Feliza Mirasol is the science editor for 

Feliza Mirasol

Motor neuron connecting to muscle fiber, 3D illustration | Image Credit: © Julian - stock.adobe.com

A positive opinion from the European Medicines Agency’s Committee for Medicinal Products for Human Use (CHMP) has moved a higher-dose regimen of nusinersen closer to approval in Europe, according to a Nov. 17, 2025 announcement by Biogen. The committee’s positive opinion signals a potential shift in treatment approaches for spinal muscular atrophy (SMA), the company noted in a press release (1).

On the back of the committee’s recommendation, a 

 is expected from the European Commission in January 2026. The recommendation reflects a growing interest in dosing strategies that may offer expanded therapeutic benefit for individuals diagnosed with the most common form of the disease, 5q SMA (1).

SMA is a rare, genetic neuromuscular condition that affects people across age groups. With treatment landscapes evolving rapidly, decisions around dosing, long-term outcomes, and real-world effectiveness have become increasingly central for clinicians, researchers, and 

“While we’ve seen great progress over the past decade [Table], there is urgency to do more to address the clear unmet needs of the SMA community,” said Priya Singhal, MD, MPH, executive vice president and head of development, Biogen, in the press release (1). “The CHMP’s positive opinion for the high dose regimen of nusinersen represents a promising advancement in our commitment to support the evolving needs of individuals living with SMA and deliver therapies that can enhance patient outcomes.”

Biogen licensed the global rights to develop, manufacture, and commercialize nusinersen (brand name Spinraza) from Ionis Pharmaceuticals (1).

What study findings are shaping expectations for clinical impact?

The CHMP’s opinion is based on data from a multi-part Phase II/III study (DEVOTE), which explored safety, efficacy, and pharmacokinetics of a higher-dose regimen across treatment-naïve individuals and those who had been receiving the existing 12 mg dose. In treatment-naïve infants in the pivotal Part B cohort, investigators reported statistically significant improvements in motor function relative to a matched sham group drawn from an earlier study. Participants treated with the higher dose also experienced a reduction in the risk of death or permanent ventilation. These findings underscore the potential for dose intensity to influence therapeutic outcomes, an area of active discussion within neuromuscular research (1).

In Part C of the study, which followed individuals who transitioned to the higher-dose schedule after years on the standard regimen, investigators observed motor function improvements during the first 302 days of treatment. Because long-term durability and safety remain important considerations, the extension phase of the study continues to assess outcomes over time (1).

“The positive CHMP opinion for the high dose regimen of nusinersen is an important milestone for the SMA community,” said Eugenio Mercuri, MD, PhD, professor of Pediatric Neurology at the Catholic University, Rome, Italy, in the release (1). “Based on the results from the DEVOTE study and my experience with patients receiving this novel regimen, I am confident that high dose nusinersen has the potential to bring meaningful benefits to people living with SMA.”

How could a new dose option affect global regulatory decisions and care models?

Nusinersen is approved in more than 71 countries at its current dose, and the higher-dose regimen has recently received approval in Japan, according to Biogen. The company also stated in its release that regulatory reviews are underway in multiple regions, including the United States, for which a decision is expected in April 2026 (1). If additional regions move forward, health systems may see shifts in treatment planning, administration logistics, and long-term monitoring practices. Intrathecal administration, which requires specialized experience, will remain a key implementation factor for hospitals and clinics (3,4).

Safety observations from the study were generally aligned with both the known profile of nusinersen and common clinical events in SMA populations. Ongoing surveillance will continue to shape clinician guidance, particularly around procedural considerations and laboratory monitoring (1).

 the evidence, decisions around dose flexibility may influence how clinicians personalize therapy and how drug developers design future trials aimed at optimizing motor outcomes, durability, and safety for diverse SMA populations (5).

High Dose Regimen of Nusinersen Receives Positive CHMP Opinion for the Treatment of Spinal Muscular Atrophy

. Press Release. Nov. 17, 2025.
2. Servais, L.; Day, J. W.; De Vivo, D. C.; et al. Real-World Outcomes in Patients with Spinal Muscular Atrophy Treated with Onasemnogene Abeparvovec Monotherapy: Findings from the RESTORE Registry. 


3. Finkel, R. S.; Ryan, M. M.; Pascual Pascual, S. I.; et al. Scientific Rationale for a Higher Dose of Nusinersen. 


4. Cordts, I.; Lingor, P.; Friedrich, B.; et al. Intrathecal Nusinersen Administration in Adult Spinal Muscular Atrophy Patients with Complex Spinal Anatomy. 


5. Finkel, R. S.; Day, J. W.; Pascual Pascual, S. I.; et al. DEVOTE Study Exploring Higher Dose of Nusinersen in Spinal Muscular Atrophy: Study Design and Part A Results. 

U.S. FDA Approves Biogen’s SPINRAZA™ (nusinersen), The First Treatment for Spinal Muscular Atrophy

. Press Release. Dec 23, 2016.
7. Ionis. 

SPINRAZA® (nusinersen) Approved in the European Union

. Press Release. June 1, 2017.
8. Novartis. 

AveXis receives FDA approval for Zolgensma®, the first and only gene therapy for pediatric patients with spinal muscular atrophy (SMA). Press Release

FDA Approves Oral Treatment for Spinal Muscular Atrophy. Press Release

FDA Approves Genentech’s Evrysdi (risdiplam) For Use in Babies Under Two Months with Spinal Muscular Atrophy (SMA)

Articles

The European Medicines Agency's Committee for Medicinal Products for Human Use has given a positive opinion on a higher-dose regimen of nusinersen for spinal muscular atrophy (SMA), potentially altering treatment strategies. This decision, based on the DEVOTE study, showed significant motor function improvements and reduced mortality risk in treatment-naïve infants. The higher-dose regimen, already approved in Japan, is under review in other regions, including the U.S. If approved, it could impact global treatment planning and administration practices, emphasizing the need for specialized intrathecal administration expertise.

CHMP supports an enhanced nusinersen regimen, according to Biogen, indicating possible SMA treatment shifts and international regulatory decisions.

Implications on SMA Care of High-Dose Nusinersen

At AAPS PharmSci 360 2025, Elly Zhou says digital twins helped forecast the effects of drugs on human drugs via a digital control arm.

Achieving a Personalized Digital Control Arm for Preclinical Drug Evaluation 

In this interview regarding the poster presentation “A Novel Approach to Preclinical Drug Development Using Digital Twins of Ex Vivo Human Lungs” at 

, Elly (Xuanzi) Zhou, MS, PhD-Candidate, University Health Network, Toronto, Canada, discusses a project that seeks to address significant limitations inherent in traditional randomized control trials, namely, she says, the limited availability of human organs for testing and the high inter-subject variability that often complicates result interpretation. Furthermore, Zhou notes that conventional evaluation models like animal models or organoids often fail to fully capture the complexity of the human system.

The central innovation of her research is using digital twins to create a personalized digital control for every organ being treated. The digital twin leverages large-scale multimodal datasets to train machine learning models that accurately forecast future lung and organ function, Zhou notes. Specifically, after a human lung receives a drug treatment, the digital twin generates the hypothetical untreated effects—the outcome 

 the organ was not treated. This, she adds, serves as a robust digital control arm, enabling direct comparison between the observed treatment effects and the digital twin-generated untreated effects within the same lung. By reducing the reliance on traditional cohort-based analysis and the number of human lungs needed for control groups, this approach is designed to reduce study size and accelerate clinical trials, according to Zhou.

The foundation of the data collection is an

 lung perfusion (EVLP) system, an artificial circuit developed by thoracic surgeons at Toronto General Hospital in 2008. EVLP keeps human lungs alive outside the body by perfusing the organ through vasculature and keeping the lungs ventilated at 37 degrees Celsius. This method allowed Zhou and colleagues to test human lungs directly with a condition of interest, such as perfusing a lung with disease on the circuit. The resulting data are considered highly valuable because they are“clean and capture the lungs in isolation,” free from the systemic effects of the rest of the human body, Zhou explains.

The models incorporate multiple layers of data, including lung physiology (air pressure, compliance, gas exchange), biochemistry (pH level, electrolytes), imaging data (X-rays taken during EVLP), proteomic analysis, metabolic biomarkers, and transcriptomic pathways, says Zhou. This rich dataset is used to generate personalized forecasts. As she summarized,"If you are treating a lung in real life,… you give the treatment and then you observe the treatment effects in terms of organ function and behavior, but... digital twins… generate… untreated effects to serve as this personalized digital control for this organ being treated." Furthermore, the EVLP system demonstrated utility in Zhou and team’s study beyond testing, having been used as a therapeutic platform to perform gene editing using CRISPR technology on human lungs.

*Editor’s Note: This transcript is a direct, unedited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.



 Hi everyone, my name is Elly. I'm a third year PhD candidate at the University of Toronto in Canada, and my supervisor is Dr. Andrew Sage. And my project is focused on developing digital twins of ex vivo human lungs to potentially accelerate preclinical drug development.

Yeah. So if you think about a randomized control trial where you have the two arm design, you have the control and the treatment. So essentially what happens is that we face two major challenges. The first is the limited availability of human organs for testing, and a second is, we're looking at a significant variability within the inter subject conditions that can cause the result interpretation to be very difficult.

So what digital twins can do is that it can generalize a personalized control for every organ that's been treated. So essentially after you provide a drug to treat the human lung, and then what you observe is essentially the observed treatment effects. And then for the digital twin part is that it's going to generate the untreated effects as if the organ was not treated.

So essentially this will allow us to reduce the reliance on a cohort based analysis where we can do direct comparisons between the untreated and treatment effects within the same lung. So this will reduce the study size because this will reduce the number of human lungs we use as controls. So in that way we'll be able to have a faster clinical trial.

So if we think about the traditional drug evaluation models, for example, animal models or organoids, they typically don't fully or often fully capture this. Complexity within the human body or system. So what digital twins can do is that we actually leverage a large scale multimodal data set to train the machine learning models to accurately forecast lung function, organ function of future time points.

So in this way we'll be able to essentially say what is the untreated effects of this drug in this given lung that's been treated? And in addition on this EVLP system, ex vivo lung perfusion, we’ll actually be able to test human lung with the condition of interest directly.

Like for example, we can perfuse a human lung with disease directly on the circuit and observe its behavior, the organ function.

So for this model, we actually incorporate multiple layers of data. So we have lung physiology data, for example, lung, air pressure, compliance, gas, like oxygenation exchange and also biochemistry data such as pH level, acid base and different electrolytes. We also have imaging data, x-ray images because on this EVLP profusion system, we can actually take x-ray images of the lungs.

And in addition to that, we also have proteomic analysis metabolic biomarkers and also transcriptomic pathways. And they have all been incorporated into the model.

Yeah. And so what digital twin does is its going to serve as this robust and also effective digital control arm in the study. So if you can imagine if you are treating a lung in real life while you give the treatment and then you observe the treatment effects in terms of organ function and behavior but what digital twins do, is that it's going to generate this, I guess, untreated effects to serve as this personalized digital control for this organ being treated. So by doing this comparison between the treatment effects and digital twin-generated, untreated effects, we can actually do a direct comparison to say, what is this drug's impact on this organ been treated.

Yeah, so what EVLP system is Ex vivo lung perfusion, which means we're trying to keep a set of human lungs alive outside the human body. So what we do is that we have this artificial circuit that was originally developed in 2008 by a group of thoracic surgeons at Toronto General Hospital. So what we do is we perfuse the organ through vasculature, keep the lungs ventilated through the trachea, keep everything at 37 degrees Celsius in a physiologically protective environment.

So during the process we'll be able to collect a set of clean multimodal lung function data. That can be used to train the digital twin model. And also this data is very clean in the sense that we're actually just looking at the lungs in isolation without systemic effects of the human body.

And in addition to that, at our hospital, we actually have demonstrated that the EVLP system can be used as a therapeutic platform in the work or in the study led by Dr. Shaf Keshavjee at Toronto General Hospital, we have shown that you can actually do gene editing on a set of human lung using CRISPR technology during EVLP

Videos

At AAPS PharmSci 360 2025, Siddhant Sojitra, Alexion, defines an agitation model to reliably test stability for early-stage biologics.

A Scientifically Justified Agitation Stress Model for Early-Stage Biologics 

Siddhant Sojitra, Associate Scientist III, Injectable Drug Product Development, Alexion Pharmaceuticals, discusses the primary role played by scale-down agitation in the development of high-concentration biologics by simulating mechanical stress on drug products in this interview regarding the poster presentation “

Defining a Scale-Down Agitation Model for Early-Stage High Concentration Biologics Formulation Development

. This stress, often encountered as shaking and mixing, occurs throughout the drug product lifecycle, including during manufacturing, transportation, storage, and administration, Sojitra and colleagues 

. Utilizing this model offers crucial insights into how varying levels of agitation impact drug products. Ultimately, the goal is to develop more stable formulations capable of sustaining these mechanical forces without compromising the drug's quality or effectiveness, he adds.

Mechanical stress testing is essential because constant agitation leads to significant negative impacts on product quality, primarily protein aggregation and particulates formation, Sojitra notes. The shaking can expose the protein’s hydrophobic patches, causing nucleation and aggregation, and may also unfold the protein structure. Aggregation severely compromises the protein’s potency, while the formation of particulates raises the risk of immunogenicity and can violate regulatory guidelines, the study team notes in their poster.

To assess the stability of biologic formulations against these stresses, quality attributes (QAs) are demonstrated through various testings, including analysis of appearance, turbidity, size/charge variance, aggregates formation, and particulates formation, says Sojitra. The researchers specifically utilized analytical methods, such as size-exclusion ultra-performance liquid chromatography, to measure high molecular-weight species (HMWS), micro flow imaging to detect subvisible particles (SVP), and optical density (OD) to assess turbidity.

The study systematically evaluated three physical agitation models: an orbital shaker, a multichannel vortexer, and a bench-top shipping simulator (VR5500). Comparisons showed that both the orbital shaker (at 200 RPM) and the vortexer (at 1200 RPM) subjected samples to more severe mechanical stress than the VR5500, making them suitable for robust formulation development studies. A key finding was that the different models impacted distinct QAs. The orbital shaker was found to predominantly promote the formation of HMWS, whereas the vortexer was more likely to induce the generation of SVP.

Based on the study's findings, the optimal, scientifically justified agitation model for early-stage formulation development was defined. Recognizing the need for smaller sizes due to material constraints in early development, the standard configuration selected was the 2R vial. The data support using the 2R vials with a minimum fill volume of 1 mL, positioned in a horizontal placement, and subjected to orbital shaker agitation at ambient temperatures for up to 24 hours. This setup provides a reliable and consistent method to assess the impact of mechanical stress, thereby helping to identify stable formulations early in the development pipeline, Sojitra and team stated.

Check out Sojitra’s take on the roles and barriers to AI and digital technology in biologics, our 



I am Siddhant Sojitra. I work as an associate scientist three in drug injectable drug product development team at Alexion, AstraZeneca. I have three plus years of working experience in the pharmaceutical industry now. My specialization includes biologics drug product formulation development, especially high concentration monoclonal antibody-based formulations.

I have an engineering background. I did my masters in chemical engineering from Northeastern University of Boston.

So the primary role of scale-down agitation model is to simulate agitation stress on drug products. This mechanical stress is in the form of agitation, which means drug products are getting exposed to shaking, mixing, and this is often encountered during manufacturing, transportation, storage, administration.

So that's where the scale-down agitation model comes in. Having this model gives us crucial insights about how different label of agitation impacts drug products, and can also help us to develop formulations much more stable version of drug products, which can sustain all this shaking without compromising its quality and effectiveness.

The major impact on drug product quality are protein aggregation and particulates formation. So because of this constant shaking and agitation, proteins often get exposed to its hydrophobic patches, which can nucleate segregation. It can also unfold protein, and because of this aggregation, it impacts protein's potency, and particulates formation increases immunogenicity risk, and it can also violate guidelines.

Drug products’ quality attributes are demonstrated by various testings, such as appearance and turbidity, measuring size and charge variance, aggregates formation, particulates formation. This is how the drug products quality attributes are demonstrated.

So for early-stage stress testing, we are keeping material constraints in mind. We focused on smaller size vials, which are widely used and our data shows that at least 1 mL in 2R vials when shaken horizontally, using an orbital shaker up to 24 hours, provides a reliable approach to study early-stage stress testing.

Following mechanical stress, there are various testings done, which includes appearance, turbidity, particulate formation, using microflow imaging techniques or light obscuration techniques, aggregates formation using size-exclusion chromatography. And this gives us an idea how drug product is behaving and how the impact of agitation is on drug product.

Siddhant Sojitra, Alexion, defines in an AAPS PharmSci 360 2025 presentation an agitation model to reliably test stability for early-stage biologics.

Defining An Agitation Model for Early-Stage, High Concentration Biologics Formulation Development

American Association of Pharmaceutical Scientists

 (AAPS) will spotlight advances in drug manufacturing and technology at the 

 conference, taking place November 9–12 in San Antonio, Texas. This year’s event will kick off with a plenary session on how investment strategies, production innovation, and emerging modalities are transforming pharmaceutical 

 and the scalability of future therapies. Thousands of industry professionals and researchers are expected to attend as the bio/pharmaceutical sector adapts to new operational demands driven by cutting-edge science (1).

, PhD, associate professor of finance at the Carlson School of Management, University of Minnesota, will deliver the opening plenary on November 9. His session will examine the economics driving innovative therapeutic development, with a focus on the rising complexity and cost of manufacturing advanced modalities. His talk will also explore how these developments relate to improving 

This keynote continues a discussion that began during the 2025 National Biotechnology Conference, where 

, PhD, an economist from MIT Sloan School of Management, addressed similar financing challenges and risk-sharing models. That presentation remains available online through 

 for attendees seeking continuity leading into the upcoming discussion (1).

“Many of the attendees are either involved in developing therapeutics using new modalities or planning to move into this burgeoning sector,” said 

, PhD, chair of the 2025 PharmSci 360 Scientific Programming Committee, in a company press release (1). Dr. He gave a 

“This session will offer insights into the economics driving this critical area in a time of rapid and evolving changes," Dr. He stated in the release (1).

How will investment strategies influence new therapeutic modalities?

Bio/pharmaceutical companies are expanding pipelines that include 

, each carrying unique development and scale-up demands. Financing approaches can directly influence research direction, regulatory timelines, and the resilience of supply chains (3,4). AAPS stated in the release that sessions like the opening keynote aim to help drug developers better assess funding risks tied to these modalities (1).

Dr. Thakor is also scheduled to join the executive session, “

Molecule to Milestone: IND-Enabling Strategy for Pharma Leaders

,” on November 10, in which panelists will discuss how to align scientific milestones with realistic business strategies.

How is AI transforming drug development economics?

Industry analysts note that the rapid adoption of artificial intelligence (AI) across discovery, manufacturing optimization, and quality control could shift cost structures (5). PharmSci 360 will also feature multiple sessions on responsible integration of AI and digital tools, reflecting growing investment in automation and data-driven decision-making. These discussions support a broader conference theme: ensuring that technological progress remains economically viable (1).

How can industry support global access to emerging technologies?

AAPS’s programming emphasizes the importance of equitable access alongside innovation. Key sessions will address the challenges of delivering advanced therapeutics to developing countries, where economic barriers often delay treatment availability (6). Understanding financing mechanisms could help ensure that therapeutics derived from new technologies reach more patients worldwide (7).

Both the opening and closing plenary speeches will feature renowned scientists, which is intended to foster high-level discourse on research philosophy, scientific trends, and future directions, Dr. He noted in her interview. The conference is further expanding engagement with hot-topic sessions and spotlight speakers and encourages greater inclusivity and participation from top experts (2).

AAPS PharmSci 360 Opening Session Examines Drug Development Financing

. Press Release. Nov. 6, 2025.
2. Mirasol, F. 2025 

AAPS PharmSci 360 to Showcase Essential AI Integration and Emerging Technologies

Cell & Gene Therapy Clinical Trials: Current Dynamics & Pipeline Outlook

. Market Research Report. 2025.
4. Labcorp. 

Cell & Gene Therapy Answers: The Evolving Cell & Gene Therapy Landscape

, Aug. 5, 2021.
5. Huanbutta, K.; Burapapadh, K.; Kraisit, P.; et al. Artificial Intelligence-Driven Pharmaceutical Industry: A Paradigm Shift in Drug Discovery, Formulation Development, Manufacturing, Quality Control, and Post-Market Surveillance. 

 (accessed Nov. 7, 2025).
7. Kang, S-K.; Lee, B.; Gupta, R.; et al. Research and Development Financing Models for New Biopharmaceuticals in the United States. 

The 2025 PharmSci 360 conference, organized by the American Association of Pharmaceutical Scientists, will focus on advancements in drug manufacturing and technology. The event will feature discussions on investment strategies, production innovation, and emerging modalities, with a keynote by Richard Thakor, PhD, on the economics of therapeutic development. The conference will also explore the impact of AI on drug development and emphasize equitable access to advanced therapeutics. Sessions aim to help drug developers assess funding risks and align scientific milestones with business strategies.

PharmSci 360 will spotlight the economics behind AI, scale-up, and advanced modalities, addressing cost barriers that influence future drug manufacturing.

Why Investment Strategies Matter for Advancing Pharmaceutical Technologies

PharmSci 360 will spotlight AI advances, gene therapy progress, and leading pharma research insights this year, says programming chair Mei He.

2025 PharmSci 360 to Highlight Next-Gen AI for Drug Development

, in San Antonio, Texas, from Nov. 9–12, highlighting cutting-edge innovations shaping the bio/pharmaceutical sector. 

, Chair, 2025 PharmSci 360 Scientific Programming Committee, and associate professor, University of Florida College of Pharmacy, shares an exclusive preview of this year’s agenda and discusses the transformative role of 

 (AI) and advanced technologies in bio/pharmaceutical research with the 

What are the key trends shaping the 2025 annual meeting?

This year’s conference brings together leading researchers to discuss trending topics, including basic research 

, and the clinical-to-translational research pipeline, Dr. He emphasizes. She notes that more than 800 abstracts for posters and over 200 oral presentations have been submitted, reflecting rapid advances in the industry.

A central theme this year is the integration of AI into all aspects of bio/pharmaceutical research. “You will find a lot [of] interesting topics in this year’s annual meeting…we have a lot of spotlights for the scientists to present in [the] meeting,” Dr. He notes.

AI-powered analytics and manufacturing processes are set to take center stage, along with emerging technologies, such as spatial transcriptomics and 

The event will host opening and closing plenary speeches from renowned scientists, fostering high-level discourse on research philosophy, scientific trends, and future directions, she adds. The conference is further expanding engagement with hot-topic sessions and spotlight speakers, encouraging greater inclusivity and participation from top experts. With AI and 

 trends at the forefront, the 2025 meeting offers an essential platform for scientists aiming to stay ahead in bio/pharmaceutical innovation, Dr. He asserts.

Mei He, PhD, Chair, 2025 PharmSci 360 Scientific Programming Committee and Associate Professor, University of Florida College of Pharmacy

Dr. He is a senior member of the National Academy of Inventors, and chair of the American Association of Extracellular Vesicles scientific program. She is also an editorial board advisor for the journals 

 and the Royal Society of Chemistry’s (RSC’s) 

. Dr. He’s research innovation has led to more than 20 pending and issued patents, of which most have been licensed and launched as products on the market by multiple companies. Dr. He received the National Institutes of Health’s Maximizing Investigator’s Research Award and the RSC’s 

Editor's note: This transcript is a direct, unedited rendering of the original audio/video content. It may contain errors, informal language, or omissions as spoken in the original recording.

Hi everyone. I'm associate professor from the University of Florida, College of Pharmacy, and serve as the chair of the certificate program of the AAPs and especially for this year, AAPs 2025, annual meeting in San Antonio. My research expertise focused on the drug delivery, formulation, the gene therapy and theoretical development, especially, we use the latest modality of the actual cellular vesicles for gene therapy treatment.

This is a great question, and well, this year especially, we have quite a few hot topics in the APS meeting. And every session that we have mainly focused on the six of the same we have the basic research discovery and the formulation drug delivery by analytics and the manufacturing and the clinical size, translational research and with all those different theme and we can see the AI Artificial Intelligence actually plug into the each application very tightly from this year, and they catch up the latest development. And using artificial intelligence, and using the AI approach to develop for each application, and especially their hot topic, is from the translational research session, and also from the formulation drug delivery session, and even in the manufacturing session, we also have the AI plug in to develop the artificial intelligence, and they enhance the manufacturing process. So all those could be very interesting and cutting edge.

This year, we have more than 800 abstract submission and for poster. And we have more than 200 of the submission for the simplest and we also have the hot topics and the rapid fair. And all those sessions are catch up the change in the frontier of the pharma industry and research developments, and especially for the submission trending using the new techniques, and some techniques like artificial intelligence and also the spatial transcriptomics And the gene therapy and AI designed drug so all they use the into therapeutic development, which are the trending right now? So if you want to catch up the frontier of the former development and know what's new of the technology, definitely, you will find a lot interesting topic in this year annual meeting

for today of the top scientists, and we have a lot of spotlights for the scientists to present in APS meeting, and especially for the opening plenary speech, and also for the closing plenary speech, we have those top scientists to present in the to catch up their philosophy and also the research development and also share their experience and the perspectives and during those opening remarks. And we also have hot topics that we are going to develop this hot topics and the spotlight speakers and more and more in the future of the APS annual meeting, which actually have much more engagement of the speakers compared to the past few years. And this also will open the submission for the hot topics and also spotlight speakers, and we want to be more inclusive to accept the more top scientists to be engaged in our meeting.

AAPS PharmSci 360 will spotlight AI advances, gene therapy progress, and leading pharma research insights this year, says programming chair Mei He.

2025 AAPS PharmSci 360 to Highlight Next-Gen AI for Drug Development

In this episode of Drug Digest, the discussion centers around the optimization of biopharmaceutical manufacturing and supply chain efficiency through the mastering of AI capabilities, data integration, and critical validation challenges.

Drug Digest: Strategic Alliances and Technology Integration in the Evolving Biopharma Landscape

The biopharma industry is actively navigating an evolving landscape through strategic partnerships and advanced technology integration. Collaborations are crucial for market expansion, while some companies are leveraging artificial intelligence (AI) for the discovery of novel therapeutic modalities and for manufacturing efficiency. Experts evaluate partners for their AI capabilities, focusing on data integration and validation challenges. Manufacturing, licensing agreements, and supply chain strategies are also paramount. This episode of 

 will explore these trends and how partnering can lead to success in bringing new biopharmaceutical modalities to market.

Sigma Mostafa, Chief Scientific Officer, KBI Biopharma

Cory Smith, Senior Product Manager, Nucleic Acid Services, TriLink Biotechnologies

® editors, who interview industry experts to discuss the emerging opportunities, obstacles, and advances in the pharmaceutical and biopharmaceutical industry for the research, development, formulation, analysis, upstream and downstream processing, manufacturing, supply chain, and packaging of drug products.

MJH, pharmaceutical technology presents drug digest, a tech talk with the pharmaceutical technology editors all about emerging opportunities, obstacles and advances in the pharmaceutical, biopharmaceutical and biotech industries. Join us as we discuss with industry experts the research, development, formulation, analysis, upstream and downstream, processing, manufacturing, supply chain and packaging, as well as business strategies and regulatory issues.

Hi and welcome to the junk digest video series. I'm feliza mirasol, the science editor for pharmaceutical technology, pharmaceutical technology Europe and BioPharm International. In this episode, I'll be talking with industry experts about navigating biopharma's evolving landscape for strategic partnerships and AI innovation. Our discussion will center around the optimization of bio manufacturing and supply chain efficiency through mastering AI data integration and critical validation challenges. Joining me, this episode will be subject matter experts from CTMC, KBI biopharma and trilink biotechnologies.

This episode of drug digest is sponsored by Biovectra, Ecolab, Eppendorf, Fujifilm Biotechnologies, Lab Vantage solutions, the Parenteral Drug Association and pyramal pharma solutions.

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Piramal pharma solutions a cdmo and part of pyramidal pharma Ltd offers end to end development and manufacturing solutions across the drug life cycle, serving customers through a globally integrated network of facilities in North America, Europe and Asia. Now, without further ado, let's meet our guest speakers.

I have about 25 years experience in small, medium and large size biotech and biopharma, mostly developing products, bringing products from research side into the clinic, and then I've been fortunate to be involved in bringing several products through clinical development, through global commercialization, with peak market sales projected At more than three and a half billion dollars. Over the last five years of my career, I've really turned my attention to cell therapies, which have a tremendous amount of potential, and yet I think one of the keys to realizing that full potential is coming up with fit for purpose. But. Development and manufacturing strategies, and that's what I really focus on, my attention on today as CEO of CTMC. CTMC is a joint venture between MD Anderson Cancer Center National resilience, where, with a differentiated model, we help biotech companies develop and manufacture their impactful cell therapy products and basically increase access to patients for those products. 

I'm sigma Mostafa. I'm Chief Scientific Officer for KBI biopharma in my role as CSO, I'm responsible for our cell line process development and all analytical services, that's about 40% of our business. And I'm also responsible for all of our new technical offerings, as well as digital service offerings. I have been with the company for over 15 years. My role right before I became CSO. Was a scientist for two of our largest sites, and being involved in clinical and commercial manufacturing, I have commercialized multiple drugs, as well as taken into clinic upward of 200 molecules. I started my career at Eli Lilly after finishing my PhD from Northwestern in chemical engineering. I was in Lily for about seven years, then with Mark, a subsidiary of Mark organ on biosciences, before joining KBI. Overall, my my expertise is in building and sustaining large technical and operational organizations and being able to bring key unique value proposition through those organizations.

 My name is Corey Smith. I work at trilink bio technologies, part of Marvi Life Sciences. Been at this company for six years now, working on the cdmo side. I've held various roles across the organization, but currently manage the GMP service or cdmo service portfolio at trilink, been working in the RNA field across a couple of different modalities for about 10 years now at innovator companies developing therapeutics, as well as now at the on the cdmo side, it's great to be here today

 On AI integration for novel therapeutic modalities. How are biotechnology experts evaluating potential partners for their AI capabilities in drug discovery, particularly around identifying and optimizing novel modalities? What are the specific data integration and validation challenges?

I'm going to pivot a little bit from discovery to more development, where I think there has been a lot of hype, as in almost every industry, about AI, we focus mostly on working with companies once they've gone through that early discovery point and have Clinical candidates, and need to bring those into the clinic and develop them through the clinic. And I think there's a really important role for digital systems overall in that, and they've this has been contemplated for seemingly for decades, but I think cell therapy is a modality where this digitalization, and in some ways you do, which is a adjacent to AI, is not a nice to have, but is like essential, and it's going to be a key driver going forward, with the difference being that with a lot of traditional modalities, whether it's small molecules or, let's say antibodies, the way we scale is we scale up and we make bigger batches, batches that can produce hundreds of 1000s of doses per batch. And so even for very successful commercial products, the number of batches you produce a year is fairly manageable, maybe on the order of 1050 and while those that type of production benefits from digitalization, It's not essential you can get by making 10 batches a year on on paper, based systems and looking at all that data on an Excel table and plotting it a couple different ways, but with cell therapies. Even for a phase one study, you're making 2530, batches. For a phase three study, you're making potentially 300 batches. And for commercialization, we're talking 1000s of batches, 10s of 1000s of batches a year. And so doing that in a paper based system is just not possible. And so the and yet, a lot of the. Industry hasn't like pushed that fully yet, and so the first phase is just getting this information to be digital instead of paper based. But then I think the really next important step, which is also critical, is integrating these digital systems to talk to each other. So for example, lots of groups have and they're utilized electronic Batch Records. You essentially have a screen, and it lets the operators put the information directly into a digital system, which is good, very important advance from paper. But still, that batch record typically doesn't connect into a LIM system, or doesn't connect into a training database, or doesn't connect into your ERP system for materials management. And so what we're doing, and really trying to push the envelope, is have a very integrated, holistic digital environment where, when that operator goes into the batch record and starts to enter in information, first, they'll check the training database and say, is that person qualified to run this step? Oh, no, their training isn't up to date. Then they can't even run it. Hey, they're scanning a barcode on a raw material before they bring it into the hood to add it to the to the cells. Is that material fully released? Has it met all its testing requirements? Yes. Okay, proceed. No. Oh, and I think why that's critical is this will start to rather than have a paper trail to document mistakes, will create a system that prevents mistakes from happening in the first place. And I think for for manufacturing, that is a critical difference, to preempt these mistakes, reduce quote, unquote operator error and the like. And then as we get all this information into digital systems, that's when we can start really utilizing AI to collect that data, analyze it, optimize it as we scale to 1000s, 10s of 1000s, hopefully hundreds of 1000s, of batches. So I know that answer is a little bit different than pure AI for discovery, but I think it's an under appreciated area that needs great solutions, and is still a challenging area, but is critical for the scaling of cell therapies.

So at a high level, when we are looking at building partnership with AI, different AI companies, one of the primary things to look at is, is their technology truly novel, and is it bringing value compared to others in the field, right? Because there are quite a few options out there. What we need to look at is the uniqueness of their technology, the data assets that they are using for their modeling, their actual R and D experience. Because oftentimes what happens is, biopharmaceuticals like us have a lot of data, and the AI companies may not have a lot of clinically relevant data, so what they're developing versus what you need, there might be a bit of a mismatch, right? So that proprietary data assets that they have is important, and during the due diligence process, being able to look at how they have done their scientific validation, the transparency of the data, how they can take multi modal, multi omics data and be able to incorporate in Their platform, what's the core IP, the scalability of the data sets and its applicability. Have they really tested it, how, how specific and obviously the accuracy of the data? Or if we are talking about particular biologics, we can even think about generative AI, which is now being used both in the CGT and in the biopharmaceutical side, for developing novel molecules with very unique attributes, right very targeted attributes. So being able to handle large volume of data, and in the proof of concept stage, being able to take, perhaps your data set and showing the actual value is very important. Otherwise, there is a gap in what the technology says it can do versus its application in your therapeutic field.

Now, in light of discussions surrounding MNA activity, what are the primary Manufacturing Technology? Integration challenges and strategic considerations for biopharma companies that are engaging in acquisitions or partnerships within the complex and rapidly evolving CGT landscape.

 I think complex is a great way to describe the CGT landscape right now, there are quite a few choices that developers need to make, both on the technology side and the modality that they're choosing, as well as the partners they choose, either on the manufacturing side or the technology side. One of the key first challenges, of course, is determining what type of editing or cell therapy technology you would like to use. You can look at in vivo editing technologies, your traditional CRISPR, CAS systems, you can look at ex vivo editing technologies or ex vivo cell therapies. Think cell engineering, car T or other ex vivo editing technologies both have risks and benefits. Both have significantly different aspects and roles that they play when it comes to partner selection. But the key thing here is that you want to choose a partner that is is certainly specialized and experienced on either side. You want to have a partner that's worked through the the difficulties of of ex vivo cell therapy manufacturing when it comes to the biologic side, as well as the drug substance or raw material manufacturing side, and for in vivo gene editing, you need to have a partner that really produces very, very highly pure product. Quality is key in the CGT space. Gene editing requires extremely so that you can safely and effectively edit your specific target and any kind of lack of specificity, whether that's on the technology side, so that the drug development side, or on the partner side, the manufacturing side, can have pretty drastic side effects when it comes to things like off target effects, unwanted editing in the patients and eventually, of course, clinical trial failures or major hurdles in clinical trials. So choosing the right systems from a technology standpoint is extremely important, but choosing the right partner as well is extremely important as well, and I think we really want to make sure that when we're looking at modalities and making choices as drug developers and cdmos, we have the right services to meet the needs of each specific market segment in the CGT space

 for manufacturing integration, I'll focus on those challenges first, and then perhaps on the strategic side, some of the key things is looking at scalability and proven track record around scalability. This is potentially more true for CGT, where a lot of the operations are manual, but even for therapeutic biologics, drugs, there are a lot of open operations and manual operations which integrating those technologies. If you have your own automation platform, etc, it is very important to understand if this is going to be a seamless integration or not, the quality systems, obviously, as well as the supply chain models and logistics for those manufacturing entities is going to be key factors to look at. Otherwise, the integration may lead to more headache than actually solving, solving your gaps right the regulatory experience of the entity, as well as the quality control. In other words, the testing that gets done are those similar is something that has to be looked at, because if you're completely using different tests or with similar products, getting different results, etc, integrating the manufacturing component would be very difficult in terms of strategic considerations, the due diligence and the technical assessment has to be extraordinarily robust. We know of many mergers where it ultimately did not give the efficiency, the time savings, the cost savings, because there were such differences in in the technologies, also in terms of the cultures of the companies, and the post merger integration portion is also very important in terms of how do you build Your strategic commercial plan so that you can execute and deliver on it a lot of times, the merger may be successful, but over time, having a fully integrated end to end plan is hard to develop, and again, differences in technology, automation, etc, may make it difficult, and you end up not being able to make it a success.

What is really interesting about cell therapy and in terms of creating partnerships, is, I think it up ends, or has the potential to upend, or if you want to, maybe to read more specific. Specific if you want to be really efficient in how you develop cell therapies, reconfiguring the traditional structures of partnerships can be very beneficial. So what do I mean by that? Right? Typically, there's a biopharma or biotech. They do. They develop a product, they hire a CMO to manufacture that product. They contract with different clinical sites to run trials for that. And the biopharma then hires a CRO, clinical CRO to, like, run those sites and to basically, you know, hires the CMO. They make a bunch of product, they ship it out to the pharmacy, and then, then they, you know, run a clinical trial. So that's what traditional modalities, right? We can store the product on the shelf and just take it off the shelf when you need it. With cell therapies, and especially autologous cell therapies, these trials are all on demand manufacturing. There's a different relationship between the clinical trial, because as you enroll the patients, you need to engage the manufacturer. And so you very arm in arm the manufacturing in the clinical site are arm in arm to the clinical study, as opposed to being decoupled in traditional manufacturing, traditional modalities like antibodies, and so as I was looking at this field, a lot of companies try and basically force this different kind of relationship, or this different kind of structure into the traditional partnership models. Okay, biopharma is going to hire a CRO and these and then, you know, to run an autologous clinical cell therapy trial. You know, every day of the week you're calling up your clinical sites saying, hey, when do you have patients? Oh, I have a patient coming in on Wednesday. Then that company is calling the CMO and saying, Hey, can you take this patient batch on Wednesday? Oh, no, we can't take it Wednesday, but we can take it Tuesday, going back and forth on the logistics of the trial with the biotech or right in the middle. And so one of the things that I think is an opportunity is to change that structure and have the manufacturing in the clinical very tightly aligned, and then providing that solution to a biotech. When a biotech comes to us with a new product, we say, hey, we can develop your process. We can manufacture that product. We can actually handle regulatory interactions for you too, and we can handle all the clinical trial logistics and operations for trials run in MJH. And so all of that will be transparent to you as a biotech, but you won't have to be involved with it. And so I use this as an example feliz of like a different way of arranging the pieces on the board to be more efficient for that biotech. And so they don't have to hire because we're doing this every day with mjhnderson and negotiating slots, and when patients can come, and when manufacturing lines up with clinical we handle all of that for them, as well as the shipping logistics and so that allows companies to be much leaner and capital efficient, because they don't have to build out all of this infrastructure to manage that whole operation. And so I use that as an example of, I think, in these new and advancing modalities really thinking from first principles about what the fit for purpose solution is, what is the what's the challenge, and not just defaulting for the way we've always done things with other modalities. And I think there's real opportunities there to streamline things and make things more capital efficient or time efficient, reduce risk and reduce costs. So that's overall what we look for, and when we figure out how to structure partnerships, is, how can we do all those things I just mentioned in order to increase value?

Now on vertical integration versus specialized manufacturing partnerships, given recent moves in the biopharma industry, how are experts assessing the benefits and risks of vertical integration versus specialized contract manufacturing partnerships to secure critical components and expand niche manufacturing capabilities within The biopharma supply chain?

So I'll start with the benefits of Article integration, right? Obviously, it gives you better control over the entire supply chain. It gives you better quality oversight across the value chain. Theoretically, it reduces. Is timeline and reduces cost, and it enhances the supply chain reliability. You are not dependent on some unique raw materials and you don't know when it will arrive, etc. Now the risks are usually it's very capital intensive and therefore substantial cost, as well as the overall exposure in terms of market volatility. This is more true for cdmos that look at end to end, versus having some specific areas that they're very good in because now you have married yourself to certain technologies. Let's say in context of antibody drug conjugates, if you are doing your drug substance production, but you are also doing your ligand production and your payload production, then you are married to that particular technology now, and the customers will come only based on if they want that particular technology, as opposed to creating partnership with a third party. So you have more flexibility, essentially. So there is more exposure if you don't have the demand for that end to end, and it has ultimately led to more hybrid models, I would say, for KBI, what we have done is we acquired a cell line provider selects is a premium cell line provider, and we create highly successfully. Were able to integrate them to create a shorter timeline while maintaining their unique culture in Switzerland, and they're very much R and D focus and yet integrate into our cdmo. On the other hand, when we looked at field finish, we decided to partner with equally technically good company, Argonaut, and we are looking at other partners as well, similar things for ADCs, I would say where end to end drug substance and the conjugation may be beneficial, but we are also seeing companies that are now focusing on just on the conjugation portion and not On the drug substance, whereas we bring in drug substance. So we are looking at a model, because we have lot of customers whose portfolio is changing to antibody drug conjugates to support them as they want to stay with us, we are looking at offering those services, but being able to also have partner do this through partnership, as opposed to a one stop shop.

The key, again, like I said before, with with the answer about how you arrange partnerships is, you know, really understanding what your pain points are, and then how to solve those and so, and where vertical integration matters, and where special specialization is more beneficial. And so, for example, for early stage development, when you want to bring a product into first in human testing, manufacturing and regulatory interactions are almost always on the critical path. How am I gonna get my ind in how am I gonna be able to start up my clinical trial as quickly as possible? And so, you know, for a typical cell therapy, there are a number of different manufacturing components that need to be brought together. For your typical viral based cell therapy, you need to secure plasmid, secure virus, figure out how you're made the cell therapy, put that all together in a regulatory filing, know where you're going to run the clinical study, and then put that all together in a package and get the clinical study up and running. So I think vertical integration of those activities for a standard. I think what's great about the industry now cell therapy, that really is only eight, nine years old. If you think about like the first commercial car T, is that we can say standard, standard cell therapy. It's no longer like totally new. So if we think about a standard car T or something, and you need to bring those components together. They really benefit from vertical integration. We see a lot of partners try and be in the middle again, of doing all of those and arranging all of those interactions that I just mentioned. And it just becomes hard for them to set up these, you know, for the first time, and for one off, I do think for those, some of those different components, as you move later in development and you have more time to plan and scale, is more important that say plasmid or viral vector manufacturing can be more more specialized sites. But I still. Think. And I'll take, if I, if you can indulge me, I'll take a little deeper dive on the relationship between the clinic and the manufacturing. I think will persist, not only through that and the benefits of arranging that properly, but will carry forward, not only through the first human study, but throughout clinical development, and even I would argue commercial development, one of the big debates in Cell Therapy fields is decentralized versus centralized manufacturing. And I think what we're right now, where we are, is a lot of centralized manufacturing. You know, there's one or two big sites for the commercial products, and that's how they're produced. There's a lot of initiatives, mostly coming out of academic centers, of trying to do some small amount of manufacturing very locally, because cell therapies will always have this special relationship between the patient and the manufacturing, because each batch is made for a particular patient in really in a very unusual circumstance, the patient is the source of the starting material, and so taking that into account, when you shape the supply chain, really seems fit for purpose right now, and you can only do that when you move away from centralized manufacturing. So what we have now currently with commercial the main commercial cell therapies, centralized manufacturing, distributed raw material supply, basically the patients are everywhere, literally everywhere in the world and ship their products to a center, ship that starting material, the patient's blood, often to a centralized manufacturing facility that then does the manufacturing, and then ships it out to every place in the world for on demand manufacture in real time, where the patient, you Know, for oncology, doesn't have that much time because their disease is so severe, typically at this stage. And so to me, that's like using our traditional approaches to try to solve the current challenges in cell therapy. And I don't think it's fit for purpose. I think long term, what will be successful is a relationship between a regional manufacturer and various clinical centers, and that then sponsors or commercial suppliers will basically tap into these regional networks and say, for example, this manufacturing site already has a relationship to produce cell therapies for let's, I mean, let's just use it, since it's in my background for the Texas Medical Center, where there's more patients treated in this area than any other geography, small geography In the world, and there'll be a regional manufacturing that will have a short supply chain, short transit time, and a pre existing relationship with those hospitals. And I think long term, that's a different kind of supply chain shape than it for traditional where, again, the biopharma is sort of in between, and the hospital never really interacts at all with the manufacturing site. I think these manufacturing sites will almost turn into cell therapy pharmacies, where the doctor, rather than ordering up something from the pharmacy, will just say, hey, I want to prescribe this cell therapy for my patient, and I'm going to basically order it from the manufacture, the local manufacturing facility. I think long term, you know, that's not going to happen next week or next year, but long term, I think having the supply chain built in consideration of the raw materials for the patients will be the long term solution for Cell Therapy, which is very different structure than what a lot of people envision, and definitely different than how other modalities are typically supplied,

 build versus buy, is often the number One question a near clinical phase or a late stage pre clinical company will start to ask themselves, what mainly goes into this is oftentimes a risk based approach. From a CMC perspective, there is obvious benefit in owning your supply chain upfront, right, in having control over your your raw material inputs, or your drug manufacturing. But of course, it's extremely expensive standing up GMP manufacturing is a very, very expensive and, quite frankly, often risky business to get into. So that's why people do often turn to cdmos, right when you look at early phase clinical companies and think, you know, biotech and biopharma companies that I. Have a very strong candidate, but are looking for funding or support on the manufacturing side using a well established cdmo is, is a very nice option to reduce your risk from a financial standpoint when it comes to building out manufacturing or or, of course, buying companies that are doing the manufacturing while kind of partnering with a company that has good quality systems, a well established manufacturing platform and an area that really can help support some of the difficulties of of GMP manufacturing or clinical manufacturing. And so you can think companies that that maybe have a few early phase assets, there's always the risk of building and spending quite a bit of money that could be spent elsewhere without the Surefire thing of having a clinical success and a commercial success. So cdmos really can step in and help support that right. We can help support the the infrastructure needed for GMP manufacturing and help reduce some of the financial risk that's associated with building out or buying through M and A parts of the supply chain that you currently don't control.

Now, I feel that one thing we perhaps do not look at too closely are the partnerships that are on strategic licensing, especially when those deals are based on foundational technologies. So from a biopharmaceutical technology perspective, what are the key technical and intellectual property considerations when entering into licensing agreements for platform technologies that impact the fundamental properties of the advanced therapeutic that is in development or that will be moving towards commercialization

With these advanced therapies, especially cell therapies, a lot of the innovation goes on in the engineering aspect. You know, how you structure the car? What other elements do you put on when you try and armor the car? But you know, you think like an armored car is like one of our more advanced things, or even a logic gated car that may have two different binders, and there's some logic between those. So most you're expressing like, three different proteins, and those are pretty complicated, and yet, what's really interesting about cell therapy is you're putting those into a vehicle of a T cell that is expressing many, many, many orders of magnitude more proteins there, you know, 10,000 different proteins, all regulated in different ways. And clearly, how you grow those cells, how you do the engineering. One little aspect that we can look at is that aspect that we've engineered, and we're starting to get better tools at looking at the rest of the scaffold, essentially, that you're attaching that car to. But it has vastly more impact on the efficacy of that treatment, the safety and the efficacy profile of that treatment than for other modalities, like, for example, we're making a capsule, okay, yeah, sure. We're going to take some powder, take an API, and that API is going to have a certain structure and everything, we're going to lyophilize it and then, but then we're going to put it into a capsule. That capsule probably has very little to do with the overall efficacy of the product. You know, maybe, let's say, 5% 2% you know, an antibody. You know, when you have the basic backbone of an antibody, it's really this CDR domains that are the binding domains that confer the real efficacy and safety profile of that but for cell therapies, it's really bringing these two components together. And there's a huge amount on the scaffold, if you will. And so for companies, oftentimes their technology is focused on the engineering component, yet finding partners who have a really solid like you said I liked your word you used about foundational technologies, how to produce things. So you know one thing, the most clear example, maybe at least a clear example in cell therapy is actually tills. Car TS get a lot of play, but tills, which the first commercial till, was approved last year, these are tumor infiltrating lymphocytes. I think it's undeniable that how you produce the tills is equally, if not more, important than how you engineer them. And so there's been a number of different approaches on how to engineer those cells, but for those companies to partner with, you know, it's hard for them to build both of those capabilities in house, to be like, Hey, we were going to develop a best in class till manufacturing process, and we're going to have all this understanding and know how around an IP, around an engineered the engineer, and so where we've seen the most success is companies who focus on the engineering aspect, have IP around that, and then, you know, partner with companies so that that scaffold does justice, to be honest. To how you engineer the product to give you the best safety and efficacy profile. And I think we've seen examples companies who actually have really great engineering but haven't paid as close attention to the scaffolding and have said, like, oh, we could just do that ourselves too. Those products have failed. Like, there's been a little bit of a graveyard of specifically, tills in the field. And we don't honestly know, is that because that engineering wasn't the right engineering to do and didn't have the desired effect, or was it the platform that they chose to bolt their engineering on top of my overall advice to companies is figure out where your expertise is, you know, and if you're really, if your expertise is really in the engineering aspect of it, the construct, then, rather than trying to do it all yourself, find a partner who has that foundational technology so that and That's clinically validated, so that then your engineering aspect can demonstrate its full potential. So

I'll start with the technical aspect of licensing. So ideally, there would be a proof of concept study to demonstrate the value of the technology, the reproducibility of the technology, the scalability, manufacturability, the analytical methods that gets used with the technology is also very important. An example would be, oftentimes, one test we offer that customers for using a V's come to us for is analytical Ultra centrifugation testing to look at field versus empty capsids, and this kind of very unique testing is needed to know if the technology you are using to create the capsids is good or not. So when you are evaluating a technology for licensing, knowing how good the analytical methods is and the data you are seeing is really going to translate to larger scale is very important. The overall product, quality, safety, platform, adaptability, when you are looking at for your disease, indication, therapeutic area, etc, is also very important, IP wise, obviously, freedom to operate, we need to understand and internationally, both regulatory and legal landscape varies, so understanding the actual IP state of the Technology and being able to operate in different countries in the way you want to operate, if that flexibility is there is very important exclusivity or non exclusive licensing, understanding. Those are very important as well as one of the key things we see is as the technology improves from from the company that will licenses it out ownership and accessibility to the upgrade of the platform. Where does that reside? If you are licensing in the technology, do you get the upgrade as well? Is also important. In our case, we license our select System line technology, and we see licensing as a process of creating long term partnership. So our model is not just the licensing as a only step, but longer term support of our partners. And that also has built in some incentives for the partner to work with us for clinical and commercial manufacturing, yet the partner has full flexibility. However, they want to do the cell line development using our technology.

How do you balance the tension between being a one stop shop and being a specialist?

 It's a great question. You know, there are several aspects of the one stop shop that are seen as highly preferable. You can combine contracting, you can combine quality systems. But I think the reality of what we've seen is that often in these scenarios, it ends up not being as one stop shop, as folks think. You know, it is extremely important. And we have decided that there are, there are parts of the supply chain when it comes to CGT manufacturing that are extremely important to focus on at trilink and MJH, we focus on the drug substance part, and our goal is really to provide the highly pure drug substance, whether that is guide RNA or an mRNA to fit into the CGT workflow, and we feel that that is the area, one of the areas that is extremely important for understanding whether or not your therapy will be successful. Now we totally recognize the one stop shop area, and so we've done quite a bit of diligence in partnering with other companies externally to make sure that we can facilitate the rest. Of the supply chain. And so that's kind of the key here is that, you know, we have these partners in the industry, and these are very strategic decisions to make sure that we are appropriately not only providing the singular solution of what we manufacture, but we're providing a net of solutions for for our partners and our customers. So, you know, really looking at this across the board? Yes, there is, there is something to be said about the One Stop Shop mentality. There's also something to be said about building a network of the suppliers out there and then providing that as a singular solution as well. And we think that that gives our customers and our partners the best shot for success. Really, right is is getting the best out of each area. So whether that's the best drug substance manufacturer paired with the best drug product manufacturers, we want to provide an ecosystem that really fits that bill, rather than getting a total jack of all trades approach.

Well, that's all the time we have. Thank you to our speakers for being on today's episode and sharing their insightful perspectives. I'd also like to thank our sponsors, biovectra, Ecolab, Eppendorf, Fujifilm, biotechnologies, lab Vantage solutions, the parenteral Drug Association and piramal pharma solutions, for supporting today's episode. You can catch all our drug digest videos@www.pharmtech.com thank you for watching until next time.

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