service vs. Tool
Paulius emphasized a crucial distinction that emerged from SCOPE: 95% of AI vendors are selling tools. 5% are selling solutions.
The difference:
Tool: “Here’s software. You implement it, manage it, troubleshoot it. You’re responsible for ROI.”
Solution: “Here’s the software + our implementation team + our QC + our ongoing service. You get the outcome. We handle the work.”
For small biotech, the tool model is economically unfeasible. You’d have to hire staff to manage the tool, negating ROI. This is why end-to-end service is critical.
Vendor Evaluation: The Hard Questions
When evaluating an agentic AI vendor, Paulius recommended asking:
Future Roadmap
Perceive Biotherapeutics is expanding agentic AI to:
Why this progression makes sense: Each use case builds on the previous success. TMF proved agentic AI works in their organization. Now they’re scaling to other operational areas.
Rather than bring PV in at protocol finalization, integrate early into study startup:
Result: Sites feel prepared; safety signals detected earlier; CRAs understand the “why” behind queries.
Real Example: Education vs. Correction
Beam Therapeutics discovered commercial teams were misclassifying mild events as “serious” because patients were hospitalized (for routine care, not safety). Rather than issue corrective queries, PV + operations created a retraining program. Sites understood the distinction; misclassification stopped.
Statistics + Operations Partnership
Biostatisticians can paint narratives from data that regulatory understands. Best practices: Include stats in database design, use real-world evidence early, visualize signals, hold monthly cross-functional reviews (not functional silos).
Megan Sniecinski (COO, Praxis Precision Medicine) presented the essential tremor trial that became a masterclass in patient-centric protocol design.
The disease: Essential tremor impacts 7 million people in the US. Only 1 drug is indicated for treatment (approved 50 years ago on 9 patients). Patients have few options.
The problem: In Phase 2b, Praxis discovered that eligible patients couldn’t participate because:
The solution: Design Phase 3 to bring the trial to the patient.
The Planning Session: Everything Hinges on This
Megan emphasized: The most important decision was the one-week planning session with all partners before execution.
Who attended?
What they did:
Why this mattered: This upfront planning allowed agility during execution. Everyone knew the playbook. When issues arose, the team could respond fast because they’d already talked about contingencies.
Execution Philosophy: “No Plan Survives First Contact”
Taylor Crush (Senior Director Patient Recruitment) emphasized a military principle: Plans are useful, but commitment to the plan is dangerous.
What they got right:
The flexibility story:
The protocol originally specified all home health visits. But when running, patients wanted:
Rather than rigidly enforce home visits, the team asked: “How do we maintain study integrity while being flexible on HOW visits happen?”
Result: Flexibility on logistics; rigidity on data quality and assessment protocols.
The Outcomes
Key Takeaways from the Praxis Model
One of the most actionable findings from SCOPE: When asked “Who negotiated skin-in-the-game (equity, risk-share, milestone-based) with a vendor in 2025?”, only 2 hands went up in a room of 100+.
Yet when panelists detailed their experiences, the room realized it’s far more common than they thought. The gap is awareness + willingness to ask.
Real-World Models
Model 1: Stock + Discount
Model 2: Private Placement Participation
Model 3: Milestone-Based Pricing
Model 4: KPI Risk-Share
The Psychological Shift
Matthew Failor made a critical observation: When a vendor has financial skin in the game, their daily behavior changes.
Instead of finding reasons to monetize scope creep, they help solve problems. Why? Because finishing faster means equity payoff or milestone achievement.
Matthew noted: “You’d be amazed how often this works. Even large vendors, when you structure it right, will participate. They believe in you too.”
Doug Shantz (Head Clinical Operations, AskBio—Bayer’s gene therapy company) faced a CEO question on his first day in July 2022: “What time is the patient being dosed in Cincinnati?”
He didn’t know. Small biotech trusts their teams. Large pharma demands real-time visibility.
The Integration Solution
Rather than assimilate AskBio into Bayer’s model, they kept separate legal entity status, negotiated what Bayer brings (data management, biostatistics, regulatory), protected what AskBio keeps (site relationships, scientific independence), and created governance (JOC for conflict resolution).
Early integration challenge: 13 Bayer people showed up uninvited to a call. Doug’s transparent response—”Don’t do that. Here’s how we’ll coordinate”—resolved it immediately. Both sides acknowledged this was ongoing change management, not a one-time event.
Startup Acquired by Larger Entity: The Alpheus Model
Ann-Marie Huistine (VP Clinical Operations, Alpheus—formerly large pharma, now startup-turned-enterprise) experienced the opposite scenario: startup acquired, CRO transitioned to a larger provider.
The problem: Sites noticed. Communication slowed. Responsiveness declined. Sites preferred the smaller vendor.
The workaround: Rather than fight the transition:
Lesson: Sites have choices. Sponsors don’t get to demand loyalty—they have to earn it through responsiveness and respect.
Jeremy Goldberg (investor perspective) provided context on why the industry is under such pressure:
2010: Cost to develop new medicine = $802 million
2025: $2.6 billion (3.24x increase in 15 years)
At the same time, revenue risk is increasing:
The math: Every month saved in development = millions in revenue protection and earlier market entry.
Yet the industry hasn’t cracked the code on actually saving months. Productivity gains have been consumed by complexity. We’re more productive, not faster.
The Bifurcation Reality
Scott MeGaffin (CEO, Adiso Therapeutics) noted: 2026 is the “year of the horse”—discipline momentum. M&A is selective. Capital flows to winners. Non-winners stall.
This creates pressure on small biotech to execute flawlessly. Execution failures are now existential.
Vendor Strategy:
Vendor Management:
Protocol Design:
Cross-Functional Alignment:
Enrollment Forecasting:
M&A Preparation (if acquiring):
Acquisition Integration:
Co-Development Governance:
AI Implementation:
Site Management:
SCOPE 2026 Day 2 revealed an industry at an inflection point. The narrative has shifted from “innovation in tools” to “discipline in strategy.”
The clinical research industry has spent two decades optimizing individual functions and adding tools. Yet the molecule-to-market timeline persists. The cost has tripled. And execution—not science—now fails more programs than any other factor.
The companies that will thrive in 2026 will be those that:
The good news: This is learnable. Jazz Pharmaceuticals, Daiichi Sankyo, AskBio, Praxis Precision Medicines, and others are already executing this playbook. Their successes—and hard-won failures—are the map for the rest of the industry.
The acceleration won’t come from another tool in the exhibit hall. It will come from teams that are ruthlessly aligned on what matters.
This executive intelligence brief was compiled from concurrent sessions at SCOPE 2026 Day 2 (February 3, 2026). It reflects themes, frameworks, and real-world examples shared by clinical operations leaders, regulatory professionals, and technology vendors. Distributed to clinical operations leaders, development leaders, regulatory professionals, and clinical strategy executives who attended or want consolidated insights from the conference.
February 4th sessions pivoted from M&A and vendor strategy to operational execution mechanisms: digital recruitment, cross-functional collaboration, and the integration of real-world evidence with clinical trial design. The unifying theme: Patient experience is now a compliance requirement, not a marketing concept.
Three critical insights emerged:
Published Evidence (Ludwig Maximilians University, Impact Factor 5.8)
An undisclosed recipient presented peer-reviewed data demonstrating that video ads are 40% more cost-effective on Facebook and 35% more cost-effective on Instagram compared to classical ads. TikTok requires video format and reaches a mean age of 21, compared to Facebook (~50) and Instagram (~30). Online-recruited cohorts are medically identical to site-recruited cohorts on depression severity (PHQ-9 scores), gender distribution, and age stratification.
New Mechanism for Reaching Vulnerable Populations
Four percent of online recruits were “under the radar” patients—highly depressed, socially isolated males with minimal healthcare contact who would never appear at traditional trial sites. This is the first published mechanism for reaching this vulnerable population and directly addresses health disparities in mental health trials.
Real-World Application: Tourette’s Syndrome Trial (Noema Pharma + AutoCruitment)
Jill Pellegrino, CEO of AutoCruitment, and Kristina Johnson, VP and Global Head of Clinical Development Operations at Noema Pharma AG, presented the trial rescue case.
Study Details: Phase 2b, randomized, placebo-controlled, double-blind. Target: 180 screens, 140 randomized. 60 sites across the US and Europe. Adults 18+. Required washout from all medications, including cannabis. BMI 18-35. Stable treatment status for comorbid psychiatric conditions (OCD, ADHD). Noema Pharma is a clinical-stage small CNS biotech with programs in Tourette’s Syndrome, pain, trigeminal neuralgia, and menopausal symptoms.
Initial Projection: 12-month enrollment (July 2024–July 2025). Reality by March 2025: trending toward late 2026 (14+ months behind).
AutoCruitment Deployment (March 2025):
Initial Results: 4 referrals per week (insufficient). Analytics revealed audience confusion (Lyme disease ↔ “tics”).
Rapid Optimization:
Site Support Services:
Final Outcomes:
AutoCruitment operates in 120 conditions across 38 countries.
Regulatory Requirements
ICH E6(R2) and E8(R1) mandate:
CREST Framework
Critical Requirements
A single, unified platform across recruitment → engagement → retention is essential. Global reach requires 80 countries, 60 languages. Technology fragmentation creates a “whitewater rafting” experience; a unified approach creates a “lazy river” experience. Must speak the patient’s language within the cultural context. Trusted companions are required across all geographies and ethnicities.
Premier Inc.
Myla Mahoney, Chief Growth Officer at Applied Sciences Premier Inc, presented the real-world evidence capabilities:
Northwell Health (Largest Private Employer in New York, 104,000 Employees)
Christina Brennan, MD, MBA, FACRP, Senior Vice President of Clinical Research at Northwell Health, presented two case studies:
Milk Allergy Investigation: Pediatrician observation → system-wide EMR validation → cross-reference with 25-year NIH-funded longitudinal studies → problem scope identification → intervention study design.
Lead Exposure Study: Physician observation → system-wide data analysis across all Northwell locations → clinical care changes throughout the entire health system.
Avera Health (Rural South Dakota, 300 Clinics, 38 Hospitals)
Amy Elliott, Ph.D., Chief Clinical Research Officer at Avera McKennan Hospital & University Health, described their innovation: Research data scientist embedded directly within the IT department (not research operations). Has security clearances and direct data warehouse access. Eliminates lag-time from traditional feeder systems. Enables real-time recruitment lists for time-sensitive studies (stroke trials). The Research Institute operates in the black, with approximately 100 FTEs. Transitioning to Epic with go-live 124 days from the session date.
Site Selection Enhancement
Premier Inc. data identifies high commercial potential hospitals. Clinical operations criteria + market access insights combined. Hospital formulary inclusion depends on: clinical/economic evidence + positive trial experience. Payer research informs key value drivers for P&T committees. Trial site selection considers post-approval uptake potential.
Evidence Generation
Medical affairs, clinical operations, and market access must collaborate from the outset of protocol conception. Real-world data informs: eligibility criteria, endpoint selection, site selection, diversity strategies.
Diversity Strategy
Timing Requirements
Ideal: 10 months before first patient in (minimum: 6–8 months). Reality: sometimes compressed to 2–3 months (inadequate).
Prerequisites for RFP
Team Selection Reality
Approximately 50% of bid defense teams don’t appear at kickoff. Focus on: escalation pathways, support structure, organizational culture (not just individuals). Request CVs for key roles; interview critical team members. Assess: How is the project manager supported? Attrition rate? Experience level commitment?
Red Flags
Vendor Management
Assess CRO’s vendor qualification process (not just relationships). Determine: Will CRO manage vendors, or will the sponsor hold contracts? Consider leveraging CROs with vendors (especially for small biotechs). Sponsor retains oversight of vendor outputs regardless of management structure.
Case Study: Difficult Integration Success
Teresa Devins, Vice President of Clinical Operations at Cognition Therapeutics (arrived early 2023), and Katie Rupert, Phd. Senior Project Manager from Premier Research, presented a partnership that succeeded under stress.
Situation: 8 sponsor PMs in a revolving door, 10+ CRO PMs, and knowledge loss. The study moved to a different CRO outside the US with no governance alignment. Three different countries are involved, each following different rules.
Turning Point: Senior sponsor leadership committed to a 2-week database lock turnaround (instead of typical months). CRO PM Victoria (representing the European CRO) signaled experience and authority: “Yeah, we can do that.”
Success Factors:
Outcome: All trials enrolled on time. All database locks on time.
CRO Selection Panel
Stephanie Pfister, VP Clinical Operations at Biohaven (experience across big pharma, small pharma, startups); Millie Schultz, Global Head of Clinical Operations from Galderma (dermatology focus; previously Takeda, Merck, Pfizer); and Lori Willis, Executive Director Neuroscience Business Unit at Premier Research (28 years tenure), addressed common concerns about team assignment and vendor surprises.
Problem Statement
Traditional full-service CRO: $180/hour CRA, $225/hour PM rates are unsustainable for small biotech. Full FTE hiring creates risk with funding uncertainty and workflow peaks/valleys.
Solution: Hybrid Model
Altimmune Inc. Results (4 Years)
Randy Brown, Head of Clinical Operations at Altimmune Inc., presented results over 4 years:
Randy Brown started in clinical operations at Eli Lilly and other mid-size companies before moving to smaller biotech.
Infrastructure Requirements
Staffing Philosophy
Staff to valleys, resource to peaks. Contractors dedicated solely to sponsor (no competing priorities). Guarantee hours to contractors; can deploy additional resources as needed. Mix evolves based on study phase and needs.
Control Advantages
Scalability Limitations
Model works well for US-based trials (~60 sites manageable). Phase 3 global expansion requires CRO partnership. Not suitable for: early phase with minimal activity; ex-US heavy trials without infrastructure.
Regulatory Drivers
ICH E6(R3) and E8(R1) mandate proportional, risk-based approaches. Compliance requirement, not just optimization opportunity.
Root Causes Addressed
RBQM Framework
Bo Maach-Moller, Head of Risk-Based Quality Management at Novo Nordisk, presented the framework:
AI Integration: Celonis Partnership
Novo Nordisk partnered with Celonis. AI trained on historical protocols in specific therapeutic areas. Draft protocol outline → AI suggests CTQs, risks, monitoring plan elements. Library-based approach (CTQ library, risk library, monitoring activity library). Human-in-loop validation required (clinical ops + medical science background). Saves hours to weeks of manual document review.
Study Hub Technology
Dynamic protocol outline development. Inclusion/exclusion criteria changes → immediate impact on recruitment/setup timelines. AI-powered predictions for trial size, duration, resource needs.
Change Management Barriers
Three Governance Models Presented
Sanofi (Top-Down):
Denise Gascard from Sanofi presented the approach: CEO mandate to become “AI-first biopharma company.” Governance established before implementation. Responsible AI framework developed. Internal LLMs deployed. Heavy investment in team training (time-intensive, often underestimated). The control tower maintains visibility. Several years of experience with AI in translation (proven savings).
Centessa Pharmaceuticals (Cautious, 125 people):
Scott Sawicki from Centessa described a cautious approach: Very risk-averse. Legal team required 2–3 months to negotiate MSA for EEG headband with AI analytics. Recently hired Head of IT with AI focus. Small company size enables alignment across IT/clinical ops. Not pushing AI full throttle; testing carefully.
Syneos Health (Client-Driven):
Max Ghez from Syneos Health (CRO) explained their client-driven approach: Listen to client needs; deploy AI tools to meet them. Some tools embedded in standard operations (CRA optimization, protocol analysis, pharmacovigilance). Some tools ad hoc based on project needs. Transparency with clients on what AI is used and how. Goal: AI becomes seamless, not separate discussion topic.
Site Perspective:
Jimmy from SCRS (site representative) emphasized that sites need education on appropriate AI use and must know what AI tools are being used on their behalf.
Trust & Fear Management
Fear Sources: job replacement concerns, confidentiality/data security, accuracy questions, regulatory uncertainty.
Trust Builders: transparency (disclose what AI is used, how, and why); education (“treat AI like summer intern”—review everything); augmentation messaging (AI makes best people better); demonstrated value (case studies); regulatory alignment (FDA guidance leaves door open).
Relationship Impact
Strengthens when: sites understand what AI tools are being used on their behalf; decisions made with AI are explained; AI enables faster, informed site selection; technology reduces site burden; consistent communication is maintained despite automation.
Weakens when: sites unaware of AI use in feasibility/selection; decisions made without explanation; technology fragmentation increases; human relationships replaced rather than augmented.
Cost & Savings Reality
AI implementation costs money upfront (validation, training, integration). Savings not yet transparent to sites/vendors. CRO hourly rates unlikely to decrease immediately. Efficiency gains: fewer hours × same rate = some savings. Long-term: 5+ years out before significant cost reductions materialize.
Regulatory Perspective
FDA wants AI; wants to understand how it’s used. Transparency in submissions about AI role in document preparation. Source data remains clinical trial data (not AI tools). Document automation/AI assistance disclosed in processes, not cited like academic sources.
Implementation Lessons
Start with quick wins, not “shiny new system.” Build trust through small successes before scaling. Cross-functional alignment essential (IT, clinical ops, compliance, legal all at table). Test 3–4 months before broader rollout. Communication at every layer critical.
Co-Development Partnerships
Kristine Koontz, VP of Global Clinical Operations at Daiichi Sankyo (17,000 employees, Japanese-based, 20+ years of co-development experience), described how difficult conversations about capability mismatches strengthen partnerships.
AskBio Gene Therapy Integration
Doug Schantz, Head of Clinical Operations at AskBio (now owned by Bayer, gene therapy company), faced a different challenge: integrating startup culture with large pharma processes. Maintained AskBio as separate legal entity, negotiated what Bayer contributes (data management, biostatistics, medical writing, regulatory), protected what AskBio keeps (site centricity, scientific independence, patient engagement), and created standing JOC for conflict resolution.
M&A Challenges
James from Jazz Pharmaceuticals (which conducts M&A at least once annually, focusing on neuroscience/oncology/sleep/epilepsy) presented the Chimerix case: acquired a late-stage asset with imminent FDA approval (announced March/April 2025, approval deadline August 2025). Decision: hands-off approach until August approval. Post-approval replan began after approval.
Lesson: You acquire for a reason. Disrupting success is counterproductive.
Cost Escalation & Market Realities
Jeremy Goldberg from Arsenal Capital Partners (investor perspective) provided financial context: 2010 cost to develop new medicine = $802 million (Tufts data); 2025 = $2.6 billion (3.24x increase in 15 years). Medicare negotiation (IRA) creates 5–10% revenue exposure per large pharma. Every month saved in development = millions in revenue protection. But the industry hasn’t cracked accelerating timelines.
AutoCruitment’s 255% enrollment acceleration in the Noema Pharma Tourette’s trial demonstrates that video-based digital ads are 40% more cost-effective than classical ads. More importantly, they reach vulnerable populations that traditional sites never see. Allocate meaningful budget to digital recruitment and measure cost-per-eligible-lead by platform and indication.
ICH E6(R2) and E8(R1) mandate patient voice in protocol development. Use CREST framework: Comprehensive creative → Real-world data → Evidence-based channels → Scalable platforms → Technology-enabled measurement. Implement unified platforms to eliminate technology fragmentation that burdens patients.
Premier Inc’s partnership with Northwell Health and Avera Health demonstrates that RWE integration accelerates post-approval uptake. Partner with health systems with embedded data science capability and direct data warehouse access. Involve medical affairs and market access in protocol development. Use RWE to inform eligibility criteria, endpoint selection, site selection, and diversity strategies.
Start RFP process at -8 to -10 months (minimum -6 months). Teresa Devins and Katie Rupert’s partnership at Cognition Therapeutics and Premier Research showed that transparency in change orders and shared accountability drive success. Require CRO to bring proposed team to bid defense; interview key members. Document governance, escalation paths, and vendor management approaches upfront.
Randy Brown’s model at Altimmune, Inc. achieved 40% cost savings vs. traditional CRO, near-zero turnover, and 100% on-time enrollment/database lock. Core FTEs (strategic functions) + 1099 contractors (specialized, time-bound work) + staffing partners (rapid scaling) works for US-focused mid-size biotech. Staff to valleys; resource to peaks.
Bo M’s RQBM framework at Novo Nordisk uses Celonis AI to suggest CTQs, risks, and monitoring elements from draft protocols—saving hours to weeks. Upfront investment in Critical to Quality identification reduces downstream protocol amendments and overall cycle time. Centralize monitoring to protect precious CRA resources.
Sanofi’s top-down mandate, Centessa’s cautious testing, and Syneos Health’s client-driven approach all demonstrate that governance must precede tools. Start with 1–2 high-impact use cases, not entire portfolios. Transparency with sites is critical: explain what AI is being used and why. Cost savings won’t materialize for 5+ years; don’t “nickel and dime” vendors/sites during transition.
The industry has spent 20 years adding tools and optimizing individual functions. Yet molecule-to-market timelines persist. Jeremy Goldberg’s analysis shows cost of development has tripled to $2.6 billion. Companies succeeding in 2026 are ruthlessly aligned on simplicity, transparency, and patient-centricity—not breakthrough innovation.
This executive intelligence brief was compiled from seven concurrent sessions at SCOPE 2026 Day 3 (February 4, 2026). It reflects themes, frameworks, and real-world examples shared by clinical operations leaders, regulatory professionals, and technology vendors. Distributed to clinical operations leaders, development leaders, regulatory professionals, and clinical strategy executives who attended or want consolidated insights from the conference.
As SCOPE 2026 entered its final day, the narrative shifted decisively away from technology novelty toward pragmatic, people-centered solutions. The message from the stage, the working groups, and the conversatons was unmistakable: the future of clinical research belongs to organizations that simplify operations, reduce unnecessary burden, and build trust through transparency.
The Flagship Working Group
“Simplify to Elevate: Designing Leaner, Smarter Clinical Protocols” brought cross-functional teams from Bristol Myers Squibb together to identify actionable ways to simplify protocols while preserving scientific integrity. This wasn’t a panel discussion—it was a collaborative workshop where participants rolled up their sleeves and explored three core focus areas:
Data Optimization
Identifying what’s essential and eliminating what’s not. Prioritize critical endpoints that drive decision-making. Remove data collection that doesn’t move the needle.
Reduce Burden
Craft lean protocols that are easier to conduct. Eliminate avoidable amendments. When protocols are complex, sites struggle, patients withdraw, timelines slip.
Smart Assessment Planning
Prioritize must-haves and eliminate noise. Reduce complexity while ensuring compliance. Ensure protocols that sites can execute effectively and patients want to participate in.
The working group’s core insight: Simplification must move from talking point to systematic, sustainable practice. Organizations that measure protocol complexity and intentionally reduce it see measurable improvements in enrollment, retention, and compliance.
Empirical Evidence: Quantifying the Impact
A major presentation by PwC and AbbVie presented data that changed the conversation. They developed a multi-dimensional, quantitative framework to measure protocol complexity and applied it to digitized data from thousands of clinical trials conducted over the past decade.
Using empirical models, they quantified how specific complexity dimensions directly influence enrollment speed and patient-initiated withdrawal. The data proved what operational leaders have long suspected: protocol complexity isn’t just an inconvenience—it’s a measurable constraint on trial success.
Their scenario-based analyses demonstrated that targeted protocol simplification can improve operational performance and support more efficient prospective trial design. This is actionable, not theoretical.
Implication for sponsors: You can measure protocol complexity. You can predict its impact on enrollment and retention before launch. You can optimize it prospectively rather than amending after sites struggle.
The breakfast presentation by ProPharma Group’s Shelby Stillwagon set the tone for Day 4: clinical trial success requires deliberate, systematic support for sites and patients. This isn’t an afterthought—it’s a core strategy. What Organizations Are Implementing
Specialized Roles Integrated into Site Teams
Not handing sites a protocol and expecting execution. Leading organizations embed specialized support roles within site operations—providing hands-on support in prescreening, recruitment, data entry, and remote study visits. This reduces site burden while improving data quality and patient experience.
Flexible, Scalable Resourcing
Site capacity needs to be flexible. Organizations are moving away from fixed staffing models toward flexible, demand-based resourcing that scales to actual workload. This allows sites to maintain optimal staffing without creating waste during low-activity periods.
Global Scalability with Local Expertise
Patient engagement and site operations look different across geographies. Effective models combine global consistency with local expertise—ensuring that support is standardized in process but customized in execution.
Measurable Outcomes
The ultimate goal isn’t activity—it’s improvement in site performance, operational efficiency, patient engagement, and retention. Organizations succeeding at this are building operational metrics that track what actually drives trial success.
A critical Day 4 priority emerged across multiple sessions: data minimization. Leaders argued for prioritizing critical endpoints to reduce patient burden and operational complexity. This represents a fundamental mindset shift in clinical research. The traditional approach: collect everything, analyze later. The emerging approach: collect only what you need to make decisions, minimize patient burden, reduce operational complexity.
The Logic Is Straightforward
Data minimization isn’t about cutting corners. It’s about strategic focus on what matters—improving patient experience and operational efficiency simultaneously.
The Competitive Advantage: Organizations that optimize data collection early gain months of acceleration across the entire trial lifecycle. This compounds from enrollment through final readout.
A major panel discussion brought sponsors, sites, patients, and technologists together to examine responsible integration of AI. The conversation moved beyond “how” (the technology) to “why” (the business case) and “who” (all stakeholders).Key Themes That Emerged
Move Beyond Hype Into Frameworks
AI must move from “interesting innovation” into regulatory frameworks that sponsors and regulators can trust for clinical outcome assessments. Responsibility matters more than novelty.
Balance Innovation, Privacy, and Regulatory Concerns
The path forward requires practical implementation of AI tools that protect patient data, comply with regulations, and actually improve outcomes. This requires governance, not just technology.
Patient-Centric Transparency
Patients want to understand what AI is being used, why, and how it affects them. Transparency builds trust. Organizations hiding AI implementation erode confidence.
Industry Best Practices for Data Integrity
AI tools can streamline operations, enhance data quality, and improve patient engagement—but only if implemented with clear governance and oversight. Data integrity is non-negotiable.The consensus: AI is not a magic wand. It’s a tool that works best when responsibly implemented with oversight from sponsors, regulators, sites, and patient advocates. The organizations winning at AI integration are those treating it as a governance problem, not a technology problem.
CVS Healthspire presented data showing that 85% of clinical trials fail to recruit or retain enough participants. They demonstrated how robust pharmacy and medical claims data—enhanced by payer insights—can be strategically used to transform recruitment feasibility.
Site Input to DCT Elements: The Missing Piece
A panel led by the Decentralized Trials & Research Alliance (DTRA) highlighted a critical gap: sites often don’t learn that decentralized clinical trial (DCT) elements are included until the investigator meeting or site initiation meeting. By then, they’re not set up to succeed.
Two initiative teams are systematically changing this by collecting retrospective data on DCT use and creating structured pathways to gather prospective input from sites during protocol development. The aim: increase collaboration and insight to optimize best-fit DCT element use and implementation.
The insight: Site input in protocol design isn’t optional. It’s essential to ensuring that innovative trial designs actually work operationally. Sites are experts in their patient populations and operational constraints. They should be partners in design, not implementers of others’ decisions.
Meeting Sites Where They Are
Partners highlighted sessions on “Meeting Sites Where They Are,” emphasizing reducing site burden through connected technology and aligned workflows. The message: innovative technology is only valuable if it fits naturally into site operations and reduces, not increases, their workload.
Bristol Myers Squibb presented an AI/ML framework that operationalizes equity in clinical trials. This isn’t just an ethical imperative—it’s an operational strategy for better science.
The Framework
The outcome: Organizations using AI responsibly to improve diversity end up with more generalizable results, better science, and broader evidence. Equity isn’t a constraint on efficiency—it’s a lever for it.
IQVIA presented innovation in clinical trial financial management—demonstrating how AI can streamline payment automation and improve site outcomes.
The Operational Reality
When sites are paid accurately and on time, they’re more engaged. When financial processes are automated, sponsors can redirect resources to strategic activities. When payment workflows are transparent, sites have confidence in partnerships.
This isn’t exciting innovation. It’s operational discipline. But operational discipline is what drives trial success.
Day 4 ended with the “Closing Ceremony” booth crawl—a SCOPE tradition where the exhibit hall transformed into a celebration of the week’s “triumph and teamwork.” The winners focused on technologies that solved real problems: those reducing site burden through connected workflows, improving patient experience, and enabling smarter, faster decisions.
The Best of Show winners weren’t the flashiest innovations—they were the ones that worked. That reduced complexity. That enabled execution. That put patients and sites at the center.
The signal: Innovation is only valuable if it solves real operational problems. The clinical research industry is moving past “interesting technology” toward “functional, integrated solutions that enable execution.”
This executive intelligence brief was compiled from concurrent sessions at SCOPE 2026 Day 4 (February 5, 2026). It reflects themes, frameworks, and real-world examples shared by clinical operations leaders, regulatory professionals, and technology vendors. Distributed to clinical operations leaders, development leaders, regulatory professionals, and clinical strategy executives who attended or want consolidated insights from the conference.
Clinovo’s workforce solutions help clinical research teams run faster, smarter, and more compliant trials, delivering outcomes investors, regulators, and patients can trust.
At Clinovo, we deliver expert-led technology and workforce optimization solutions that accelerate clinical development with targeted precision. Eliminate barriers, achieve measurable ROI, and bring life-changing therapies to market faster.
Quick Links
Contact Us
Visit Us
Copyright 2025 Clinovo | All Rights Reserved
