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

Concept image of the six most common questions | Image Credit: © RTimages - stock.adobe.com

Editor's Note: 
Stay tuned for additional coverage and industry expert perspectives on how the CNPV program'

 ultra-fast review forces firms into a parallel execution mode, posting tomorrow. And check out "

How the FDA Commissioner’s National Priority Vouchers Reshape Manufacturing, Pricing & Global Strategy

Winners & Losers: What the First FDA Commissioner’s National Priority Vouchers Tell Us About Early Movers vs. Late Movers"

from our colleagues over at Pharmaceutical Executive.



The introduction of the FDA Commissioner’s National Priority Voucher (CNPV) pilot program in 2025 has ignited intense debate regarding the balance between speed and scientific rigor in drug review (1-4). The program offers an "unprecedented opportunity to reduce drug and biological product application or efficacy supplement review times from 10-12 months to just 1-2 months" (5,6) (Figure). FDA Commissioner Marty Makary, MD, MPH, championed this effort, calling it a “common-sense approach” that harnesses a "tumor board style" discussion to deliver "more cures and meaningful treatments to the American public” (6). However, experts in public health and regulatory policy (1-4), as well as several industry experts who we spoke with, warn that this acceleration may come at the expense of established safety standards and fiscal responsibility.

How are safety standards and independent regulatory scrutiny affected?

The most significant public health critique comes from those who fear that compressed timelines inherently increase risk. Doctors for America released a statement calling the CNPV program "a very bad idea," with "vague criteria" that "will endanger Americans" (1).

Dr. Robert Steinbrook, Director of Public Citizen Health Research Group, stated definitively: “The priority voucher program is not a ‘common sense’ approach as the FDA Commissioner claims, but a dangerous one” (1). Dr. Steinbrook cited research demonstrating that "when the FDA rushes to review and approve new drugs, there is a higher likelihood that these drugs will have safety problems after approval." He concluded that the CNPV program "will only be a boon for Big Pharma at the expense of the American public."

Furthermore, the fast-track nature is perceived to threaten external review mechanisms. Dr. Steinbrook also noted that the program "will likely bypass the agency’s advisory committee process that allows for outside independent input” (1). Echoing concerns about transparency and patient trust, Dr. Reshma Ramachandran, a member of the Board of Directors of Doctors for America, questioned: “How can patients and clinicians trust that drugs approved with one to two months of review are truly safe and effective?” (1).

What logistical and resource allocation challenges are introduced?

The CNPV challenges FDA’s long-established performance goals under the Prescription Drug User Fee Act (PDUFA), which commits the agency to reviewing priority applications within six months and standard applications within 10 months following the 60-day acceptance period (8). Achieving a consistent one- to two-month timeline necessitates a radical rethinking of resource allocation.

Rory Budihandojo, an independent good manufacturing practices consultant, questions the operational feasibility, stating it is "not clear logistically how the FDA can provide resources needed for this short/intense review without impacting other FDA review programs" in an interview with 

. He elaborates that this acceleration "may divert resources from the FDA’s regular standard review program to this expedited review program." This diversion could impact other crucial therapies, including those under the statutory Priority Review Voucher (PRV) program, which "expedite the review to 6 months instead of 10 months."

In a client alert dated Sept 29, 2025, David Dorsey, strategic advisor, and Stephen Holland, senior counsel, both at the law firm Brownstein, noted the logistical challenges of CNPV, stating that FDA’s Center for Drug Evaluation and Research and Center for Biologics Evaluation and Research already "struggle to meet certain PDUFA goals," particularly those related to meetings with sponsors, producing meeting summaries, and responding to follow-up questions within mandated time limits (4). These pre-existing struggles, wrote the authors, are likely to be "aggravated, by the resource needs of the CNPV program"(4).

A significant financial trade-off is the lack of a dedicated funding mechanism, according to Dorsey and Holland. Unlike the statutory PRV programs established by Congress, which require the payment of an "extra user fee on top of any other application fee to provide for the additional resources needed to conduct a priority review…, no similar fee would exist for the CNPV program," they wrote, indicating that this means the entire resource cost must be absorbed internally through reallocation (4).

What are the associated scientific and operational challenges?

To compensate for the compressed review timeline, the CNPV program requires sponsors to submit chemistry, manufacturing, and controls (CMC) information and proposed labeling at least 60 days prior to the formal application filing (5). This front-loading is intended to allow reviewers to begin analysis ahead of submission.
But Dorsey and Holland emphasize that this requirement introduces scientific and procedural challenges. “It is impossible to write and review a drug label without a thorough understanding of all the clinical trial data,” they wrote, adding that pre-submission labeling review may effectively ask reviewers to evaluate claims for which final clinical data are not yet available, “putting the cart before the horse.”
Operationally, the compressed timeline also raises questions about coordinating pre-approval inspections (PAIs), which are required for new products and manufacturing sites. Budihandojo questions whether inspection scheduling could realistically be compressed into the same 1-2-month window.
Aloka Srinivasan, principal and managing partner at Raaha LLC—who has helped a CNPV winner with their application and paperwork and is now getting them ready for the project—adds nuance in an interview with 

, stating that for many generics, especially non-complex sterile injectables, CMC work can occur months before filing, leaving bioequivalence as the only major outstanding issue. In such cases, she argues, the CNPV structure may support what is essentially a “first-cycle” approval based on extensive pre-submission interactions.
Still, Srinivasan emphasizes that companies must overhaul their development model to take advantage of the voucher. “The reduction in formal review time does not imply that product development, marketing preparation, or post-approval planning must also be compressed proportionally,” she explains. Instead, organizations must begin market access, pricing, supply-chain qualification, and labeling strategy in parallel with regulatory interactions rather than sequentially.
In an interview with 

, Metin Çelik, PhD, president, Pharmaceutical Technologies International, Inc (PTI), summarizes the shift in risk, noting that compressed reviews mean reduced iterative interaction with the FDA, which "places more pressure on a flawless first submission." The result is “more reliance on post-market commitments, including safety studies, registries, or [risk evaluation and mitigation strategy, or REMS] adjustments, because uncertainties cannot be resolved during the short review,” Çelik adds.

What are the sponsor organizational readiness and preparedness differences?

One of the clearest takeaways from the industry experts we spoke with is that the CNPV does not merely test FDA readiness, it tests sponsor readiness. The voucher only benefits companies that enter the process with mature governance systems, integrated quality risk management, strong digital validation capabilities, and robust pre-submission preparation (5).
Henrik Johanning, senior vice president, Quality & Strategy, Epista Life Science notes in an interview with 

 that compressed timelines “amplify every weakness in a company’s QRM framework.” He explains that risks can easily spill into manufacturing, supply chain, labeling accuracy, or post-market surveillance when iterative review cycles are shortened.
Drawing parallels to COVID-era emergency authorizations, Johanning argues that speed is possible, but only when supported by scalable digital documentation, disciplined cross-functional governance, and deeply integrated CMC and regulatory planning.
Çelik emphasizes that the compressed environment requires “integrated readiness war rooms” and that nearly all manufacturing and supply-chain readiness must be completed before filing. With only 30-60 days for FDA review, “there is no time to fix compliance gaps once the file is submitted,” he warns.

What are the discretion, incentive, and transparency concerns?

The discretionary nature of the CNPV award raises questions about the program’s foundation and ultimate incentives, wrote Dorsey and Holland. The CNPV award is "entirely discretionary and based on largely undefined criteria," they wrote (4).

Budihandojo suggests that the program transparency itself "might be in question; as this is based on the commissioner’s discretion and decision, it may be political based and not just based on science and public need." An industry expert with whom 

spoke and who asked to be anonymous, added that attempting to "define and demonstrate the elements" in the program’s parameters, such as to “increase affordability, domesticate manufacturing as a national security issue, or address an unmet public health need,” could be "open to interpretation." Eric Langer, president and managing partner, BioPlan Associates, also notes the "complexity for drug innovators trying to gamble on demonstrating" these elements, in an interview with 

Dorsey and Holland highlighted that, unlike the statutory PRV programs for which the sponsor knows the criteria and the transferable value (vouchers have recently sold for about $100 million), the CNPV's value as an incentive is questionable (4). Because the award is discretionary and occurs late in development, it is "hard to understand the CNPV as incentivizing anything," especially early development decisions like manufacturing location, they stated (4). The non-transferability (7) and the requirement to use the voucher within two years (7) further limit its appeal, meaning "small biotech companies are less likely to benefit from a CNPV," they added (4).

Despite these risks, FDA Principal Deputy Commissioner Sara Brenner, MD, MPH, maintained confidence, asserting in a news release that the "more efficient process can be achieved without cutting any corners on safety or scientific evaluation” (6). The FDA retains a critical safeguard: the right to extend the review window if data or application components are "insufficient or incomplete," if pivotal trial results are "ambiguous," or if the review is "particularly complex" (5,6).

FDA Commissioner’s National Priority Vouchers Will Endanger Americans

Questions Remain as FDA Opens Submissions for New Priority Voucher Program

How to Make One Line in the FDA Commissioner's New Drug Review Program Into a Force for Affordable Access for Patients

Commissioner's National Priority Voucher (CNPV) Pilot Program

FDA to Issue New Commissioner’s National Priority Vouchers to Companies Supporting U.S. National Interests

FAQs: Commissioner’s National Priority Voucher Pilot Program

Articles

The FDA's National Priority Voucher (CNPV) pilot program aims to expedite drug review times significantly, reducing them from 10-12 months to 1-2 months. While this initiative promises faster access to treatments, it raises concerns about compromising safety standards and bypassing independent regulatory scrutiny. Critics argue that the accelerated timeline could lead to safety issues post-approval and strain FDA resources. The program's discretionary nature and lack of dedicated funding further complicate its implementation, potentially limiting its appeal and effectiveness, especially for smaller biotech companies.

FDA’s CNPV pilot aims to speed drug reviews but raises questions about safety trade-offs, resource strain, and unclear incentives for sponsors.

The Regulatory Crucible: Risk, Resource Drain, and the Hidden Trade-Offs of the CNPV Pilot Program

Feliza Mirasol is the science editor for 

Patrick Lavery is an Editor for the MJH Life Sciences brands 

. Previously at MJH, he filled the same role for 

Sanjay Konagurthu AAPS Interview, Part One

, held from Nov. 9–12 in San Antonio, Texas, 

, PhD, senior director, Science and Innovation, Thermo Fisher Scientific, about the conference presentation “

AI/ML Model Informed Early-Stage Drug Development.

In the above interview—the first in a two-part installment—Dr. Konagurthu discusses the potential of 

 using artificial intelligence (AI) and machine learning (ML).

“The big advantage is time and cost savings and resource savings for the industry and our customers,” Konagurthu says. “Time is money, literally speaking, and what we bring to the table is reducing risk in product development, saving time and resources, minimizing API consumption. It's an ultra-material-sparing approach by leveraging some of these 

 modeling tools like AI, leveraging AI/ML for supporting product development and formulation development.”

How can AI/ML improve early-stage drug development?

In particular, Konagurthu says, AI/ML can help sift through a field of drug candidates in which the percentage that are 

 has increased in the past several decades from 30% to as high as 90%.

“It's a challenging environment and the probability of success of getting a poorly soluble NCE [new chemical entity] to a commercial product is pretty low,” he says. “It's way less than 10%, probably more like 5%. So, by leveraging some of these AI/ML tools that we've developed, we aim and strive to reduce the risk in product development.”

Check back for Part Two of PharmTech Group’s interview with Konagurthu, in which he drills down further on molecular dynamics simulations and quantum mechanical calculations as tools to be deployed beyond simple screening.

 for all of our AAPS PharmSci 360 coverage.

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

Hello, I'm Sanjay Konagurthu. I'm Senior Director of Science and Innovation at Thermo Fisher. I've been in the industry going on now 27 years.

Background, I'm a chemical engineer by education, PhD. My experience, broadly speaking, is in small-molecule oral drug delivery areas like solubility, bioenhancements, spray drying, hot-melt extrusion, nanotechnology, as well as modified control release, complex dosage forms, etc., ranging from early development through commercialization.

I also lead a predictive modeling and simulation team at Thermo Fisher. We are a global team. We deal with the predictive modeling and simulations for drug product development.

That's a great question. I like to tell people when I first started working in this industry over 20-plus years ago, the number of candidates that were poorly soluble were estimated to be 30% or so. Now, depending on the source that people quote, 70% to 90% of molecules are poorly soluble, so it's more than doubled, if not tripled.

It's a challenging environment and the probability of success of getting a poorly soluble NCE to a commercial product is pretty low. It's way less than 10%, probably more like 5%. So by leveraging some of these AI/ML tools that we've developed, we aim and strive to reduce the risk in product development.

We can get to accelerating the early phase especially by leveraging these 

 AI/ML tools for selection of technologies. What's the best technology that might work for any given molecule? And it's all dependent on the type of molecule. Every molecule is unique.

And also in formulation selection, for example, we deal with complex modalities like protacs, which are on the larger end of the spectrum, and the traditional small molecules. And all these molecules violate, typically, Lipinski's rule of five. So they're literally the brick dust, greaseball-type molecules. By leveraging these AI/ML tools we again, as I said, reduce the risk in product development, get to the milestones faster, and shorten timelines, etc.

The big advantage is time and cost savings and resource savings, for the industry and our customers. Time is money, literally speaking, and what we bring to the table is reducing risk in product development, saving time and resources, minimizing API consumption. It's an ultra-material sparing approach by leveraging some of these 

 modeling tools like AI, leveraging AI/ML for supporting product development and formulation development.

Every API, as I mentioned, is unique. So your structural features are very important, obviously the chemical structure, also fundamental properties like the melting point which have bearing on the crystal lattice, [the] energy of the molecule [is] important. Other properties like pKa, LogP, LogD, all of those are important.

Also, things like permeability are important. So typically we try to get data measured in 

 assays like KCO2 or MDCK, and we can leverage that to predict what's happening in the human body. These are some of the features that are important in some of these calculations that we do.

Videos

Sanjay Konagurthu of Thermo Fisher Scientific discusses how AI and ML can help solve the dilemma of poor solubility.

Leveraging AI/ML to Reduce Risk in Drug Development: Part One

UK’s Lead-212 Strategy for Cancer Care

The United Kingdom National Nuclear Laboratory (UKNNL) and Medicines Discovery Catapult (MDC) are co-leading a major project to utilize recycled nuclear materials for the development of next-generation cancer treatments (1). This effort, backed by £18.8 million (US$24.7 million) in combined public and industry funding, focuses on harvesting a radionuclide known as lead-212, from used nuclear fuel, to create treatments called Targeted Alpha Therapies (1).

According to a press release from UKNNL, lead-212 is an untapped asset in the UK that showcases 

 targeted diagnosis and therapy (1–3). However, the industry faces significant challenges related to escalating global demand, stringent regulatory requirements, and highly vulnerable supply chains stemming from reliance on imports and the short half-life of radioisotopes (2,3).

As pharmaceutical companies invest in this rapidly advancing field, overcoming development, regulatory, and manufacturing complexities is essential to accelerating these treatments to market (2,3). The following findings summarize the critical implications for industry professionals.

How is manufacturing sustainability and supply changing?

Image Credit: © Patrick Lavery/MJH Life Sciences using Microsoft Office

The development of a sustainable lead-212 supply from recycled nuclear fuel helps address the global reliance on imports 

 including the development of generator technologies and enhanced domestic production capabilities, aim to ensure a reliable source and harmonize complex logistics for these short-shelf-life medicines (5).

 that combine expertise in radiochemistry, imaging technologies, and preclinical oncology models to generate high-quality translational data and de-risk investment (2,3,6). Researchers are also focused on advancing radio drug conjugates by optimizing the chemistry required to link radio ligands to targeting molecules, 

Recent FDA draft guidance emphasizes the need for sponsors to identify optimized dosages for systemic radiopharmaceutical therapies by providing a better understanding of pharmacodynamics, therapeutic window, and dosimetry (5,7). Clinical trials must include safeguards like appropriate participant selection and safety monitoring, and may study dosages exceeding historical external beam radiation therapy organ tolerances if scientifically justified.

UK Nuclear Revolution Powers Next-Generation Precision Cancer Therapies.

 Press Release. Nov. 18, 2025.
2. Haigney, S. 

Advancing Radiopharmaceutical Development.

Collaborating on the Development of Radiopharmaceuticals.

EMA Is Tackling Vulnerabilities in the Supply Chain of Radiopharmaceuticals.

Why Radiopharmaceuticals Are Ideal for Treating Cancer.

Medicines Discovery Catapult and Crown Bioscience Form Strategic Global Alliance for Radiopharmaceutical Innovation.

Oncology Therapeutic Radiopharmaceuticals: Dosage Optimization During Clinical Development. Draft Guidance for Industry

To meet rising demand, developers of precision radiopharmaceutical therapies must overcome challenges in global isotope supply and align R&D platforms with evolving FDA guidance on clinical dosimetry.

Nuclear Waste to Medicine: The UK’s Lead-212 Strategy for Cancer Care

Cheryl Barton is director of PharmaVision, 

Landkarte *** Europa | Image credit: ©beugdesign - Stock.adobe.com

In September 2025, the European Commission (EC), together with the Heads of Medicines Agencies (HMA) and the European Medicines Agency (EMA), revealed two new goals for clinical trials to ensure Europe maintains its leadership in clinical research (1). By 2030, the European Union aims to:

Increase the number of multinational clinical trials by 100 annually; currently, an average of 900 are authorized each year.

Increase the speed of patient recruitment in clinical trials; currently, about 50% of trials recruit patients within 200 calendar days or less from the application submission date. The goal is to raise this to two-thirds (66%).

In early 2025, the United Kingdom (UK) government unveiled its plans to speed up clinical trials, unlock National Health System (NHS) data for research, and improve patient access to new treatments earlier (2). The global clinical trial arena is becoming increasingly competitive, serving as a significant revenue generator. According to market research, the global clinical trials market accounted for US$59 billion (€44 billion) in 2024 and is anticipated to grow from US$62.4 billion (€54.35 billion) in 2025 to US$98.9 billion (€86.15 billion) in 2034, growing at a compound annual growth rate of 5.2% (3).

An analysis of clinical trials between 2005 and March 2025 highlights that the United States hosts the majority of clinical trials, followed by China, France, Canada, Turkey, and the UK (

). The majority of clinical trials were conducted in a limited geographical distribution. Specifically, 26% of clinical trials were conducted in multiple locations, and only 8.2% of the total clinical trials were multinational clinical trials (4). However, market research indicates that the main barriers in clinical trials are due to poor trial design, lack of inclusivity, and inadequate clinical trial infrastructure (5). Therefore, if the EU wants to be a serious contender, it needs to strengthen its clinical trial ecosystem, promote ethical research, encourage stakeholder collaboration, and implement strategic investments.

Figure 1: Distribution of clinical trials by continents and disease, 2005-2025. (Figure courtesy of the author and modified from reference 4).

How is the EU driving innovative clinical research?

These new goals are part of the EU's ongoing effort to create a more supportive environment for clinical research following the launch of the Accelerating Clinical Trials in the EU (ACT EU) initiative in January 2022, a collaboration between EC, HMA, and EMA (6). It also builds on the EU Life Science to enhance public health, create jobs, and foster innovation by 2030, positioning the EU as a global leader (7).

The EU pharmaceutical legislation continues to evolve, and the EC has started a comprehensive review to create an agile, competitive, and equitable regulatory framework. The ACT EU is one of the first steps to strengthen clinical research in Europe (8). The ACT EU initiative has launched a trial map to help patients find nearby clinical trials. Additionally, it provides guidance to clinical trial sponsors on designing effective trials and submitting successful applications for authorisation, including marketing authorization. In addition, they can provide support for the implementation of the revised International Council for Harmonisation (ICH) E6 R3, 

 guideline and assistance for non-commercial sponsors to conduct more multinational trials.

In addition, the EU has several complementary initiatives underway to help the EU meet these targets, including:

The Clinical Trials Regulation (CTR) Collaborate initiative aims to foster interaction between national authorities and ethics committees to promote harmonized procedures and reduce administrative burden (9).

The COMBINE initiative aims to understand challenges and obstacles to align the interface between the three frameworks: CTR, In Vitro Diagnostics Regulation (IVDR), and Medical Device Regulation (MDR) (10). In June 2025, the first pilot was launched to coordinate clinical and performance study assessments into a single streamlined process (11).

The MedEthicsEU is a forum of national representatives from medical research ethics committees, established by the EC, to support discussion and mutual learning between EU/EEA Member States Ethics Committees (12).

Meanwhile, the European Federation of Pharmaceutical Industries and Associations (EFPIA) has been actively promoting innovation in this area. It has launched its Clinical Trials Strategy 2030+ with the goal of re-establishing Europe as a leading hub for faster, smarter, and more patient-centric clinical trials (

) (13). EFPIA is collaborating closely with other industry associations, patient organizations, academia, and national trade bodies to engage with regulators and policymakers, to help address the challenges in the current legislative framework (e.g., CTR, IVDR, MDR) and proactively proposing solutions (14). They are involved in multiple Innovative Health Initiatives (IHIs) that focus on patient-centred clinical research, aiming to improve trial design and conduct, enhance patient engagement and experience, increase the efficiency of clinical trials, and address health disparities.

Figure 2: Clinical Trials Strategy 2030+. (Figure courtesy of the author and modified from reference 13).

What are the implications of new clinical trial targets for pharma?

These new EC trial targets present new opportunities for the pharmaceutical industry to expand the number of multinational trials, provided they can meet patient recruitment timelines and comply with the CTR. It could catalyse changes in how clinical trials are conducted and managed in the EU, and allow sponsors to include more flexible trial design and market access strategies. This will help to increase speed to market and enable European patients to receive new therapies more quickly. The EU continues to streamline the trial process and reduce administrative burdens. Pharma companies must proactively engage with regulators and stakeholders to capitalize on the EU's strategy and strengthen their position in this multi-billion-dollar arena.

EMA. New Targets for Clinical Trials in Europe. Press Release. 23 Sept 2025. 

https://www.ema.europa.eu/en/news/new-targets-clinical-trials-europe

Wise, J. UK Launches Plan to Speed Up Clinical Trials and Improve Access to New Treatments 

Clinical Trials Market Size & Share Report, 2025 – 2034

Joshi, G.; et al. The Current Landscape of Clinical Trials. 

Apr 7;14(7):2519. DOI: 10.3390/jcm14072519.

The Lancet. Clinical Trials in Global Health 2025. 25 Mar 2025. 

https://www.thelancet.com/series-do/clinical-trials

Accelerating Clinical Trials in the EU (ACT EU)

https://accelerating-clinical-trials.europa.eu/about/initiative_en

EU Regulatory Activity is Driving Comprehensive Reforms for Pharma in 2025

https://www.osborneclarke.com/insights/eu-regulatory-activity-driving-comprehensive-reforms-pharma-2025

. 16 Apr. 2014. https://eur-lex.europa.eu/eli/reg/2014/536/oj

EC. ‘COMBINE’ Initiative–The Regulatory Landscape for Combined Studies on the IVDR/MDR/CTR Interface. 

. December 2024. https://health.ec.europa.eu/document/download/44bbffa5-e61e-4056-bfaf-50a46eeecb7b_en?filename=md_combine_presentation_en.pdf

EC. COMBINE Programme Launched a Pilot Coordinated Assessment for Clinical Trials and Performance Studies. 

https://ec.europa.eu/newsroom/sante/newsletter-archives/64447

EC.Clinical Trials–MedEthicsEU–Group of National Representatives of Medical Research Ethics Committees. 

https://health.ec.europa.eu/medicinal-products/clinical-trials/medethicseu_en

clinical-trial-strategy-in-a-snapshot.pdf

EFPIA. Improving EU Clinical Trials: Proposals to Overcome Current Challenges and Strengthen the Ecosystem

efpias-list-of-proposals-clinical-trials-15-apr-2025.pdf

Cheryl Barton, PhD, is founder and director of PharmaVision, Pharmavision.co.uk.

The European Union (EU) is setting ambitious goals to enhance its clinical trial landscape by 2030, aiming to increase multinational trials and expedite patient recruitment. This initiative is part of the Accelerating Clinical Trials in the EU (ACT EU) program, which seeks to create a supportive environment for clinical research. The EU is also implementing complementary initiatives to streamline processes and reduce administrative burdens. These efforts present opportunities for the pharmaceutical industry to expand multinational trials, improve trial design, and accelerate market access, ultimately benefiting European patients with quicker access to new therapies.

The European Union aims to become the most attractive destination for clinical research.

New Targets for Clinical Trials in the European Union

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.

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.

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

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.”

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.

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