Biorce raises $52M for AI clinical trials

Biorce raises $52M Series A to roll out Aika, its AI-native clinical trial platform, reducing amendments, speeding setup, and expanding to the US via Austin.

Biorce has secured a $52 million Series A to accelerate the global rollout of Aika, its AI-native platform built to streamline clinical trial design and execution. From a Global Martech Alliance lens, this funding round is a clear signal that “protocol intelligence” is becoming a must-have layer in modern life-sciences stacks—not a nice-to-have experiment.​

Funding round and why it matters

Barcelona-based Biorce closed a $52 million Series A round to meet rising demand, expand internationally, grow its team, and keep advancing its AI platform for clinical trials. The round includes new investment from DST Global Partners, with existing investors Norrsken VC and YZR Capital increasing participation, alongside Mustard Seed Maze, plus angel investors including Arthur Mensch, Albert Nieto, Paulo Rosado, and Nik Storonsky. After this raise, Biorce’s total funding has surpassed $60 million.​

From our Global Martech Alliance viewpoint, what’s notable is not only the size of the round—it’s the “why now.” Clinical development is under constant pressure to compress timelines while maintaining rigor, documentation quality, and patient safety, and that combination creates a perfect opening for AI systems that can make trial planning faster and easier to defend. In practical terms, the companies that can connect automation with governance-ready evidence (not just “suggestions”) will shape procurement decisions across pharma, biotech, and CROs over the next cycle.​

This is also a strong story about category clarity. Biorce is positioning itself around clinical trial design and execution—where a large portion of delays and cost blowouts are created—rather than building another analytics layer that sits downstream and reports problems after they happen. As marketing and growth teams know well, the best platform narratives don’t start with features; they start with eliminating expensive “rework loops,” and clinical trials are full of them.​

The costly reality of protocol amendments

Biorce’s core bet is that better upfront design reduces downstream chaos, and in clinical trials that chaos often shows up as protocol amendments. In traditional trial models, protocol amendments can pause patient recruitment for an average of six weeks and add between €500,000 and €1 million in cost per amendment. Those aren’t abstract line items: six weeks can mean lost recruitment momentum, site re-training, contract adjustments, additional oversight, and missed internal milestones that ripple into later-stage programs.​

A key driver behind repeated amendments is the difficulty teams face when they need to clearly justify trial design decisions to regulators like the FDA and EMA. When a rationale is incomplete, inconsistent, or poorly documented, review cycles can stretch, questions multiply, and sponsors can find themselves revising protocols midstream—exactly when change is most expensive. The operational reality is that even “small” updates (inclusion/exclusion criteria tweaks, endpoints, visit schedules, safety monitoring changes) can translate into vendor renegotiations, data collection updates, and site burden that slows execution.​

From a martech-style operating model perspective, the pattern looks familiar: teams move fast early, documentation lags, stakeholders disagree late, and then a second round of work becomes unavoidable. The difference is that in life sciences, the cost of rework isn’t just budget and timelines—it can delay patient access to therapies and reduce the probability of success across a portfolio. That’s why platforms that reduce ambiguity and increase traceability tend to win enterprise adoption: they protect the organization from its own complexity.

This is also where “AI” can easily fail if implemented poorly. If a model outputs recommendations but can’t show reasoning in a regulator-ready way, teams can’t use it confidently in submissions, and the tool becomes a side experiment rather than a system of record. In other words: explainability isn’t a compliance checkbox; it’s a product requirement that determines whether AI actually gets deployed at scale.

What Aika is (and what it’s designed to change)

Biorce is building AI infrastructure for clinical trials, with Aika at the center of its approach. Aika is positioned as an AI-native platform designed to reduce clinical trial preparation timelines and limit protocol amendments to support faster development of new therapies. That focus is important because it targets the earliest, highest-leverage phases of a trial—when design choices set the trajectory for feasibility, recruitment, operations, and regulatory review.​

According to Biorce’s CEO Pedro Coelho, the mission is to make trials “faster, more reliable, and more accessible,” emphasizing that delays and inefficiencies ultimately cost lives. This message resonates because it connects workflow innovation with real-world outcomes, not just productivity metrics. It also frames the platform as a reliability engine: reducing avoidable errors, clarifying the “why” behind decisions, and keeping teams aligned before the trial is underway.​

Aika is built on a dataset of approximately one million clinical trials, and it’s designed to anticipate risks, reduce errors, and limit the need for protocol changes. The platform is meant to support pharma companies, biotech firms, and CROs as they design trials more efficiently while maintaining scientific standards and patient safety. In GMA terms, that’s a classic “decision intelligence” promise: compress the time it takes to go from research inputs to a defendable, auditable plan—without removing clinical experts from the loop.

One practical way to understand Aika is as a protocol intelligence layer that aims to reduce blind spots before they become costly. In many organizations, teams already have data, templates, and institutional knowledge, but it’s scattered across documents, vendor portals, prior study reports, and individual experience. A platform that can bring those inputs into a structured workflow—and keep a clear chain of justification—doesn’t just speed up drafting; it can reduce stakeholder friction and the number of “late surprises” that trigger amendments.​

Biorce also emphasizes therapy-agnostic scaling: Aika is already being used across therapeutic areas including oncology, neurology, and rare diseases, and the company highlights that the platform can be applied across a wide range of clinical programs. That matters for enterprise adoption because most sponsors aren’t running one trial; they’re running portfolios, and portfolio value comes from repeatability, consistency, and governance across programs. When a tool is narrow, it stays in one department; when it’s flexible and standardized, it becomes a platform that procurement can justify and leadership can scale.​

From a platform adoption standpoint, Biorce’s narrative aligns with what we see across martech and enterprise software: the tools that survive procurement are the ones that reduce cycle time, reduce rework, and increase confidence in decision-making. In clinical trials, that “confidence” often has a name: regulator-ready documentation. If Aika can help teams defend decisions earlier—with clear evidence and consistency—it can reduce the back-and-forth that delays launches and increases operating costs.

Global rollout, US expansion, and what’s next

Biorce plans to expand its workforce and open a development and R&D hub in Austin, Texas, to support its activities in the US. This is a strategic move because US market entry in clinical research isn’t just about selling—it’s about aligning product design to regulatory expectations, enterprise security needs, and the day-to-day workflows of trial teams operating at scale. A US hub also signals that Biorce expects product iteration to accelerate as the platform gets embedded into higher-stakes programs and larger organizations.​

The roadmap described for early 2026 includes strengthening Aika’s protocol intelligence capabilities and rolling out additional modules for contract management, negotiation, budget planning, and operational execution. That expansion is significant because it pushes the platform beyond “design support” into operational infrastructure—where trials often encounter delays due to fragmented tools and handoffs. Put simply: trial success isn’t only determined by protocol design; it’s determined by whether the operating model can execute that design without constant midstream changes.​

From a Global Martech Alliance perspective, this modular roadmap looks like a deliberate shift toward an end-to-end platform strategy. If Biorce can connect protocol decisions to contracts, budgets, and execution, teams gain a single thread of accountability across the lifecycle—from rationale to operational reality. That’s exactly how modern enterprise platforms win: they reduce tool sprawl, standardize workflows, and enable cross-functional alignment (clinical, regulatory, operations, finance, procurement) around the same source of truth.​

It also makes the go-to-market story more compelling. When a product only solves one part of a workflow, buyers often treat it like a point solution; when it expands into adjacent “must-run” processes (contracts, budgeting, negotiation), it becomes harder to replace and easier to justify as a platform investment. For clinical teams, that can translate to smoother trial startup, fewer delays caused by operational bottlenecks, and a better ability to plan capacity across sites and vendors.​

What marketers and growth teams can learn

Even though this is a health AI story, it offers a useful blueprint for how AI platforms should be built and sold in any regulated, high-stakes domain. The winning pattern is: reduce cycle time, reduce rework, and make outcomes easier to defend—internally and externally. In martech, “defendability” can mean attribution logic and data governance; in clinical trials, it means clear rationale and documentation for regulators.​

Here are a few takeaways that matter for product, marketing, and revenue teams watching this category:

• Position AI around “avoidable rework,” not abstract intelligence: Biorce anchors the problem in protocol amendments that add weeks and significant cost.​
• Treat explainability as a growth lever: In regulated environments, the best feature is often the one that enables adoption—clear documentation, traceable outputs, and confidence in review processes.​
• Build for portfolios, not pilots: Therapy-agnostic usage across oncology, neurology, and rare diseases supports a scale story rather than a single-department use case.​
• Expand into adjacent workflows where friction lives: Contracts, budgets, negotiation, and operational execution are where “good designs” often get delayed or diluted.​

For enterprises evaluating tools like Aika, the practical evaluation criteria should go beyond “accuracy” and focus on adoption reality:

• Can teams integrate it without heavy process disruption?
• Does it create regulator-ready justification without adding documentation burden?
• Does it reduce the number of handoffs between clinical design, regulatory, and operations?
• Does it make trial planning faster while keeping experts in control?

If Biorce executes on these points, the $52M round is less about one company’s momentum and more about a broader shift: clinical trial design is becoming a software-defined discipline, and AI systems are moving from optional assistants to foundational infrastructure.​