Advancing Genomic Medicine Through Next-Generation Delivery Technologies

As genomic medicine advances beyond early proof-of-concept therapies, the field is facing an increasingly urgent challenge: delivery, not payload design, is now the primary bottleneck.

 

While genetic engineering tools have become more sophisticated, the ability to deliver them safely, reproducibly, and at scale remains problematic—particularly as developers move into complex indications, new tissues, and broader patient populations.

 

This challenge is the focus of a new collaboration between Cytiva and the San Raffaele Telethon Institute for Gene Therapy, established as part of the Danaher Beacons framework. Within this long‑term initiative, delivery is being addressed as a systems‑level problem, spanning biology, formulation science, process design, automation, and scalability, and guided by a deliberate translational roadmap.

In this article, Dr. Daria Donati, chief scientific officer of genomic medicine at Cytiva, outlines why delivery now defines the pace of the field, how lipid nanoparticles (LNPs) are being re‑engineered as a complementary delivery modality, and how collaboration can help to design genomic medicine platforms that are not only scientifically robust, but also scalable, reproducible, and economically sustainable.

The rate-limiting step in genomic medicine

Why has delivery emerged as the primary bottleneck in advancing genomic medicine?

 

Over the past decade, the pace of innovation in genetic payloads has been extraordinary. From gene addition to refined editing systems, developers now have a broad and powerful toolkit. Yet, according to Donati, delivery has not evolved in parallel, and that gap is now defining what makes it into the clinic.

 

“Delivery is no longer only a biological challenge; it has become a systems problem that spans tissue biology, engineering constraints, safety margins, and manufacturability,” she said.

 

“As programs move into more complex indications and larger patient populations, those constraints become the rate-limiting step,” she added. Reproducibility, cost, and scalability become inseparable from biology.

 

This reality is reshaping how delivery platforms are designed. Rather than treating manufacturing as a downstream consideration, Donati emphasized the importance of translational approaches that integrate clinical relevance and scalability from the outset.

 

What this means for developers:

• Payload innovation alone is no longer sufficient to advance programs.
• Delivery challenges cut across biology, engineering, safety, and manufacturing.
• Platforms must be designed for clinical and industrial relevance from the beginning.

Expanding the delivery toolbox

As genomic medicine tackles more complex indications, where do current viral vector platforms fall short, and what makes LNPs a compelling alternative?

 

“Viral vectors—including lentiviral vectors—have enabled some of the most transformative therapies on the market and remain essential,” Donati stated.

 

However, no single modality can meet every biological and commercial requirement—particularly as genomic medicine pushes into more complex editing strategies and larger patient populations.

 

Donati pointed to manufacturing complexity, scalability, and process consistency as growing pain points for viral vectors. These challenges are not insurmountable, but they do limit flexibility and speed in some settings. Cytiva is actively working to address these challenges and simplifying the process for viral vectors as well.

“LNPs are compelling as a complementary platform because they offer chemical programmability, modularity across payload types, and a manufacturing profile that can be more readily aligned with standardized, scalable workflows,” she added.

Expanding the delivery toolbox will enable developers to choose the best solution for the biology and clinical need.

The emphasis is not on replacing viral vectors, but on enabling informed modality selection that balances biology with long-term development realities.

 

Why modality choice matters more than ever:

• Viral vectors remain powerful but have limitations in scalability and consistency.
• LNPs offer modularity and manufacturing advantages for certain use cases.
• Early consideration of manufacturability can prevent downstream bottlenecks. 

Re-engineering LNPs for gene therapy applications

What specific innovations are needed to re-engineer LNPs for effective and safe gene therapy delivery?

 

LNPs are well established for nucleic acid delivery, but gene therapy places a higher bar on performance.

“A key challenge for the whole field is tissue targeting beyond the liver. However, gene therapy delivery overall raises the bar for safety, functional delivery, and dose efficiency,” Donati said. 

 

Donati noted that this work is not starting from scratch. The collaboration builds on mature, programmable lipid platforms and validated ionizable lipid libraries already used both ex vivo and in vivo.

 

“The innovation focus is therefore systematic and translational: advancing lipid chemistry and formulation, improving the balance of potency and tolerability, refining targeting strategies (active and passive), and increasing functional delivery efficiency in ways that remain compatible with scalable manufacturing,” Donati stated.

 

This translational mindset—optimizing chemistry, formulation, and targeting while preserving industrial feasibility—is central to making LNP-based gene therapies viable at scale.

 

Key priorities for next-generation LNP design:

• Improved tissue targeting beyond the liver.
• Careful balancing of potency, tolerability, and safety margins.
• Compatibility with scalable, GMP-aligned manufacturing workflows. 

A stepwise roadmap for increasing translational complexity

Your roadmap progresses from ex vivo editing to central nervous system (CNS) delivery to in vivo stem cell modification. What factors guided this progression, and which breakthroughs will determine clinical feasibility at each stage?

 

Donati explained that the roadmap progresses deliberately from ex vivo editing to CNS delivery, and ultimately to in vivo stem cell modification. Each step represents a marked increase in biological and translational complexity.

 

Ex vivo editing offers a controlled environment with established clinical and manufacturing precedents. CNS delivery introduces new challenges, including biological barriers and heightened safety sensitivity, but addresses a substantial unmet need. In vivo cell modification pushes even further, with exceptional demands on specificity, durability, and safety.

 

“Advancing in stages ensures each step is supported by robust data and scalable platforms, rather than bespoke solutions,” Donati said.

 

“Clinically, feasibility at each stage will be defined by the same critical milestones: reliable delivery to the right cells, predictable safety margins, durability of effect, and a process that can be reproduced and scaled.”

 

Why staged progression matters:

• Each phase increases biological and translational complexity.
• Controlled early steps reduce risk and generate high-quality data.
• Scalability and reproducibility are non-negotiable at every stage.

 

LNPs and the challenge of CNS delivery

How do you see next-generation LNP platforms addressing CNS delivery challenges where viral and other non-viral systems have struggled?

 

CNS delivery remains one of the toughest challenges in genomic medicine, regardless of modality, Donati said. Biological barriers, narrow safety margins, and dosing constraints have limited success across both viral and non-viral systems.

 

The strength of LNPs lies in their chemical tunability. “You can systematically adjust formulation parameters—composition, surface properties, and targeting features—without necessarily changing the underlying manufacturing architecture,” Donati explained.

 

Rather than relying on a single breakthrough, Donati anticipates progress through iterative, data-driven optimization: “I don’t think there will be a single ‘silver bullet’ breakthrough. Progress will come from incremental, data-driven optimization—building a platform that steadily improves targeting and functional delivery while staying compatible with scalability, process control, and regulatory expectations.”

 

Practical implications for CNS programs:

• CNS delivery challenges are universal across modalities.
• Incremental optimization is more realistic than disruptive leaps.
• Manufacturing continuity supports regulatory and clinical translation. 

Designing for scalability, automation, and consistency

How will this collaboration tackle the scalability, automation, and process consistency challenges that have limited advanced delivery systems?

 

One of the defining lessons from first-generation advanced therapies is that scalability cannot be retrofitted. Donati stressed that automation and process consistency must be embedded from the earliest stages of platform design: “Scalability and consistency need to be design criteria from day one, not ‘phase-two problems.’”

 

The collaboration integrates academic translational expertise with Cytiva’s strengths in manufacturing platforms, automation, and process engineering, supported by the broader Danaher ecosystem. The aim is not isolated laboratory success, but industrially relevant workflows that reduce manual variability and enable closed, automated processing.

 

“Practically, that means advancing next-generation delivery systems while also strengthening the surrounding workflow: improving process robustness, reducing manual variability through automation and closed processing, and ensuring early compatibility with standardization and future GMP translation,” Donati said.

 

Ultimately, this approach is about making advanced therapies reproducible and economically sustainable—an essential step toward expanding patient access beyond a handful of specialized centers.

 

Key design considerations for industrialized delivery:

• Early automation reduces variability and risk.
• Closed, standardized workflows support GMP translation.
• Economic sustainability is essential for broad patient access. 

Enabling long-term, high-impact innovation

Can you explain how Danaher Beacons fosters cross-disciplinary research and supports long-term, high-impact scientific innovation?

 

Danaher Beacons are structured as long-term collaborative research efforts designed to address foundational challenges that cannot be solved in silos. Rather than focusing on short-term outputs, they emphasize platform innovation with long-term significance.

 

“The ambition is lasting impact—solutions that change what’s possible across the genomic medicine workflow, not incremental gains,” Donati said.

 

By combining academic insight with industrial discipline, the Beacon model ensures that biological discovery and engineering rigor inform one another continuously—a necessity for solving systemic delivery challenges.

 

Why the Beacon model matters:

• Foundational problems require sustained, cross-sector collaboration.
• Platform innovation outlives individual programs.
• Integration of science and engineering accelerates real-world impact.

 

This content includes text that has been created with the assistance of generative AI and has undergone editorial review before publishing. Technology Networks' AI policy can be found here.