The cell and gene therapy sector has never lacked attention, but all too often, the narrative swings from one extreme to another. A few years ago, irrational exuberance set sky-high expectations; more recently, pessimism has taken hold. The reality is steadier progress, less flashy, but laying the groundwork for lasting patient impact.

And while investor sentiment may fluctuate, big pharma continues to make promising moves in the space. Recent billion-dollar bets, from Lilly’s Verve acquisition to AstraZeneca’s buyout of EsoBiotec and AbbVie’s purchase of Capstan, highlight conviction in a decades-long horizon where cell and gene therapies will reshape care.

On the regulatory side, FDA/CBER has recently issued three new draft guidances, FDA launched PreCheck to streamline quality assessments for domestic facilities, and HHS ARPA-H introduced THRIVE to expand affordable genetic medicines. This supportive regulatory environment signals a favorable policy environment oriented toward acceleration.

Yet even in this favorable environment, safety, efficacy, and scalability remain top priorities. As we’ve seen across recent issuances of Complete Response Letters (CRLs) and new guidances, robust and reproducible processes are a critical driving factor of approvals. A recent analysis of over 200 CRLs issued between 2020 and 2024 showed that 74% of letters issued were in response to quality and manufacturing deficiencies. With this, chemistry, manufacturing, and controls (CMC) and operational efficiency take center stage in commercializing advanced therapies. Understanding the pitfalls of scaling will be a determining factor in whether a program will succeed or be sent back to the drawing board.

Common Pitfalls in Scaling Cell and Gene Therapies

Most setbacks in moving from the clinic to commercialization stem from operational and regulatory gaps. These often include assays that fail to maintain reliability at scale, comparability strategies that don’t hold up under regulatory scrutiny, and processes that can’t meet commercial demands. Even in today’s favorable regulatory climate, the FDA continues to emphasize that the process is the product. Successful scale-up requires an integrated approach to regulatory strategy, risk management, and data integrity. 

Analytical Variability: Top Source of CRLs

In advanced therapy development, analytical variability, especially in potency assays, is a leading driver of CRLs. Methods for potency, identity, and purity that perform well in early development often show variability when scaled to commercial settings.

Expedited designations like Fast Track, Breakthrough, and Regenerative Medicine Advanced Therapy (RMAT) offer opportunities for increased regulatory engagement, but they don’t relax CMC requirements. RMAT allows flexible trial designs and in some cases the use of outside or real-world data, but companies must continue to meet FDA requirements to keep the designation and its benefits.

Late-stage reviews frequently identify issues like unbridged method changes, site-to-site inconsistencies, and gaps in safety testing. Regulators expect a clear link to clinical outcomes and robust lifecycle governance. Connecting assay performance to the process and standardizing operations provide more consistent results and strong data that can hold up under regulatory review.

Tech Transfer Is a Continuous Discipline

Technology transfer is often viewed as a milestone, when in reality, it is a continuous discipline.  Every transition from clinical to commercial or between CDMOs amplifies risk. Even subtle differences in raw materials or fill finish parameters between sites can become critical if left unaddressed.

In cell and gene, each modality faces its own unique challenges. For adeno-associated viruses (AAV), purification steps and plasmid supply often hold back scale. For lentiviruses (LV), maintaining stability across real-world hold times is still a challenge, and for chimeric antigen receptor T cells (CAR-T), programs quickly run into risk when vein-to-vein times stretch beyond a month, putting both product quality and patient outcomes at risk.

Regulators expect to see comparability plans built in from the start, with full change histories and proof that the product is consistent from early trials through commercial. Leveraging standardized protocols, digital dashboards, and aligned processes creates the safety net regulators expect, and can help avoid surprises later in development.

Building Credibility Through Process Control and Data Integrity

As we’ve seen with several recent examples, even if the science is strong, programs can lose credibility over weak data practices. Too many facilities still rely on manual steps, inconsistent monitoring, and incomplete calibration, creating critical blind spots. Fragmented systems for batch records, labs, and quality make matters worse, creating incomplete audit trails that regulators view as evidence of poor oversight. Complete and credible data can help demonstrate reliable end-to-end control of the process. If gaps appear, confidence in the program erodes, no matter how strong the underlying therapy.

Supply Chain Resilience in a Volatile Market

Raw Materials and Upstream Inputs

The first pressure points in advanced therapy manufacturing usually show up in raw materials like plasmids, resins, and single-use consumables. As both global and domestic supply chains become increasingly volatile, relying on a single supplier creates real risk. Qualifying backup suppliers and early capacity reservations can help ensure programs aren’t exposed to disruption, ultimately strengthening operational stability.

Patient Timelines and Autologous Logistics

In autologous therapies, where each batch is tied to a single patient, logistics are as critical as the treatment itself. Meeting chain-of-identity and chain-of-custody requirements is not only a regulatory obligation, but also the deciding factor in whether a patient receives treatment on time.

Delays or errors in tracking can jeopardize both patient safety and program credibility. Leveraging redundant checkpoints and simulated scenarios through digital twins can help mitigate logistical risks. With these tools, programs can stress-test shipping routes and site capacity, and implement real-time rerouting to create operational resilience.

Scaling autologous therapies through pod-based designs can allow for repeatable processes to seamlessly scale without losing consistency. We’re also seeing companies leverage hybrid models with centralized vector production and decentralized final cell-processing closer to the patient, to shorten vein-to-vein times without sacrificing quality.

Digital-First Facility Design

In cell and gene therapy manufacturing, facility design is critical to product success. Every decision in design, automation, and data infrastructure directly determines whether a program can scale commercially. Treating the facility as part of the product and implementing a digital-first strategy will provide the framework for long term success.

Closed, Automated, Single-Use Architecture

Cell and gene therapy manufacturing is most reliable and scalable when processes are closed, automated, and built on single-use systems. These standardized systems can help demonstrate that the process can maintain safety and efficacy as it scales. These designs also reduce open handling and manual steps, ultimately lowering the chance of contamination or operator error.

• For vectors (AAV, LV): Automation and in-line monitoring help reduce variability
• For CAR-T: Closed systems, serum-free media, sterile connectors, and robotic filling reduce human error and improve reliability from patient cells through to final product.

These designs all play a role in reducing variability, a leading hurdle in bringing cell and gene therapies from clinical to commercial scale.

Process Analytical Technology and Advanced Sensing

Process Analytical Technology (PAT) uses in-line sensors and analytics to monitor production in real time. This creates a “fingerprint” of each run so issues can be detected earlier, reducing the lag between production and quality release. The result is shorter quality assurance (QA) cycles and fewer failed batches. As production scales, PAT helps maintain consistency and quality across sites, reducing variability that often causes late-stage setbacks.

Integrated Digital Stack

Regulators place high value on data integrity and expect clear, traceable records across manufacturing, testing, and quality systems. A connected digital stack provides that foundation by linking:

• Manufacturing systems to ensure processes are executed consistently and right the first time
• Testing systems to track assay performance and flag when methods drift or need re-validation
• Quality systems that extend beyond equipment and processes to also govern software models and digital tools.

Integrated data demonstrates a well-controlled and reliable process, while reducing errors to help move products through quality release faster. A strong digital backbone also helps keep facilities future-ready. Advanced tools like AI integration and digital twins can only be integrated if the underlying systems are validated and compliant.

AI and Digital Twins for Process Control

AI-backed tools like digital twins are becoming essential for building more resilient cell and gene operations. They can:

• Assist in early detection in small process shifts like minor temperature changes before they show up in quality control (QC)
• Use soft sensors to forecast yield, potency, or infectivity, helping teams intervene sooner
• Optimize facilities with plant-level twins that can support predictive maintenance and production scheduling
• Improve oversight with enterprise twins (DTOs) that can map processes to reveal bottlenecks, inefficiencies, and compliance risks.

These tools can give predictive insights that ultimately improve throughput, reduce downtime, and make scaling more feasible. But they only build value if they’re validated, explainable, and managed under strict quality systems. Without governance, the same models meant to speed development can undermine regulatory trust and delay approvals.

Leveraging Real-Time Release Testing

Real-Time Release Testing (RTRT) changes how products move through quality review. RTRT uses continuous monitoring and rapid in-line or at-line tests to confirm quality as a batch is being made. Even partial RTRT, built on advanced sensors and quick assays, can:

• Shorten QA cycles so products clear review faster
• Catch problems earlier, reducing costly deviations
• Lower the risk of wasted batches, protecting both time and resources.

Faster release times mean patients get therapies sooner, and companies that implement RTRT effectively may have a competitive advantage. Finally, demonstrating that quality is monitored in real time may strengthen regulatory confidence.

A digital-first facility isn’t about adding technology for its own sake. It strategically weaves automation, analytics, and strong governance into the process so therapies can scale reliably, meet compliance standards, and reach patients on time.

Anshul Mangal is a biotech entrepreneur, experienced executive, board member, philanthropist and attorney. He is the CEO of Project Farma (PF) and President of PerkinElmer OneSource. He is also a board member at the Alliance for Regenerative Medicines, Alliance for mRNA Medicines and IQHQ.