Nature Neuroscience, Published online: 08 May 2026; doi:10.1038/s41593-026-02305-0
The choreography of cerebral vasculature development
Nature Neuroscience, Published online: 08 May 2026; doi:10.1038/s41593-026-02305-0
The choreography of cerebral vasculature development
Nature Neuroscience, Published online: 08 May 2026; doi:10.1038/s41593-026-02307-y
Screening for photoreceptor survival
Nature Neuroscience, Published online: 08 May 2026; doi:10.1038/s41593-026-02306-z
A couple of couplings
Nature Neuroscience, Published online: 08 May 2026; doi:10.1038/s41593-026-02304-1
Neurons for seeing and imagining
The rapid growth of cell and gene therapies is exposing structural limitations in how traditional biopharmaceutical systems were designed. Unlike batch-based manufacturing models, these therapies are patient-specific, requiring tightly coordinated execution across clinical, manufacturing, and quality domains.
In this environment, maintaining chain-of-identity and chain-of-custody is not simply a regulatory requirement, but a foundational design constraint. As programs move from early clinical development into global commercialization, gaps in system-level orchestration can translate directly into compliance and operational risk.
These pressures are driving renewed attention toward how digital infrastructure is architected in regulated life sciences, particularly around validation, traceability, and cross-system integration.
Monika Birdi, global product strategy leader for SAP’s Cell and Gene Therapy Orchestration (CGTO) platform, has spent more than two decades working on regulated enterprise systems across industries, with a recent focus on advanced therapy manufacturing and supply chains. In this interview with GEN, Birdi discusses SAP CGTO’s architecture, regulatory design in SAP Batch Release Hub (BRH) and Intelligent Clinical Supply Management (ICSM), and digital frameworks for inspection readiness, jurisdictional control, and chain-of-identity enforcement. She also shares insights on balancing innovation with GxP validation and building digital infrastructure for global commercialization of patient-specific therapies.
GEN: What foundational lessons about compliance architecture, data integrity, and large-scale system design most influenced your transition into life sciences and cell and gene therapy?
MB: The biggest shift I experienced after moving to life sciences was in perspective and significance. During the many years I worked building large-scale regulated systems in diverse industries, a failure of data integrity meant financial loss or reputational damage. However, when I moved into the pharma and biotech life science sectors, I realized that in this domain, there was zero margin for error. If the chain-identity breaks anywhere in that journey, there is no fallback.

This reality puts compliance at the heart of architecture. Controls need to be built from the start and cannot be retrofitted later. We must stop treating compliance and scalability as competing priorities, because when you architect them together, one enables the other.
GEN: When you began working in advanced therapies, what operational or digital fragilities did you observe in early-stage programs that signaled a structural gap in how regulated supply chains were being architected?
MB: The first thing we need to understand is that advanced therapies are completely different from traditional small molecule manufacturing. Hence, for organizations that have been in the pharma business, shifting to manufacture advanced therapies is different from both scientific and architectural perspectives. The same tools that worked for small molecules will not serve the end-to-end business for advanced therapies.
The common structural gaps I observed were around chain of identity and chain of custody tracking. Since these are typically not part of the native system design, every single process runs via piles of papers that are difficult to organize and trace. In these cases, there was no orchestration layer and all the systems—such as clinical, manufacturing, quality—were running in silos.
GEN: You have led the design and commercialization of SAP CGTO. What operational failures or regulatory risks did you observe in early-stage CGT programs that convinced you digital orchestration had to be architected differently from traditional pharma systems?
MB: Traditional pharma systems are built around batch manufacturing, where thousands of units are manufactured in one batch. Even if one batch fails the compliance, the next batch can be used by discarding the non-compliant batch. Chain-of-identity is being maintained through a combination of spreadsheets. This is what convinced me to rethink orchestration. You can’t take a traditional batch management system and configure your way into CGT compliance.
The right therapy needs to reach the right patient. So, with CGTO, the design question was never “how do we adapt existing functionality” to make a compliant solution. Our approach was to ask, “if we are building this from scratch for one patient and one batch, what should the process actually look like?”
GEN: Autologous cell and gene therapy manufacturing is patient-specific and tightly synchronized. How did you architect SAP CGTO to enforce chain-of-identity and chain-of-custody controls at every transition point rather than relying on retrospective reconciliation?
MB: Personalized advanced therapies operate under a unique manufacturing cycle, which makes conventional post-production reconciliation processes ineffective. We needed an architecture that shifts the control point from “detect and correct” to “prevent and confirm” for every transaction.
With SAP CGTO, every transition point, from receipt at the plant, disposition, manufacturing start, and allocation to final shipment, is within an order and includes validations to make sure the right patient gets the right therapy. The system won’t let you proceed with a mismatched identity. These validations ensure that the process is stopped immediately, instead of alerting the user at a later point in time.
GEN: In your work on SAP BRH, you focused on jurisdiction control and regulatory components. How do digital release architectures need to evolve to support multi-country regulatory environments while preserving data integrity and inspection readiness?
MB: Most organizations use local Standard Operating Procedures (SOPs) and spreadsheets, utilized by people who have been around long enough to manage the regulatory requirements. This system will likely fail if a critical employee leaves, or if you are entering a new market under pressure, or when an inspector asks you to reconstruct a release decision from two years ago.
Jurisdictional controls should be part of the solution. Once validations are embedded directly into workflows, compliance becomes part of the business process. The audit trails are thus automatically created as a natural result of doing the job.
GEN: You believe designing infrastructure before scale exposes operational gaps. What are the most common digital fragilities you see when sponsors defer enterprise architecture decisions until Phase III or Phase IV?
MB: In cell and gene therapy, many sponsors treat digital infrastructure like office furniture: something to worry about later. The largest problems tend to be in two areas: traceability and coordination.

In terms of traceability, it’s common for programs to track materials in whatever way is convenient at that time, such as spreadsheets, half-set-up software, or systems that don’t talk to one another. But for a hundred patients across many sites, it becomes nearly impossible to track it all correctly, especially when the FDA starts asking questions.
But as trials get bigger, it becomes difficult to manage all of it through those means—and in fact, it can become dangerous. Then, as the trial advances, scale your investment in alignment with emerging trial results.
GEN: Across CGTO, BRH, and ICSM, you have helped define regulatory-ready digital architectures for emerging therapy models. What measurable operational or compliance outcomes have resulted from these implementations, and how do they demonstrate advancement in the field’s digital maturity?
MB: The actual benefit of digitalization in advanced therapies shows up in audits and inspections. By ensuring that digital systems are properly implemented from the beginning and integrated with quality and batch record systems, decisions regarding the release of batches are much faster and more accurate.
In the area of clinical trials, integrated systems enable teams to predict and prevent problems rather than simply reacting to them. This results in fewer delays, and the benefits are easy to demonstrate and prove to the authorities.
GEN: What principles guide your approach to building compliant cloud-native platforms that remain modular, secure, and extensible?
MB: I believe modularity itself is a compliance strategy. Highly integrated platforms introduce hidden risk, because every regulatory change or market requirement can trigger system‑wide retesting.
I design security and extensibility together, with clear separation between what is validated, configurable, and subject to formal change control. That clarity allows teams to move faster without compromising compliance.
Commercialization teaches you that adoption depends on validation of reality. A platform can be technically strong, but if it is difficult to validate and operate in a regulated environment, it will not be scaled. The most successful products do not transfer the customer’s validation burden.
GEN: As advanced therapy pipelines expand and manufacturing networks become more geographically distributed, which architectural capabilities will determine whether organizations can sustain compliant commercialization without repeated remediation cycles?
MB: We need to start building compliance as the core of architecture instead of treating it as per each unique market need. Once the foundation has been set, market regulations can be adjusted accordingly. A few capabilities in which I would invest early include real-time chain-of-identity enforcement, jurisdictional logic embedded in workflows rather than documented beside them, and audit structures that generate inspection-ready data as a natural output, as opposed to a reconstruction exercise. What really matters most is the flexibility of architecture. Regulations evolve, new markets pop up, and manufacturing networks constantly adapt and relocate. This requires organizations to build adaptable and modular architecture that can evolve with growth.
The post How Digital Orchestration Is Redefining Regulatory Infrastructure for Cell and Gene Therapy appeared first on GEN – Genetic Engineering and Biotechnology News.
MADRID — Spanish authorities on Friday were preparing to receive more than 140 passengers and crew members on board a hantavirus-stricken cruise ship headed for the Canary Islands, where health officials have said they will perform careful evacuations.
The vessel is expected to arrive Sunday at the Spanish island of Tenerife, off the coast of West Africa, and passengers will be taken to a “completely isolated, cordoned-off area,” said the head of Spain’s emergency services, Virginia Barcones.
Roche has signed a deal to pay $750 million upfront for Boston-based PathAI, an acquisition by the Swiss pharmaceutical giant to speed up its use of artificial intelligence to help pathologists diagnose disease.
The agreement, which is expected to close in the second half of the year, could generate an additional $300 million for PathAI if it leads to the achievement of certain milestones.
“Joining forces with Roche marks a new era for PathAI, enabling us to realize our mission of improving patient outcomes through AI-powered pathology at unprecedented scale and speed,” said Andy Beck, chief executive and cofounder of PathAI, in a statement. “Roche’s global infrastructure and expertise will bring our digital diagnostics technology to patients worldwide.”
Background: Marijuana initiation among adults aged 50 years and older has increased substantially. Although acute tetrahydrocannabinol exposure can impair psychomotor function, less is known about how real-world medical marijuana initiation relates to functional tasks such as driving in mid-to-late life. Objective: The objective of our study was to evaluate the feasibility of recruiting and retaining adults aged 50 years and older, who are newly registered for medical marijuana, and matched non–marijuana-using controls, into a longitudinal high-fidelity driving simulator protocol, and to explore preliminary associations between medical marijuana initiation and simulated driving performance. Methods: This prospective, nonrandomized feasibility cohort study enrolled adults aged 50 years and older who are newly registered in the Florida Medical Marijuana Use Registry, along with age-, race-, and sex-matched controls. Assessments occurred at baseline (T1; preinitiation) and at 1 month (T2). Primary feasibility outcomes included recruitment, retention, simulator completion and tolerance, and exposure verification. Exploratory outcomes included reaction time and divided attention (DA) performance, which are measured using an immersive, high-fidelity driving simulator. Results: Recruitment and exposure verification procedures were feasible, but simulator sickness contributed to substantial missing data. Exploratory analyses suggested group differences in select DA outcomes at T2. At T2, reaction time to DA situation 3 (DA3) was significantly shorter in the medical marijuana group (n=14, mean 2.57, SD 1.63) than in the control group (n=7, mean 5.79, SD 4.32; =−2.50, =.02, =−1.11, 95% CI −2.04 to −0.16). These findings should be interpreted cautiously, given the small sample size, missing data, and multiple comparisons. Conclusions: A prospective protocol examining medical marijuana initiation and simulated driving among mid-to-late-life adults is feasible, but future studies should incorporate design and analytic refinements to address simulator sickness and missing data and to better characterize exposure timing and patterns. Trial Registration: ClinicalTrials.gov NCT04629716; https://clinicaltrials.gov/study/NCT04629716
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Background: Childhood obesity constitutes a complex medical and psychosocial challenge that requires both nutritional knowledge and sensitive, relationship-oriented doctor-patient communication. The Planetary Health Diet links individual health promotion with environmental sustainability and represents a relevant framework for contemporary medical education. Objective: This proof-of-concept study investigated how different information sources influence medical students’ acquisition, structuring, and application of knowledge on childhood obesity and the Planetary Health Diet within a communication-based teaching setting, including the exploratory use of artificial intelligence–based tools. Methods: A total of 359 second-year medical students participated in a mandatory communication seminar during the 2023‐2024 academic year. Following a precourse knowledge assessment and a brief theoretical introduction, students worked on a standardized counseling scenario addressing childhood obesity. In small groups, students used only 1 assigned information source (ChatGPT, Google Search, scientific papers, or instructional videos) to prepare a counseling approach. Group outcomes were assessed using a predefined scoring system based on a sample solution, complemented by thematic content analysis. Results: All information sources enabled students to acquire relevant knowledge on childhood obesity and the Planetary Health Diet. However, groups differed with regard to the depth, differentiation, and structuring of their responses. The ChatGPT group achieved the highest conformity scores with the sample solution and provided the most additional information, followed by the Google and video groups, while the paper group achieved the lowest scores. Prior to the course, students reported limited knowledge of the Planetary Health Diet and little practical experience in counseling children with obesity and their families. Conclusions: Communication-based teaching formats provide an effective framework for introducing medical students to complex topics such as childhood obesity and sustainability-related nutrition early in their training. Easily accessible digital tools, including artificial intelligence–based systems, may facilitate knowledge acquisition and elaboration; however, their use requires explicit didactic framing, critical source evaluation, and reflection on the complexity of chronic conditions to support responsible and realistic learning outcomes in future physicians.
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