Behind the Headlines Episode 27

Ask the Expert

Small Molecules, APIs, and Excipients—Trends, Challenges, and Opportunities

Drug Digest September 2025

Artificial intelligence, machine learning, and novel instruments are helping drug developers.

Enhancing Bioanalysis and Drug Development with Advanced Tools and Technologies

J.P. Morgan Report Lists Biologics, Obesity, China

Top Trends Reshaping Pharma R&D

Feliza Mirasol is the science editor for 

Mechanistic models and hypothesis-driven strategies generate optimized efficient solutions for drug development, says Catalent’s Nathan Bennette at AAPS PharmSci 360.

Shifting from Trial-and-Error to Rational Design Drives Efficiency in Pharmaceutical Formulation

American Association of Pharmaceutical Scientists

, director, Scientific and Technical Advisory, Catalent Pharma Services, discusses a paradigm shift toward rational design—a method grounded in conceptual and mechanistic modeling. According to Bennette, the rational design approach brings clarity and efficiency to the development of new drug 

Instead of the traditional trial-and-error method, Bennette advocates a structured approach. “The rational design concept is to use models—conceptual models and mechanistic models—to develop more focused hypotheses and then targeted experimentation to more efficiently get at the solution,” he explains. This shift begins with the creation of conceptual models to understand the problem in depth, followed by mechanistic (quantitative or mathematical) models that reveal the fundamental physical and chemical processes at play, he explains.

Semi-empirical models, often realized via computer simulations, Bennette notes, further refine hypothesis testing and solution optimization. Bennette shares a recent example in which his team faced a drug with poor oral absorption. Through 

 experimentation, the team isolated the rate-limiting step—diffusion across the unstirred water layer—and designed formulations specifically to enhance that process. Bennette notes that the 

How are rational design models transforming pharmaceutical problem solving?

Bennette believes this efficiency-first mindset yields tangible industry advantages. “If you can come up with these really focused hypotheses and work on those problem statements, you get there faster. You get there with less expenditure of time and energy and resource, and, ultimately, I think you come up with a better product,” he says.

Bennette adds that, as pharmaceutical companies face mounting pressure to deliver innovations with speed and efficacy, rational design frameworks promise to shape industry standards for problem solving and formulation optimization.

Nathan Bennette, Director, Scientific and Technical Advisory, Catalent Pharma Services

Bennette is a subject matter expert on establishing developability and non-parenteral formulation strategies for poorly bioavailable molecules, including protein degraders and others described as “beyond rule of 5”. He has worked in drug development for over 15 years in a range of technical and leadership roles and has broad experience with formulation of small-molecule therapeutics. Bennette applies his passion for mechanistic understanding of drug delivery to design systems tailored to each molecule and target product profile, utilizing a range of oral technologies such as amorphous solid dispersions, controlled-release platforms, nanocrystalline formulations, multiparticulates, and lipid-based systems. He has experience working across the entire drug development lifecycle from preclinical and early phase development to late phase clinical studies and commercialization.

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, Nathan Bennette, I work in our scientific advisory function at catalent pharma solutions, and my role there is to be sort of an in house consultant working with customers to define the problem statement and develop technical strategy for formulations.

So in sort of traditional problem solving and pharma development and formulation and process development in particular, a lot of times, we have historically done a lot of trial and error, where you form a hypothesis, but then you run a large number of experiments trying everything under the sun to develop a solution to the problem. The rational design concept is to use models, conceptual models and mechanistic models to develop more focused hypotheses and then targeted experimentation to more efficiently get at the solution.

The question, it's principally around efficiency. Those trial and error experimentation methods require huge amounts of effort and to arrive at a robust solution eventually. But these mechanistic, driven, hypothesis, driven experiment designs allow us to use the best practices in science to build out our understanding of the system and more efficiently come to a more optimal solution.

I think of it in sort of three layers. First, you have conceptual models, you have to form a picture in your head of what is actually happening in the system that you're studying. Once you've done that, you can start to form a real hypothesis about what might be going wrong with your with your molecule, for example, as you're trying to develop your formulation, all formulation development is a problem solving exercise, and it's important to know what problem you're trying to solve. So this conceptual model allows you to have a framework for forming a hypothesis. Then there's another level that I call mechanistic models. Some people call them quantitative models, mathematical models. These are the basic physics that underlie the physical situation of your drug molecule and the question you're trying to answer maybe it's from an absorption perspective or from a stability perspective. And so once you have your quantitative mechanistic model, you can start to form a more specific hypothesis. How fast does this process happen to? What extent can we expect this process to proceed. And then finally, we have sort of empirical or semi empirical models where that mechanism and concept have been reduced to an actual computer program, and you can run simulations. So these tools are all available for a range of different questions that are relevant to pharma development, like pharmacokinetic absorption or chemical stability or process modeling for different pharmaceutical manufacturing processes. So we use the starting from conceptual to mechanistic to semi empirical models. We use this whole framework to describe the problems that we're trying to solve and develop actual formulations to resolve that.

I have a really good one from recent work that does both. It helped us to get much more quickly to an optimized solution that actually we tested it out in vivo, and it worked really well. So we were developing this compound that had very, very poor oral absorption. And we asked the question first, why? And we started with the conceptual model that every molecule has to get into the GI tract. It has to dissolve it then has to diffuse across the unstirred water layer, up against the epithelium and then partition across the epithelium to get into systemic absorption. So that's our conceptual model. And we asked, Well, why is this molecule having a hard time doing that? What? What is the fundamental rate limiting step? And we learned through a series of in vitro experiments that the rate limiting step was diffusion across that unstirred water layer, the mucus layer. And so with that in mind, we didn't, we didn't go out and try every formulation concept under the sun that would be a trial and error approach. Let's try this. Let's try this. Let's try this. We said, Okay, we know the key problem is diffusion rate. So what formulations can we develop that enhance the diffusion rate? Because that's the key step. So we went in the lab and we developed a few formulations that we proposed would help with that, and we tested them in vitro and demonstrated that they did, in fact, enhance the diffusion rate. And then we took the best of that set into an in vivo study. And what was really cool was that the extent to which. We enhanced diffusion with those formulations, in vitro correlated very well with the in vivo enhancement factor as well. So we saw, we figured out what the right problem was. We developed a conceptual framework for how to resolve that, and we went and tested that specific hypothesis, and much more quickly, much more efficiently, came to a workable solution.

I think I've been hitting a lot on the efficiency, the efficiency of the process of coming with a workable formulation. I think that translates to faster timelines if you're if you're spending enormous amounts of time trying everything in order to find the one thing that works. Then you spend a lot of resource. You spend a lot of time working on stuff that isn't isn't going to be the answer. But if you can come up with these sort of really focused hypotheses and work on those problem statements, you get there faster. You get there with less expenditure of time and energy and resource and ultimately, I think you come up with a better product. It's a it's a more optimized outcome.

Videos

Patrick Lavery is an Editor for the MJH Life Sciences brands 

. Previously at MJH, he filled the same role for 

3D rendered blue laboratory test tubes with red positive results | Image Credit: © mguido - stock.adobe.com

Drug substance testing is a critical component of the biopharmaceutical analysis process, carrying with it inherent benchmarks of safety and efficacy that must be met. In an exclusive interview with 

, summarizes the current trends in this field and how ever-evolving regulations, as well as technologies, are moving companies forward toward greater accuracy and dependability for patients.

 Have there been notable regulatory changes in drug substance testing that have affected processes or quality issues? If not, are any expected?

 I think we are seeing four key areas of focus—it’s probably not so much about change; it’s more about concentrating on those aspects. Clearly, data integrity is a significant topic, and all agencies worldwide continue to stress the importance of data integrity throughout the lifecycle of drug substance testing. Impurity characterization and control remain significant topics of discussion. There is a trending focus on more thorough characterization of impurities, stricter controls, and an increased emphasis on understanding potential genotoxic impurities while establishing appropriate limits. Therefore, I believe this is a key focus area.

Stability requirements are evolving and being continuously refined; there’s a progression in the expectations concerning that data, necessitating support for that data, as well as support for retest periods and shelf life. And then, a higher emphasis on process understanding and control strategies. There is a clear drive toward a deeper understanding of the manufacturing process and the establishment of robust control strategies. I believe none of this is revolutionary or sweeping; however, I feel that all of these areas are worth focusing on. When we look ahead, I believe we will clearly see advanced analytical technology on the horizon. Therefore, we can expect more emphasis on the use of advanced analytical technologies like mass spectrometry and spectroscopy for improved characterization and real-time monitoring. Regarding process understanding and control strategies, advanced methodologies will certainly increase focus in that area. We can anticipate a greater emphasis on sustainability and greener technologies overall, alongside a stronger focus on sustainable manufacturing practices—we have also started to implement our My Green Lab certification in this context—along with new approach methodologies, NAMs.

In certain fields, particularly for safety testing, there is already a push to lessen reliance on animal testing. We have observed government agencies signing orders related to this and adopting new approaches. While this is more advanced in direct product testing, we may see a gradual effect on certain aspects of drug substance testing in the long term. We’ll see how this develops, but we all need to stay attentive to that progress.

Finally, with the massive cuts currently occurring at FDA under the current administration, there is reason to be concerned regarding how FDA approaches its regulatory oversight of drug substance testing (and everything else for that matter). It would not be surprising to see FDA slow down and/or become more conservative over the next 12–18 months, as it adjusts to lower headcount and support within the agency. Innovators would be wise to interact with the agency as early as possible and stay abreast of ongoing regulatory trends as the field adjusts to the new normal.

Have newer modalities caused any shift in previously standard analytical methods or procedures

We definitely see an increased emphasis on biological assays. Traditional methods often relied on physicochemical characterization, such as HPLC [high performance liquid chromatography] and spectroscopy. Newer modalities, including cell therapies, gene therapies, complex biologics like ADCs [antibody-drug conjugates] or bispecific antibodies, and importantly, peptides and oligonucleotides, necessitate a much greater focus on biological assays to assess potency, efficacy, and safety. For many of them, it’s even a question of how to best define potency and how to test efficacy on an ongoing basis.

We also observe enhanced characterization techniques. The complexities of these new modalities demand more sophisticated analytical methods for comprehensive characterization. For example, peptides, though smaller than full biologics, require rigorous analysis for sequence confirmation, impurities (e.g., related substances, residual solvents), and chirality. Techniques like mass spectrometry are essential for precise molecular weight and sequence verification, while advanced chromatography is used for separation and quantification of minor impurities. Looking at oligonucleotides (like siRNAs [small interfering RNAs], antisense oligos, and aptamers), these are complex synthetic polymers that require specialized methods to verify length, sequence fidelity, and the presence of modifications (e.g., phosphorothioate linkages, 2'-O-methyl groups). Techniques such as capillary electrophoresis and hybridization assays are crucial here, in addition to highly resolving liquid chromatography and MS. Additionally, there is an emphasis on impurity profiling specific to each modality.

Newer modalities often differ significantly from those of small molecules. We now need to factor in aspects such as process-related impurities, vector-related impurities (for gene therapy), cellular impurities, and also synthetic impurities and truncations that are characteristic of peptide and oligonucleotide manufacturing. Furthermore, we are witnessing the emergence of rapid in-process testing methodologies, which facilitate obtaining test results in real-time and potentially allow for process modifications based on those results. For some newer modalities—particularly cell and gene therapy—with short shelf lives or autologous nature, there’s a growing need for rapid testing methods that can provide quick turnaround for critical quality attributes. This need is often balanced with the highly accurate and specific testing required for oligonucleotides and peptides to confirm purity and identity before final release.

And the last thing I’d like to mention is increased regulatory scrutiny and comparability. That’s clearly an item that we have seen FDA pushing back on submissions in the past. When manufacturing processes for these complex modalities change, or when we have tech transfers, new plans, and so on, demonstrating comparability becomes increasingly critical. This applies across the board, from cell therapies down to synthetic peptides and oligonucleotides, to ensure product quality and patient safety. Rigorous analytical testing is essential, as nobody wants to repeat clinical studies for manufacturing changes. Therefore, comparability capabilities and evidence become more important.

How is artificial intelligence (AI) factoring in, now and in the future?

I firmly believe that AI, in the long run, will play an important role in revolutionizing the industry and lead to better outcomes at all levels, whether it’s yield, right-first-time, speed of tech transfer, the reduction of wet lab work necessary to develop a process, the number of tests ultimately needed to confirm quality, or overall productivity. These are just a few areas where I, or we as a company, believe that AI will significantly change our lives. We are currently in the early stages, like many others.

The most important prerequisite for AI is digitalization, and we are still working in some areas to ensure that everything currently available on paper is converted into data so that AI can truly leverage it. I think the most important aspect of AI deployment is that people understand the benefits of the specific use case for each project. You should not pursue AI for its own sake, but there are already excellent use cases available that can enhance regulatory compliance, improve quality, and shorten development cycles, and we will see more of those in the future. AI has the potential to significantly accelerate process characterization by identifying complex patterns across large datasets that are often too nuanced for traditional statistical methods. For cell and gene therapy, where variability is high and sample sizes are small, machine learning can optimize parameters like transfection efficiency, vector yield, or cell expansion conditions by correlating input variables with critical quality attributes. Ultimately, this allows developers to refine processes more efficiently and with greater confidence, reducing development timelines and improving product consistency.

So yes, AI usage will continue to grow. It is in its infancy and will undoubtedly drive adaptation and revolution in the industry going forward.

With tariff policy changes in the United States, are there hurdles between countries that must be overcome to ensure accurate, equitable testing?

I don’t think there is necessarily an impact to the testing out of the tariff situation ... Right now, [we] always assume that shipping samples would be exempt from any tariffs. But again, the situation is fluid, so you never know. But let’s assume that there’s no impact on testing and analytical execution, if you will. What there will be an impact on is, eventually, testing costs—meaning, if certain materials used for certain tests are coming from a specific region which now has a tariff, then of course tests may become more expensive. I’m not sure how big of a role this plays in a bigger picture.

I think the impact of the tariffs to the raw materials for the manufacturing process itself is probably significantly bigger, and that’s clearly an area which we as a company watch. We are also looking into, what does it potentially do to our customers’ behaviors? And how much are they eventually altering their supply strategies? And how do we, as a service provider who already today has capabilities and capacities on the three main continents (being the US, Europe, and Asia), how do we continue to build up that network in order to meet the ever-changing requirements? So that’s clearly how we see it. The pace of those changes is exacerbating the complexity of policy implementation and mitigating actions, and we clearly see some long-term impacts. We see increased cost for materials and APIs. We see potential delays and disruptions in production. We see potential staffing constraints as manufacturing moves into regions which haven’t had so much manufacturing recently. We’ll definitely see a shift toward domestic or regional manufacturing. Pricing pressure from the customers, potential retaliation from other countries ... I mean, I think the impacts are manifold, and as a company, we’ll watch them, and we’ll do what we can, within limits of course, in order to ensure that we mitigate those issues.

What else do you see potentially impacting drug substance testing in the future?

I think what’s very important right now from my point of view is that we have seen, over the past year, significant changes in the dynamic of the advanced therapy market. And the outcome of many of those changes right now, from what we can see, is that companies have focused on the scientifically more promising assets. We also have seen significant advancements in, for example, analytical capabilities, the ability to find a potency metric which is approvable by the authorities. Many of those advancements make us positive, in a sense, that we will see more clinical success rates going forward for the advanced therapies. And overall, while we have less assets in active development globally, we most likely see more of them being successful in getting licensed and becoming commercially successful, because companies were forced to go through a very rigorous process to assess their portfolios for future marketability and for scientific advancements. And I think that has happened, continues to happen to some extent, and we will see this lead into the next wave of advanced therapies on the rise.

Articles

Drug substance testing is crucial in biopharmaceutical analysis, ensuring safety and efficacy. Current trends emphasize data integrity, impurity characterization, stability requirements, and process understanding. Advanced analytical technologies like mass spectrometry are gaining importance. Newer modalities, such as cell and gene therapies, require sophisticated biological assays and rapid in-process testing. AI is expected to revolutionize the industry by enhancing regulatory compliance and process efficiency. Tariff policy changes may impact testing costs and supply strategies. The advanced therapy market is focusing on scientifically promising assets, potentially increasing clinical success rates.

Quality, stability, sustainability, and the increased and thoughtful integration of artificial intelligence are foremost in the minds of those on the leading edge of testing trends.

How Therapeutic and Analytical Advancements Help Drug Substance Testing Evolve

At AAPS PharmSci 360 2025, held from Nov. 9–12 in San Antonio, Texas, Corey Bloom, PhD, associate director, CMC (chemistry, manufacturing, and controls) and Bioavailability Enhancement at 

, gave a presentation titled “Amorphous Solid Dispersion Development for Straightforward to Challenging Compounds.”

Here, Bloom answers some questions about key points in his talk at the conference.

How important is selecting the appropriate drug delivery technology to address low solubility compounds?

Today, compounds with low solubility or low bioavailability are becoming the rule rather than the norm, as around 90% of preclinical compounds are now estimated to have bioavailability challenges. This is the result of more new chemical entities with complex needs entering drug development pipelines.

Low solubility during the earliest stages of drug development creates significant challenges for small and emerging biopharma companies. Therefore, it is crucial to choose the right formulation and process strategy early on to maximize a compound’s chances of progressing through clinical trials and achieving commercial manufacturing success. An optimized formulation and process can streamline development, while a less effective approach may lead to longer, more complex development timelines or even unnecessary failures.

What approaches to formulation and process development do you recommend?

Careful selection of the right technology to enhance bioavailability is essential in development programs from initial preclinical phases to commercialization. A science-based technology selection process is presented, based on a series of inputs including the target product profile, drug properties, extensive past project experiences, technology maps, and absorption modeling.

 tools to predict how certain compound properties are expected to impact performance and thus provide measurements of key drug physicochemical properties to guide technology selection. We then review the target product profile to define the goals, including dose, pharmacokinetic profile, and image.

We then use biomodeling tools to help define the problem statement and evaluate solubility, dissolution rate, and permeability. One approach is leveraging physiologically based pharmacokinetic models to evaluate hypotheses about barriers to absorption, whether that is dissolution rate, solubility, and/or permeability. A formulator can use absorption modeling to understand existing 

 data for a formulation of interest or establish a framework for predicting 

 data. These models may also be useful for predicting specific formulation attributes from enabled formulations (e.g., amorphous solid dispersions, lipid-based formulations) such as how specific drug species may contribute to absorption.

Through these processes, we can collaborate with drug developers to select the most appropriate high level formulations approach and optimize the formulation through 

Why do amorphous solid dispersions have such a breadth of applicability?

Amorphous solid dispersions (ASDs) can provide optimal performance and stability for compounds with a fairly wide range of properties, including lipophilicity, melting point, and pKa. By liberating the API from a crystalline lattice and including concentration enhancing excipients, ASDs can increase drug solubility up to 10-fold relative to crystalline API. These improvements facilitate dissolution in gastrointestinal (GI) fluids and optimize the quantity of drug that enters the bloodstream. This boost in oral bioavailability holds the potential to enhance patient outcomes by reducing variations in plasma exposure, lowering required dosages, and mitigating the impact of food intake and GI system conditions in specific patient populations.

Enhancing bioavailability through ASDs can be achieved through hot-melt extrusion (HME) or spray drying. The drug product's API properties and stage of development are important factors to consider when deciding which technique to use. HME offers the advantages of mature process understanding, a small process footprint, continuous operation, and ready scalability. These attributes can enhance the flexibility of the unit operation, resulting in relatively lower manufacturing costs and a more appealing commercial process train. HME is also a solvent-free unit operation that can eliminate concerns about solvent impurities while enabling sustainability.

Another technique is spray-drying dispersions. This method is suitable for a wider range of APIs and dispersion polymers because the API and excipients are dissolved in a volatile organic solvent. Additionally, spray drying does not require melting of the API to expose the API to excessive heat during the production of the amorphous dispersion. It can also be scaled down, allowing formulation screening with smaller amounts of API.

For challenging compounds, what are some best practices for spray dried dispersion processes?

Challenging compounds have low solubility in preferred volatile solvents, and/or propensity to crystallize during manufacture. For these compounds, it is essential to develop a preclinical to late-stage and commercial production roadmap to improve bioavailability. This includes starting with a target product profile before developing formulations in a phase appropriate approach to match the development phase of the drug candidate. Drug manufacturers can leverage a full range of spray dryers, based on the required scale and process needs, to support feasibility assessments through clinical studies and commercialization.

There are also several factors to consider throughout the process. Specialized process improvements including temperature shift or processing aids can enable manufacture of difficult compounds. Further, the science of scale to evaluate key process variables early in development and translate them into full scale development can help save time, money, and use of APIs from more trial-and-error approaches.

How can these methods help save both time and materials?

During the initial stages of drug development, the primary focus is on achieving optimal performance and moving the drug into clinical trials as quickly as possible. As the drug advances through clinical trials and approaches commercialization, considerations such as cost, production efficiency, and sustainability become increasingly important.

Partnering with a contract development and manufacturing organization that offers a range of formulation techniques and extensive experience with scale up and potential technical and logistical pitfalls is crucial for selecting the best development strategy. This collaboration helps ensure that an effective and stable formulation is established early, reducing the risk of costly delays and the need for reformulation later in the clinical pipeline.

Selecting the appropriate drug delivery technology is crucial for addressing low solubility and bioavailability challenges, which are common in modern drug development. Amorphous solid dispersions (ASDs) offer a versatile solution, enhancing solubility and bioavailability through techniques like hot-melt extrusion and spray drying. These methods optimize drug performance and stability, facilitating efficient clinical progression. For challenging compounds, a strategic roadmap from preclinical to commercial stages is essential. Collaborating with experienced contract development and manufacturing organizations can streamline development, reduce costs, and ensure effective formulation strategies.

Corey Bloom of Lonza outlines major points from his AAPS presentation, from drug delivery technology selection to the importance of CDMO partnerships.

At AAPS PharmSci 360, Solutions for Challenges in Amorphous Solid Dispersion Development

We highlight the week’s industry news in an easy-to-consume, fun format.

PharmTech Weekly News Roundup — Week of November 10, 2025

In this PharmTech video feature, we highlight the week’s industry news in an easy-to-consume, fun format. New roundups will drop every Friday, so be sure to come back each week.

Collectively, the week’s coverage discusses the pharmaceutical industry’s recent developments and current regulatory landscape. Read on for recaps of each story we’ve covered.

How are AI-powered digital twins revolutionizing drug discovery?

 to accurately forecast human lung function across numerous parameters, successfully revealing therapeutic effects missed by conventional preclinical studies. This methodology accelerates drug discovery by simulating the untreated outcome, directly supporting advances in precision therapeutics.

What is the relationship between AI and molecular dynamics?

 modeling incorporating artificial intelligence (AI) and molecular dynamics 

 for poorly soluble drug candidates, which represent a majority of compounds in development. This approach efficiently identifies optimal solubilization methods and excipients, minimizing reliance on time-consuming empirical screening.

What's the latest in instrumentation innovation for bioanalysis?

 like flow cytometry and polymerase chain reaction requires an 

, SOP-driven assay validation for regulated use, challenging existing guidance precedents. High-resolution mass spectrometry is increasingly utilized for quantitative bioanalysis of large molecules, including oligonucleotides and biologics, due to its enhanced selectivity and mass accuracy.

Is there a new approach to streamlining workflows to identify particulates?

A Six Sigma Define, Measure, Analyze, Improve, Control-based workflow 

 particulates using microscopy and spectroscopic analysis for efficient root cause analysis in biologics manufacturing. This integrated approach leads to timely process improvements, demonstrating how modifying shear stress from mixing can preserve solution homogeneity and product quality.

How do 3D-printed tablets impact personalized medicine?

 by allowing for personalized dosing and versatile release profiles. The technology successfully created a budesonide tablet with targeted delayed release to the ileum, validating its potential to significantly reduce 

How does blood-brain barrier-crossing technology tackle lysosomal storage disorders?

 of achieving therapeutic exposure in the central nervous system by efficiently crossing the blood-brain barrier. This focus aligns with the trend toward vertical integration in biopharma, combining R&D and manufacturing capabilities to accelerate rare disease timelines.

What's novel about an agitation model for biologics formulation?

 essential for assessing and preventing protein aggregation in high-concentration biologics. For early-stage testing, an orbital shaker with horizontal 2R vials provides a reliable, scientifically justified method for stress evaluation.

How does a personalized digital control arm work?

 by generating the hypothetical untreated effects for an organ receiving therapy. This innovation reduces reliance on large cohort analyses, minimizing the need for human organs as controls and potentially accelerating clinical trials.

Why does context matter in validating biomarker assays?

 rather than fixed criteria, given the variances in data purpose and the endogenous presence of the analyte. Nevertheless, essential performance metrics like accuracy, precision, sensitivity, and matrix parallelism must still be characterized to meet the intended data use.

Accelerated drug development insights using AI/digital twins, advanced bioanalysis, targeted delivery, and optimized formulation stability models.

We analyze a recent House of Lords report.

UK's Persistent Failure to Commercialize R&D Threatens Life Sciences

A report from the United Kingdom House of Lords Science and Technology Committee, titled 

“Bleeding to Death: The Science and Technology Growth Emergency,”

 highlights significant challenges that threaten the UK’s position in the global science landscape, particularly within the life sciences sector (1). While the UK maintains a globally competitive R&D base, it has been less effective at commercializing R&D, leading to a persistent failure for promising early-stage companies to scale up and remain domestically, according to the report.

The current state of the life sciences sector is presented as illustrative of a "lack of long-term thinking and coordination in government policy," according to an analysis by Resilience, the UK’s Medicines Manufacturing Centre of Excellence (2).

This situation has fueled profound negativity within the pharmaceutical industry, with key leaders suggesting that major pharmaceutical companies are signaling they are "out" and reducing investment (1,2). The urgency of addressing these issues is underscored by recent events, including Merck’s cancellation of its £1 billion (US$1.3 billion) UK research center, citing the UK as "not internationally competitive," and rumors of AstraZeneca upgrading its United States share listing (2). If the UK loses its life sciences expertise and major pharmaceutical companies, there could be substantial consequences for drug discovery, development, and manufacturing worldwide, a few of which are addressed in the following questions.

What other implications does this report suggest?

Beyond the imperative for coordinated policy and financial reforms, experts emphasize that addressing the UK’s decline requires fundamental investment in the talent pipeline (2). This ongoing requirement for workforce training is essential for enabling technological productivity gains and ensuring the life sciences sector can meet its future needs.

Science and technology companies, including those in life sciences, struggle significantly to obtain scale-up finance domestically once they move beyond Series A funding. This often leads venture-backed companies to seek funding from abroad, especially the US, where capital pools are deeper, or results in acquisition by an overseas buyer (1).

It is seen as critical to invest in attracting, engaging, and training future generations, as skills are considered the engine of growth that encourages companies to invest and innovate. Initiatives like Resilience are using advanced virtual reality technology to deliver training, which helps boost productivity, provides practical skills, and supports sustainability goals by reducing laboratory waste and expensive consumables (2).

Bleeding to Death: The Science and Technology Growth Emergency

; 2nd Report of Session; UK Parliament, November 2025.
2. Resilience—UK Medicines Manufacturing Skills Centre of Excellence. House of Lords Report Says Government Lacks Long-Term Thinking in Life Sciences, But Leading Academic Says the Problems Run Deeper. Press Release. Nov. 14, 2025.

To prevent catastrophic loss of expertise and investment, government and academic leaders say coordinated policy and significant investment in workforce talent are urgently needed in the UK.

UK’s Persistent Failure to Commercialize R&D Threatens Life Sciences: Report

FDA announced on Nov 06, 2025, the award of its second batch of Commissioner’s National Priority Vouchers (CNPV) pilot program recipients (1). This cohort adds six awardees, bringing the total number of voucher recipients to 15. According to the Nov 6 news release, the agency is committed to accelerating the review of products that address key national priorities. FDA Commissioner Marty Makary, MD, MPH, stated that the agency is "pioneering new ways of bringing these cures and meaningful treatments to the market faster" (1).

These vouchers are highly selective, granted only when the company agrees to increase affordability, domesticate manufacturing (as a national security issue), or address an unmet public health need (1). The core benefit is speed: national priority voucher holders will receive a decision within 2 months, a drastic reduction of the typical review timeline. This accelerated process includes a one-day “tumor board style” meeting, which brings together a multidisciplinary team of physicians and scientists for review. The FDA stated that is authorized to test these innovative regulatory approaches under acts like the 21st Century Cures Act (1).

In light of the pilot programs continued growth and potential impacts on the bio/pharmaceutical industry, we are conducting as survey of industry professionals. This is your critical chance to voice your opinions and professional insights on what the CNPV program means to you, your organization, and the industry as a whole. Participate today and help shape the conversation around innovative regulatory review!

FDA Awards Second Batch of National Priority Vouchers

The FDA has awarded its second batch of Commissioner’s National Priority Vouchers (CNPV), adding six new recipients and bringing the total to 15. These vouchers aim to expedite the review of products addressing national priorities, with decisions made within two months. The program requires recipients to enhance affordability, domesticate manufacturing, or meet unmet public health needs. The accelerated review process includes a multidisciplinary "tumor board style" meeting. The initiative is part of the FDA's efforts to innovate regulatory approaches under acts like the 21st Century Cures Act.

Take our survey to voice your opinions on the bio/pharma industry impacts of the FDA Commissioner’s National Priority Vouchers program.

Share Your Perspective on the Commissioner’s National Priority Vouchers Program

Brain neurons in lysosomal storage diseases, 3D illustration | Image Credit: © Dr_Microbe - stock.adobe.com

 a subsidiary of Abbvie, is collaborating with Italy-based 

 to leverage blood-brain barrier (BBB)-crossing platform technology to treat lysosomal storage disorders (LSDs) (1). According to a press release from Chiesi, the nature of the partnership is positioned to address challenging disease areas that have high levels of unmet need.

The worldwide, exclusive license enables Chiesi Group to develop and commercialize enzyme replacement therapies (ERTs) using Aliada’s proprietary BBB technology (1). The agreement builds on a collaboration, 

 that was intended to focus on multiple enzyme cargoes modified with Aliada’s Modular Delivery (MODEL) platform (2).

According to information provided by both companies at that time, the MODEL technology enables high therapeutic exposure in the brain, demonstrating advantages over competing approaches by offering a broad design landscape with an ability to optimize therapeutics for both central nervous system (CNS) delivery—many LSDs have CNS involvement—and downstream functionality (2).

How are company leaders welcoming the news?

“This agreement underscores our continued commitment to creating potential solutions that target the significant unmet needs in managing cognitive and neurological symptoms across several rare diseases,” 

 executive vice-president, Chiesi Global Rare Diseases, said in a press release (1). “These aspects of [diseases] are frequently underserved, yet they can profoundly affect patients and their families. By advancing this research, we intend to go beyond symptom management and potentially address the fundamental neurological burden directly.”

“We're proud to deepen our collaboration, propelling our partnership with Aliada to its next stage,” 

 senior vice-president, R&D, Chiesi Global Rare Diseases, added (1). “We're advancing therapies and opening the door to identifying therapeutic pathways for LSDs, supported by encouraging preclinical data. What truly drives us is the urgent call from patients and families to move beyond symptom management and directly address the unmet neurological burden. That inspiring call to action shapes our work every day."

What does this mean for the challenges of treating LSDs?

The partnership represents a strategic step toward overcoming one of the most persistent challenges in treating LSDs: effective delivery of ERTs across the BBB.

This collaboration underscores growing industry emphasis on molecular delivery technologies that bridge peripheral and CNS pathology. If successful, MODEL could provide a scalable approach to transporting biologics into the brain—an area where traditional ERTs have shown limited efficacy due to restricted BBB permeability (2).

From a manufacturing standpoint, Chiesi’s integration of this program into its Biotech Center of Excellence in Parma, Italy, may streamline the translation of these therapies from research to clinical-grade production (3). The partnership also illustrates a wider trend among mid-sized biopharma firms pursuing vertical integration—combining R&D, process development, and biologics manufacturing—to accelerate rare disease program timelines.

What else have these companies announced recently?

 which was reported to be a $1.4 billion cash transaction (4). In that announcement, AbbVie touted the deal as a boon to its neuroscience pipeline.

 the aforementioned Biotech Center of Excellence that is intended, according to a press release, to provide integration of the entire supply chain, developing and producing monoclonal antibodies, enzymes, and other proteins, combining those with research and industrial production capabilities (3).

Chiesi Group Enters into an Exclusive License Agreement with Aliada Therapeutics, a Wholly Owned Subsidiary of AbbVie, to Advance Blood-Brain Barrier-Crossing Platform Technology in Lysosomal Storage Disorders.

 Press Release. Nov. 12, 2025.
2. Chiesi Global Rare Diseases. 

Chiesi Global Rare Diseases Announces Co-Development Agreement with Aliada Therapeutics to Advance Blood-Brain Barrier-Crossing Platform Technology in Lysosomal Storage Disorders.

 Press Release. Aug. 15, 2023.
3. Chiesi Group. 

Chiesi Group's New Biotech Center of Excellence Brings the Future of Medicine to Parma, Italy.

 Press Release. Oct. 14, 2024.
4. AbbVie. 

AbbVie Completes Acquisition of Aliada Therapeutics.

Aliada Therapeutics, a subsidiary of AbbVie, is collaborating with Chiesi Group to develop enzyme replacement therapies (ERTs) for lysosomal storage disorders (LSDs) using blood-brain barrier (BBB)-crossing technology. This partnership aims to address unmet needs in treating cognitive and neurological symptoms of rare diseases. The collaboration leverages Aliada's Modular Delivery (MODEL) platform, which enhances therapeutic delivery to the central nervous system. Chiesi's Biotech Center of Excellence in Italy will facilitate the transition from research to clinical-grade production, reflecting a trend towards vertical integration in biopharma.

A worldwide, exclusive license is being granted to develop and commercialize enzyme replacement therapies using proprietary platform technology.

BBB-Crossing Tech for Lysosomal Storage Disorders at Center of Chiesi–Aliada Partnership

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

Scientist operating precision equipment for 3d printing or biomedical research, illustration | Image Credit: © pramestydwi - stock.adobe.com

IgA nephropathy (IgAN) is recognized as a significant contributor to chronic kidney disease and is a primary driver of kidney failure, characterized by progressive, chronic autoimmune damage to the kidneys (1). Effective treatment requires targeted intervention. Budesonide is the first treatment approved by the FDA shown to reduce the rate of kidney function loss in adult patients managing IgAN (2). The mechanism hinges on the drug acting locally on the terminal ileum to reduce the amount of IgA1 antibodies, thereby treating the IgAN. In parallel, three-dimensional (3D) printing is an emerging technology that offers innovative solutions for both patients and the pharmaceutical industry (3). This technology can greatly benefit drug product design by allowing precise construction of the structure of dosage forms. Furthermore, 3D printing facilitates patient-centric treatment, such as personalized dosing, accommodates the treatment of specific disease states or patient populations, and provides versatile release modes to meet clinical requirements.

For a study presented via the poster “3D Printed Ileum Targeted Tablet for the Treatment of IgA Nephropathy” by Xiaoling Li, PhD, professor/CSO at Triastek, Inc., at 

, held Nov 9-12, 2025 in San Antonio, Texas (5), Li and colleagues at Triastek, Inc—Zhaoyao Chu, PhD, scientist, Formulation Development; Aiming Ma, PhD, senior manager, Formulation Development; Lanfang Chen, PhD, senior industry analyst; Fenge Zhang, director, CMC; and Senping Cheng, PhD, founder and CEO—focused on designing a 3D-printed tablet specifically for budesonide delivery to the ileum, aiming to modulate the activity and numbers of B-cells.

A novel 3D-printed tablet was created using 3D microstructure design platforms. Fabrication of this tablet, which featured a coating sheet structure, was achieved utilizing melt extrusion deposition (MED®) 3D printing technology (4). To verify performance 

, X-ray imaging was used to track the gastrointestinal (GI) transition and subsequent budesonide release. Barium sulfate was incorporated into the formulation to serve as the tracking agent during the 

How was the delayed release successfully achieved?

Through the application of 3D micro-structure design coupled with MED 3D printing technology, a functional delayed-release tablet was successfully designed and fabricated. X-ray images captured during the study indicated that the drug release occurred at four hours, confirming the successful targeting of the distal small intestine. Crucially, a human pharmacokinetic study demonstrated a more consistent delivery of budesonide within the ileum when compared against a traditional targeted-release formulation of the drug (Figure). This enhanced consistency was confirmed by observing a measured decrease in the variability of both Tlag (lag time) and Tmax (time to maximum concentration).

 Adapted from: Li, X; Chu, Z; Ma, A; et al. 3D Printed Ileum Targeted Tablet for the Treatment of IgA Nephropathy. AAPS PharmSci 360 Poster Abstract. Accessed Nov 12, 2025.

What is the long-term impact on drug development variability?

The research validates that MED 3D printing technology and 3D microstructure design can be successfully leveraged to develop drug products with precise, desired release profiles targeted to specific GI locations. Ultimately, these 3D-printed, budesonide delayed-release tablets achieved a more precise delivery of the drug to the lower small intestine area, resulting in a significant reduction of 

Long-term Renal Survival and Related Risk Factors in Patients with IgA Nephropathy: Results From a Cohort of 1155 Cases in a Chinese Adult Population

IgA Nephropathy: Current Understanding and Perspectives on Pathogenesis and Targeted Treatment

3D Printing: Innovative Solutions for Patients and Pharmaceutical Industry

Melt Extrusion Deposition (MED™) 3D Printing Technology – A Paradigm Shift in Design and Development of Modified Release Drug Products

3D Printed Ileum Targeted Tablet for the Treatment of IgA Nephropathy

. AAPS PharmSci 360 Poster Abstract. Accessed Nov 12, 2025.

IgA nephropathy significantly contributes to chronic kidney disease, necessitating targeted treatments like budesonide, which reduces kidney function loss by acting on the ileum. The advent of 3D printing technology offers innovative solutions for drug design, enabling precise dosage forms and personalized treatments. A study demonstrated the successful creation of a 3D-printed budesonide tablet using MED 3D printing, achieving targeted ileum delivery and reduced in-vivo variability. This approach promises to enhance drug development by ensuring precise release profiles and consistent drug delivery to specific gastrointestinal locations.

At AAPS PharmSci 360, Xialing Li, PhD, says 3D-printed budesonide tablets achieve precise, delayed delivery to the ileum for IgA nephropathy, lowering in vivo variability.

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