Strained Manufacturing, Complexity Stymie In Vivo Progress

By Victor Lien

The scientific hurdles of delivery are not isolated from the realities of manufacturing; they directly dictate the processes, infrastructure, and timelines required to bring in vivo gene editing therapies to patients. Each delivery platform introduces unique manufacturing constraints that translate biological risk into operational bottlenecks.

For AAV vectors, payload limitations and immunogenicity challenges force developers into technically demanding strategies such as dual‑vector systems or split‑Cas9 constructs. These approaches double the number of GMP production runs, expand analytical testing matrices, and require co‑transduction validation, all of which strain upstream bioreactor capacity and downstream purification throughput. Immunogenicity further necessitates capsid engineering and bespoke potency assays, adding layers of analytical development and regulatory complexity.

By contrast, mRNA/LNP systems shift the bottleneck into chemical synthesis and formulation. Ionizable lipid supply chains are narrow and capacity‑constrained, making raw material procurement a critical risk. The encapsulation process itself — often performed via microfluidic mixing or tangential flow filtration — demands precise process control and specialized equipment, with narrow operating windows that complicate scale‑up. When targeting immune cells or tumors, ligand conjugation steps add additional QC burdens and supply chain dependencies for biologics while higher per‑patient dose requirements in oncology magnify demand for GMP slots, fill/finish capacity, and cold chain logistics.

This linkage between delivery complexity and manufacturing bottlenecks can be summarized as follows:

Delivery Challenge	Direct Manufacturing Impact	Why It Becomes A Bottleneck	Suggested Typical Mitigations
AAV payload/packaging limits	Requires dual‑vector or split‑Cas9 campaigns, each needing separate plasmid prep, transfection, and purification runs	Oversized Cas9/gRNA constructs exceed 4.7 kb, forcing dual or split vectors. This doubles GMP runs, QC assays, and co‑transduction validation, stretching bioreactor and purification capacity.	Use smaller Cas variants; select CDMOs with multi‑vector expertise.
AAV immunogenicity/re‑dosing limits	Necessitates engineered capsid production, expanded immunogenicity assays, and long‑term stability studies for novel serotypes	Preexisting antibodies and strong anti‑capsid responses require novel serotype design and expanded immunogenicity testing. Each new capsid adds analytical development and regulatory hurdles, slowing release.	Outsource capsid engineering and conduct parallel assay development.
LNP endosomal escape/targeting ligands	Demands custom ionizable lipid synthesis, ligand conjugation steps, and precise microfluidic encapsulation processes	Ionizable lipids and ligand conjugates are custom chemistries with few GMP suppliers. Narrow supply chains and complex QC for conjugation efficiency make scale‑up fragile and delay‑prone.	Partner with CDMOs with validated lipid libraries.
Tumor microenvironment barriers	Requires larger batch sizes, stress stability testing under hypoxic/acidic conditions, and higher per‑patient dose formulation	Hypoxia, acidity, and dense stroma demand higher per‑patient doses and stress stability studies. This increases raw material consumption, batch sizes, and QC timelines, straining GMP slot availability.	Plan larger volumes and early stability studies.
Co‑delivery of multiple modalities	Involves parallel GMP production of Cas9 mRNA, gRNA, donor templates, plus co‑formulation and compatibility QC	Cas9 mRNA, gRNA, and donor templates require separate GMP production and release. Co‑formulation adds compatibility testing and stability assays, multiplying analytical workload and fill/finish orchestration.	Harmonize CMC and co‑encapsulation strategies.
Cell‑type targeting (T cells, NK)	Adds ligand conjugation manufacturing steps, biologics QC assays, and supply chain coordination for antibodies/peptides	Antibody/peptide ligands add extra conjugation steps, biologics QC, and supply chain dependencies. Each ligand batch must be validated for binding and sterility, extending timelines.	Modular ligand libraries; biologics‑capable CDMOs
Transient vs. durable expression	Forces reliance on distinct platforms: cell‑based viral vector production vs. chemical IVT/LNP synthesis	AAV requires cell‑based viral production; mRNA/LNP relies on chemical synthesis. CDMOs often specialize in one, so switching platforms complicates tech transfer, comparability, and regulatory filings.	Select integrated CDMOs or a multi‑partner strategy.

 

In practice, delivery choices force specific manufacturing constraints:

• Selecting SpCas9 with AAV requires dual or split‑vector campaigns, doubling production and QC timelines.
• Choosing mRNA/LNP with targeting ligands necessitates custom lipid synthesis and conjugation validation, creating new vendor qualification steps.
• Targeting solid tumors increases per‑patient material demand, amplifying GMP slot scarcity and cold chain distribution challenges.

These examples illustrate how delivery innovation and manufacturing execution are inseparably linked. The complexity of the delivery system determines not only the scientific feasibility of the therapy but also the scalability, cost, and speed of its clinical deployment. Explicitly mapping delivery challenges to the associated GMP process steps — plasmid supply, upstream bioreactors, lipid synthesis, encapsulation, downstream polishing, potency assays, and fill/finish — converts biological risk into operational risk. This translation is essential for CDMO selection, risk mitigation planning, and ultimately for ensuring that transformative therapies can move from concept to clinic without being stalled by infrastructural bottlenecks.

The Constraints Of Contract Manufacturing And CDMO Selection Matrix

Translating these technically sophisticated therapies from preclinical laboratory studies to mass-produced globally available drugs requires a robust, scalable manufacturing backbone. This infrastructure is largely provided by specialized CDMOs. The global market for CDMOs supporting CGT is projected to explode from its current value to well over $74 billion by 2034. However, severe infrastructural and operational bottlenecks currently threaten to slow the pace of innovation and clinical access.

Critical bottlenecks and strategic imperatives:

• Capacity constraints: There is a critical global shortage of GMP grade manufacturing slots, particularly for viral vectors (AAV) and LNPs. Building a new compliant CGT facility is a multiyear, multi-hundred-million-dollar endeavor, and current demand far outstrips available capacity, creating significant delays of six to 18 months in clinical development timelines.
• Tech transfer complexity: Moving a proprietary, sensitive, and often novel manufacturing process (the "recipe") from an innovator biotech company to a CDMO’s facility, known as technology transfer, or tech transfer, requires extensive documentation, intensive training, and iterative validation runs. Because gene editing platforms are often custom-built, standard protocols are rare, stretching timelines and consuming enormous resources. The utilization of process analytical technology (PAT) is becoming a strategic imperative to monitor and control processes in real time, improving the predictability of the transfer.
• Workforce gaps: The rapid exponential expansion of CGT manufacturing has severely outpaced the development of a skilled, qualified workforce. This leads to acute shortages in critical highly specialized roles, including quality control, regulatory affairs, and process engineering, forcing CDMOs and biotech to compete aggressively for a shallow talent pool. Strategic investment in internal and external workforce development initiatives is required to mitigate this risk.
• Digital fragmentation: Many CDMO networks utilize disparate legacy digital systems. This lack of integrated digital infrastructure across sites and between the CDMO and the client hampers effective data sharing, prevents process harmonization, and restricts the use of real-time decision-making and AI-driven analytics for process optimization. Full digital integration with cloud-based systems is essential to ensure traceability and efficiency at scale.

To overcome these structural impediments, CDMOs must strategically evolve from being merely service providers to fully integrated strategic partners. Key strategic priorities include platform harmonization — developing modular, scalable, and standardized processes — and full digital integration to manage the vast complexity of these advanced therapies.

While CDMOs are investing money and workforce to implement innovations and improve their capabilities, a well-structured CDMO capability matrix for mRNA/LNP and viral vector platforms can help us objectively assess and compare vendors across technical, regulatory, operational, and strategic dimensions. The following breakdown outlines key attributes necessary for selecting a robust partner.

1. Technical Capabilities

Attribute	Description
Platform Expertise	Proven experience with mRNA synthesis (IVT, capping, purification), LNP formulation, or viral vector production (AAV, lentivirus, plasmid prep).
Scalability	Ability to support scale-up from preclinical to commercial volumes, including minimal batch size GMP runs.
Process Control & Analytics	In-house analytical methods for potency, purity, encapsulation efficiency, residuals, and off-target analysis.
Closed-System Readiness	Infrastructure for aseptic processing, single-use systems, and containment for gene editing payloads.

 

2. Regulatory & Quality Compliance

Attribute	Description
GMP/GLP Certification	Track record of GMP/GLP compliance for IND-enabling and clinical batches.
Inspection History	FDA/EMA inspection outcomes, warning letters, and audit transparency.
Module 3 Support	Capability to generate CMC documentation, batch records, and comparability data for regulatory filings.
QMS Maturity	Harmonization of deviation, CAPA, change control, and document management systems.

 

3. Operational Execution

Attribute	Description
Tech Transfer Readiness	SOPs, documentation templates, and cross-site transfer experience.
Lead Times & Flexibility	Ability to accommodate compressed timelines, surge capacity, and change orders.
Supply Chain Coordination	Customs/tariff navigation, component licensing, and chain-of-custody for clinical shipments.
Digital Integration	Use of project management tools (e.g., Smartsheet, Planisware), dashboards, and real-time tracking.

 

4. Strategic Fit & Governance

Attribute	Description
IP & Licensing Clarity	Transparency on third-party IP, licensing terms, and freedom-to-operate.
Alliance Management	Willingness to engage in joint governance, escalation protocols, and performance reviews.
Geographic Footprint	Site locations across NA, EU, APAC to support global programs and redundancy.
Cultural Alignment	Responsiveness, transparency, and collaborative mindset — especially critical in interim leadership roles.

 

Beyond technical and quality metrics, the financial viability and speed of clinical development are determined by cost and turnaround time, which are intensely scrutinized for resource-intensive gene editing and mRNA/LNP programs. Here, I outline how I typically evaluate CDMOs with these two considerations.

Cost Considerations

• Per-batch pricing: Includes plasmid prep, IVT synthesis, purification, LNP formulation, fill/finish, and extensive QC testing. Gene editing payloads require custom synthesis and purity standards significantly higher than traditional biologics, which inherently drives up costs.
• Licensing and IP fees: If the CDMO utilizes proprietary technologies, such as advanced LNP systems or high-efficiency enzymes, the client must account for significant one-time or royalty-based licensing and IP fees.
• Tech transfer and onboarding fees: Many CDMOs charge distinct fees for the initial documentation review, analytical method transfer, and formal validation runs required to transition the process from the client to the manufacturing site.
• Stability and storage costs: The long-term storage and ongoing stability studies required for GMP materials — particularly those requiring ultra-cold storage, such as mRNA — add significant sustained overhead costs that must be factored into the total program budget.
• Customs/tariff costs: For global clinical programs, the logistics of import/export, associated tariffs, and regulatory documentation for shipping clinical materials across international borders represent a complex, non-trivial financial and logistical burden.

Turnaround Time Considerations

• Lead time for GMP slots: Due to capacity constraints, top-tier CDMOs often have wait times of six to 12 months for a reserved GMP manufacturing slot unless the reservation is made very early in the process, necessitating aggressive long-term planning.
• Tech transfer duration: This duration is highly variable, depending on the quality of the client’s documentation, the technical complexity of the method, and the CDMO’s platform familiarity. It typically ranges from three to six months before a full-scale engineering run can be scheduled.
• Batch release timelines: The time required to complete all mandated QC release testing — including sterility, endotoxin assays, and the critical functional potency assays — is often a major rate-limiting step, frequently requiring four to six weeks post-manufacture before the product can be released for patient dosing.
• Regulatory documentation prep: Authoring the comprehensive Module 3 CMC sections for regulatory filings and generating the required comparability data can be an intensive process requiring two to three months, often running in parallel with manufacturing.
• Contingency buffers: Due to the inherent complexity of biological manufacturing, planning must include significant contingency buffers to account for potential deviations, CAPAs, or the need for rework or repeat batch production.

Conclusion: Converging Innovation And Infrastructure For Lifesaving Therapies

In vivo gene editing is not merely an incremental drug improvement; it represents a paradigm shift in oncology, offering genuine curative potential through direct programmable interventions at the genomic level. From the molecular precision offered by the continuously evolving CRISPR-Cas9 platform to the growing sophistication and scale of delivery platforms like AAV and mRNA/LNP, the field has achieved remarkable, rapid strides in a little over a decade.

Yet scientific ingenuity and molecular design alone are insufficient to impact patient outcomes globally. The successful path to widespread clinical application is inextricably linked to the ability to navigate the formidable delivery challenges posed by the harsh tumor microenvironment, overcome systemic manufacturing bottlenecks, and align operational execution with global regulatory standards. The ongoing development of novel targeting strategies, advanced RNA chemical engineering, and next-generation delivery vehicles continues to expand the therapeutic arsenal, but their clinical success remains tethered to the existence of scalable, reliable infrastructure and operational readiness.

CDMOs play a pivotal bridging role in this convergence of innovation and implementation. As clinical demand surges globally, their ability to standardize and harmonize manufacturing platforms, accelerate complex technology transfer, and integrate advanced digital systems will be the primary determinant of how quickly and reliably these revolutionary lifesaving therapies reach the patients who desperately need them. Ultimately, the future of in vivo gene editing in oncology lies at the critical intersection of molecular precision and enterprise execution. By successfully uniting sophisticated delivery innovation, prudent clinical strategy, and robust global manufacturing capacity, the biotechnology industry can transition gene editing from a profound scientific breakthrough into a scalable, universally accessible reality.

About The Author:

Victor Lien, Ph.D., is a CMC strategy and platform developer with extensive experience across several advanced modalities, including antibody-drug conjugates, cell and gene therapies, and mRNA. He most recently worked as a director of biotherapeutic pharmaceutical sciences at Pfizer. Before that, he was a director of CMC and tech transfer at Gracell Biotechnologies, now a part of AstraZeneca. Other experience includes leadership positions at Bristol Myers Squibb, DowDuPont, Fluidigm, and Vertex Pharmaceuticals. He was also a systems biology instructor at Harvard Medical School. He received his Ph.D. from the University of California San Diego.