The case for smarter collaboration in CGT manufacturing 

As the cell and gene therapy (CGT) field matures, pressure is mounting to improve the reproducibility, reliability, and scalability of manufacturing processes—without compromising patient safety, intellectual property, or speed to clinic. At BIO 2025 in Boston, a roundtable of CGT thought leaders shared candid insights on the biggest barriers to data sharing, the potential for standardisation, and the transformative role of digital infrastructure. Their answers highlight the growing appetite for pre-competitive collaboration and the practical tools needed to drive it forward. 

Josh Ludwig, Global Commercial Director, ScaleReady 

What’s the biggest barrier to data sharing in CGT manufacturing today—and how do we overcome it without compromising IP? 

“There is a disconnect between the teams at a CGT company doing the work and the legal experts assessing whether information is proprietary or confidential,” said Ludwig. “The legal team is likely to err on the side of caution and is unlikely to take the time to understand what truly requires close protection.” 

He explained that R&D, process development, and manufacturing teams rely on legal departments to make those distinctions—which can limit transparency, even when information is already publicly available. 

“To move quickly in this field, information sharing is important, especially with critical vendors. The best way to overcome these challenges is to ensure CDAs are in place where appropriate, carefully consider the rationale for what ought to be ‘off limits,’ and then ensure that information is clearly communicated. Anything that can be found in patent applications, abstracts or other public documents doesn’t need to be held close to the chest.” 

Experts say 90% of CGT processes could be standardised. Do you agree? 

“We see the need for standards for about 90% of a CAR T ‘recipe’, and we’re working to help develop them,” Ludwig said. “Construct and dose are by far the most important variables on patient outcomes. The rest of manufacturing can be standardised down to how to set up cleanroom table space and how to construct SOPs for inventory management.” 

He pointed out that many startup founders have never run a business before and may not realise when they’re reinventing the wheel. “Standards will help streamline the industry.” 

How can early adoption of data analytics and digital infrastructure reduce repeated errors and accelerate time to treatment? 

“Enabling batch record and test result review in a more timely and automated manner is hugely beneficial,” Ludwig said. “Unlike antibodies or small molecules that might manufacture thousands of doses in a batch, an autologous CAR T batch contains a single dose for one patient. The complexity of managing a paper-based system at scale invites errors.” 

Digitisation, he noted, is also a useful tool for implementing standards across organisations. 

Rupa Pike, senior director, global head of strategic alliances and field scientists, cell therapy, Catalent 

What’s the biggest barrier to data sharing in CGT manufacturing today—and how do we overcome it without compromising IP? 

“IP positions and the need for security and privacy do play a role,” Pike said, “but there are other compelling factors too: compliance requirements, diverse data platforms, lack of connectivity between legacy and newer systems, and lack of technical expertise to manage data sharing.” 

She believes these barriers can be addressed through targeted standardisation and stronger partnerships across academia, nonprofits, industry groups, and regulators. “That will allow for streamlining of the data sharing process.” 

Can 90% of CGT processes be standardised? 

“Standardisation is possible for specific cell types and therapeutic indications,” Pike said. “Many steps in CAR-T processes can be standardised as we’ve gained expertise. And certain regenerative therapies share common expansion steps that could be harmonised.” 

She highlighted starting materials, cell expansion in bioreactors, and cryopreservation as areas with strong potential. “Use of semi-automated and fully automated platforms, along with instruments that provide superior analytics, can help.” 

How can early adoption of data analytics and digital infrastructure reduce repeated errors and accelerate time to treatment? 

“Cell therapies are unique. The final drug product is viable cells composed of thousands of biomolecules that can change with every manipulation step,” Pike said. 

“Advanced data analytics lets developers acquire, analyse, and optimise data on cell health and behaviour, build predictive models, and achieve efficiency. It’s the backbone of process optimisation.” 

Building digital infrastructure also improves access across stakeholders, reduces human error, and shortens turnaround times. “It makes life-saving therapies more accessible.” 

Alexander Seyf, CEO, Autolomous 

What’s the biggest barrier to data sharing in CGT manufacturing today—and how do we overcome it without compromising IP? 

“The biggest barrier is the perceived threat to competitive advantage and IP,” Seyf said. “Companies fear exposing proprietary processes, eroding market position, or compromising valuable IP.” 

Digital platforms, he explained, can enable selective data sharing with granular controls. “These solutions include robust governance, access controls, and audit trails—all underpinned by legal agreements.” 

“By focusing on pre-competitive collaboration and ensuring security, we can foster trust and collective learning.” 

Do you agree that 90% of CGT processes could be standardised? 

“Yes,” he said. “While the final drug for autologous therapies is patient-specific, the underlying operations and quality control share significant commonality.” 

He advocated for: 

• Digital MES/ELN systems for structured data capture 

• Industry forums to share anonymised process data 

• Regulatory alignment on standardised elements 

What role does trust play in enabling better collaboration? 

“Trust is the absolute bedrock of effective data collaboration,” said Seyf. “It’s essential to trust that information will be protected, data is accurate, and all parties benefit.” 

Trust, he added, is reinforced by digital systems that include transparent governance and secure controls. “This ensures partners can confidently share insights to accelerate patient access.” 

How can early digital adoption accelerate time to treatment? 

“It’s transformative,” Seyf said. “Real-time capture and analytics shift the process from reactive troubleshooting to proactive prevention.” 

He said root cause analysis can be reduced from weeks to hours, and tech transfer streamlined via standardised data. “Every adjustment feeds a self-learning loop. That visibility and learning accelerate how quickly therapies reach patients.” 

What does ‘responsible data sharing’ look like in practice? 

“It’s purpose-driven, secure, and compliant,” he said. “Clear legal agreements, IP definitions, and GDPR compliance are key—along with access controls, audit trails, and role-based permissions.” 

Scalability, he noted, depends on strong digital governance that protects IP while enabling shared insights. 

Dalip Sethi, commercial leader, cell therapy technologies, North America, Terumo Blood and Cell Technologies 

What’s the biggest barrier to data sharing in CGT manufacturing today—and how do we overcome it without compromising IP? 

“Manufacturing processes are competitive differentiators, making companies cautious about sharing data,” Sethi said. “We also face incompatible systems and a lack of standardisation.” 

He advocates for standardised, anonymised formats and secure data platforms to enable collaboration without compromising sensitive details. “When standardisation, security, and trust align, data sharing can drive innovation and operational excellence.” 

Can 90% of CGT processes be standardised? 

“Yes—but it requires shifting to digital and automated systems,” Sethi said. Automation, sensor integration, and high-quality data are prerequisites for ML- and AI-enabled analytics. “Sharing real-world case studies can demonstrate the tangible benefits.” 

What role does trust play in enabling better collaboration? 

“Trust is fundamental,” he said. “It allows stakeholders to align on shared goals and governance. Secure infrastructure ensures collaboration without risking IP or compliance.” 

How can digital infrastructure reduce errors and accelerate treatment? 

“Digital tools are essential throughout the CGT lifecycle,” Sethi said. “They reduce human error, enable real-time monitoring, and optimise steps from collection to formulation.” 

What does responsible data sharing require? 

“It means structuring anonymised data formats and establishing governance frameworks—charters, ethical agreements, role-based access,” he said. “Tech firms can act as neutral integrators to enable scalable collaboration.” 

Jonathan Wofford, CCO, Title21 

What’s the biggest barrier to data sharing in CGT manufacturing today—and how do we overcome it without compromising IP? 

“There are three key barriers: fear of exposing proprietary information, lack of data standardisation, and no centralised structure for data sharing,” Wofford explained. “But none of these are insurmountable.” 

He believes the solution starts with focusing on ‘standard’ data—such as donor demographics and collection variables—and creating a shared data language using frameworks like the one from CIBMTR. 

Can 90% of CGT processes be standardised? 

“I think 90% is too high,” Wofford said. “While basic steps like collection and infusion are similar, variation in disease protocols, instruments, and human factors makes universal standardisation complex.” 

What role does trust play in enabling better collaboration? 

“Trust is paramount,” he said. “Organisations must be confident that data is accurate, secure, and handled ethically. That’s what creates the environment where collaboration and innovation thrive.” 

How can digital adoption reduce errors and speed time to treatment? 

“Digital infrastructure allows real-time analysis, increases data integrity, and reduces manual entry,” Wofford said. “This can drastically cut errors and enable rapid decision-making that improves patient outcomes.” 

What does responsible data sharing look like in practice? 

“It’s all about clear governance,” he said. “There must be policies for data collection, analysis, and access—along with encryption, ethical oversight, and minimal exposure.” 

“Secure protocols and a shared framework protect IP while fostering collaboration.” 

Kevin Land, executive medical director, biotherapies & VP clinical services, & Robert Marriott, VP clinical & research quality services, Vitalant 

What’s the biggest barrier to data sharing in CGT manufacturing today? 

“One barrier is a reluctance to intermix data due to privacy and security concerns,” Land and Marriott said. “Stakeholders don’t always understand what’s actually covered by IP claims, which are often narrow.” 

They pointed to real-world evidence models, like big data sandboxes, as potential solutions—”everyone sees the output without compromising IP.” 

They also noted a lack of standardised terminology across systems. “Groups like OHDSI are building a Common Data Model that can serve as a universal interface.” 

Can CGT manufacturing be standardised? 

“The seven basic steps of CGT manufacturing are the same,” they said. “Some elements are therapy-specific, but the real challenge is alignment—many still want to make their processes unique.” 

They believe regulator flexibility will be critical, particularly to allow expedited reapproval of process changes that don’t impact final product quality. 

“Once you standardise processes, you must also standardise the systems capturing the data.” 

Why is trust so difficult in CGT collaboration? 

“Trust requires a mindset shift,” they said. “Many entrepreneurs succeed by working independently. But CGT is too fragmented for any one company to succeed alone.” 

“Violations of trust can be lethal—for the product and for the relationship.” 

How does digital infrastructure accelerate access? 

“Early adoption of analytics sets the framework for how organisations think about and approach data. That helps drive accuracy and faster decision-making,” they said. 

By identifying high-volume errors and starting to build large datasets early, companies can foster predictive analytics and personalised manufacturing protocols. 

“It all starts with ethics and security—and most of all, trust.”