Q&A with Marcia Blackmoore | Building Smarter, Faster CDMOs: A Data-First Strategy for Advanced Therapies

Originally published in Contract Pharma’s Pharma Matters Q&A with L7 Informatics.

 

QUESTION 1:

L7 Informatics emphasizes a “data-first” approach to cell and gene therapy manufacturing. What does that mean in practice, and why is it particularly important for CDMOs working in this complex space?

Marcia Blackmoore: 

When we say “data-first,” we mean building your processes with the requisite data model in mind from the very beginning. This approach is more efficient than the rework involved in trying to stitch it together later. In cell and gene therapy, the work is too complex and high-stakes to rely on manual documentation, siloed systems, or after-the-fact reconciliation.

For CDMOs, this becomes even more critical. You’re working across multiple clients, products, and modalities—often with inconsistent source systems and tight timelines. If data is not reliable, contextualized, and accessible at every step, it slows down everything: tech transfer, batch release, investigations, quality review, you name it.

At L7, we help CDMOs design digital workflows with structured, contextualized data baked in from the start. Our platform, L7|ESP®, gives teams the tools to standardize manufacturing and QC/QA processes, automate process execution (including data capture from instruments, equipment, and distributed control systems such as DeltaV), and keep everything traceable and audit-ready, thereby enabling on-time batch release.

It’s about creating a foundation that scales, supports flexibility, and enables teams to make faster and better decisions. That’s what a data-first approach should look like.

 

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QUESTION 2:

CDMOs often face the challenge of bridging gaps between R&D, clinical, and commercial stages. How does L7’s unified platform help streamline these transitions in a highly regulated environment?

Marcia Blackmoore: 

The handoff between R&D, clinical, and commercial is where many organizations stumble—especially in cell and gene therapy, where every stage is tightly interconnected but often managed in disparate systems by different organizations.

L7|ESP offers a unified platform that can work across these boundaries. Instead of reinventing the wheel at every phase or translating from paper and transferring between systems at each phase of the drug development lifecycle or at each touchpoint, a single digital process can be defined and carried forward, while preserving context, standards, and controls.

This is invaluable in regulated environments, where traceability can be lost or errors can be introduced at each transition point. In addition, this approach can dramatically reduce the duration of the tech transfer and ultimately, time to market. With L7, the data isn’t just there—it’s structured, version-controlled, and compliant by design.

 

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QUESTION 3:

In your collaboration with Cellipont, what were some of the key pain points they faced around data integration and scalability—and how did L7 help address them?

Marcia Blackmoore: 

Cellipont was a greenfield site that embraced the digital-first mindset with an integrated data platform. 

When we started working with Cellipont, they were preparing to scale quickly and needed a digital backbone that could grow with them. We utilized L7’s pre-built, cell therapy-focused manufacturing processes. These composable digital workflows can adapt to different client needs while maintaining consistency in core processes and data models. Using this approach, we were able to deliver an EBR and inventory management system that is both flexible and scalable within a few months.

 

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QUESTION 4:

Real-time data orchestration and contextualization are core capabilities of your platform. How do these features directly impact product quality, regulatory compliance, and manufacturing efficiency for CDMOs?

Marcia Blackmoore: 

Real-time orchestration and contextualization are the foundation of L7|ESP, which is precisely what enables CDMOs to transition from a reactive to a proactive approach. When systems are connected and your data carries full context—who did what, when, and under what conditions—CDMOs can track material usage, environmental monitoring trends, QC results, manufacturing progress, and batch status in real-time.

 

From a product quality and compliance perspective, this means you can (pro)actively detect and respond to potential issues rather than discovering them days or weeks later during a paper-based review. In addition, L7|ESP’s ability to organize data into one knowledge graph can enable far more efficient deviation investigations. 

In terms of manufacturing efficiency, orchestration eliminates the need for manual handoffs and status checks. The system drives the process, automates the routine, and flags the exceptions.

That level of visibility and control helps CDMOs deliver more consistent outcomes, accelerate timelines, and build confidence with both clients and regulators.

 

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QUESTION 5:

What are the most common data and digital infrastructure challenges you see among CDMOs, especially those entering or expanding in the cell and gene therapy market?

Marcia Blackmoore: 

One of the biggest challenges I see—especially with CDMOs entering or expanding in cell and gene therapy—are the siloed systems and the reliance on paper-based processes, even while the technology itself is on the cutting edge of innovation. 

Organizations attempt to scale without a digital foundation that can keep up. Many are still relying on paper, Excel, or disconnected point solutions to run highly complex and variable processes. 

Another issue is fragmented infrastructure. There might be an MES system, a LIMS system, and perhaps a QMS, but none of which talk to each other. Teams, therefore, reconcile data manually, which slows down tech transfers, delays batch release, and introduces risk.

L7|ESP can be layered on top of existing systems to orchestrate workflows, unify data, and bring structure without the need to replace legacy systems. L7|ESP  is able to integrate these siloed systems or fully replace existing systems. 

 

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QUESTION 6:

From your perspective, how can digital platforms like L7|ESP contribute to shortening time-to-market for advanced therapies without compromising on quality or traceability?

Marcia Blackmoore: 

One of the major bottlenecks in the product development lifecycle is the tech transfer process. L7|ESP enables digitalization and transfer from a library of pre-built recipes, unit operations, and methods. Those pre-built units can be dragged and dropped from L7|HUB® and configured for new customers or products, thereby decreasing tech transfer execution times and, by extension, time-to-market vs. paper-based tech transfers. Tech transfer times can be further accelerated if both the customer (sending party) and the CDMO (receiving party) utilize L7|ESP.

 

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QUESTION 7:

Looking ahead, how is L7 evolving its solutions to support the next wave of CDMO innovation—whether that’s personalized medicine, decentralized manufacturing, or AI-driven optimization?

Marcia Blackmoore: 

L7|HUB®, Reusable Content, Knowledge Graph (L7|INTELLIGENCE®), AI.

The next wave of CDMO innovation—personalized medicine, decentralized manufacturing, and AI-driven optimization—requires a solid data foundation and the ability to be nimble to be successful. 

Using L7|HUB and the pre-built content library, we can enable accelerated scale-up and tech transfers. L7|ESP orchestrates workflows and captures data at every step—with structure, context, and traceability built in. That means CDMOs can create AI-ready data that can be utilized for everything from predictive modeling to real-time quality control.

We’re also expanding our knowledge graph and data product capabilities, enabling customers to move beyond manual reviews and static reports toward systems that can reason, adapt, and help teams make smarter decisions more quickly. 

The promise of this next era isn’t just speed or automation—it’s intelligence. And that comes from treating data as a strategic asset from day one.