NAMs: an exciting era for drug discovery

New approach methodologies (NAMs) aim to address the limitations of animal models by assessing drug efficacy and safety in a more ethical, human-relevant way. The term ‘NAMs’ encompasses several emerging techniques and technologies, from in vitro models to in silico models – all with the aim of more closely mimicking human biology and providing therapeutics researchers with more predictive power.

In this interview, Kalpana Barnes – Principal Scientist at Sartorius (Royston, UK) – highlights how NAMs are addressing the gaps in drug discovery studies, including real-world examples, and how Sartorius is working to make NAMs more accessible and impactful. Additionally, Kalpana shares how she envisions NAMs and their regulatory acceptance will reshape the drug discovery and disease modeling landscape in the future.

This interview is part of the BioTechniques In Focus on NAMs, in association with Sartorius. Check out the animated video and infographic to learn more.

What are the biggest limitations of traditional animal models, and how do NAMs address these gaps in drug discovery?

While traditional animal models have served as the foundation for preclinical testing, their use is not without limitations. A significant factor and a major cause for the discrepancies in drug efficacy and safety is that animal models fail to fully replicate human physiology and pathophysiology. Additionally, some human diseases – for example, Alzheimer’s – do not present themselves to animals, further diminishing their utility. Furthermore, the ethics associated with the use of animals in research and social pressure regarding animal welfare are of concern. The often lengthy, time-consuming and costly nature of animal studies hinders their use further.

NAMs aim to address these limitations and offer a new paradigm for efficacy and safety testing in drug discovery and development. Comprising a diverse range of techniques and technologies, NAMs utilize in vitro, in silico and in chemico models to mimic human biology more faithfully.

In vitro models constitute advanced and more physiologically relevant culture systems. These include 2D co-culture models using relevant human cell types, or microphysiological systems such as 3D spheroid, organoid and organ-on-chip models that more faithfully replicate the structural, functional and dynamic environment of human tissues.

In silico models employ computational techniques to simulate human biological responses, track disease progression and forecast chemical properties, pharmacokinetics, off-target effects and toxicity. By harnessing big data, machine learning and AI can uncover various patterns and predict toxicity throughout the pharmaceutical space. In silico methods also assist in prioritizing drug candidates and minimizing redundant experimentation. Multiomics-based strategies, which analyze extensive genomic, proteomic, metabolomic and transcriptomic datasets from human samples, provide mechanistic insights into the impact of chemicals on biological responses. These approaches facilitate a transition towards mechanistic toxicology, emphasizing early molecular events instead of late-stage pathological outcomes.

Regarded as the most straightforward NAM technique, in chemico methods investigate the chemical reactions that occur when test substances interact with biological molecules like peptides, proteins or DNA. These methods are used to assess a drug’s potential for causing harm or side effects and to understand how it might interact with other drugs.

In combination, NAM tools and technologies deliver human-relevant data earlier in the drug discovery pipeline, supporting better candidate selection while reducing the use and reliance on animal testing.

How is Sartorius supporting researchers with tools like 3D cell cultures to make NAMs more accessible and impactful?

Advanced 3D models like organoids, including iPSC-derived and patient-derived organoids, represent a pivotal leap forward in biomedical research, offering insights into human biology that were previously not possible. These models are key NAMs, providing human relevance. However, their promise is tempered by a significant challenge: their inherent technical complexity and variability.

Standardizing iPSC quality control is vital to ensuring model validity. Robust methods are required for monitoring, detecting and reducing heterogeneity in iPSC-lines, ensuring pluripotency and viability are maintained. Once characterized, cells are then suitable for differentiation. The CellCelector Flex is an automated imaging and picking platform for gentle and accurate cell selection.

Technologies such as the Incucyte^® Live-Cell Analysis System allow researchers to non-invasively monitor the development of iPSC and 3D organoid cultures in real-time, within the physiological environment of an incubator. Using quantitative, kinetic data from this system supports objective, non-biased quality control and establishment of acceptance criteria, ensuring only high-quality cultures are used for downstream steps.

Beyond culture quality control, the Incucyte^® Organoid Assay and integrated software support a range of organoid applications. Standardized and automated organoid acquisition and real-time analysis simplify characterization of these cultures for quantification of phenotypic measurements.

Model characterization and multi-parametric profiling can be achieved using the iQue^® Advanced Flow Cytometry platform. This system supports high-throughput immunophenotyping, secreted biomarker analysis and viability measurements, all from the same culture. These measurements are key for applications, such as using iPSC-derived cardiomyocytes for quality control or liver organoids for metabolism studies, in turn accelerating the assay development pipeline.

Sartorius also offers a portfolio of synthetic hydrogels to support NAM cultures. Designed to either maintain the pluripotent identity and expansion of iPSCs cultures or create and cultivate 3D spheroids or organoid cultures.

For researchers seeking a validated starting point, our portfolio now includes Mattek’s highly characterized, ready-to-use 3D human tissue models. These solutions, such as EpiDerm™ and EpiIntestinal™, serve as effective benchmarks, reducing the initial burden of model development and validation.

Furthermore, our Multi-Organ Tox Plate (MOTP) offers a novel approach to drug-induced toxicity studies across 3D models of the intestine, liver and kidney. When integrated with the Incucyte^® system, it offers high-throughput, real-time imaging and automated analysis, enabling researchers to determine drug effects and calculate potency values across multiple human organ systems simultaneously. This approach facilitates efficient in vitro predictions, reduces animal use and delivers more physiologically relevant data.

By combining robust quality control, real-time quantitative functional analysis and ready-to-use models into an integrated workflow, we are empowering researchers to fully harness the power of 3D biology, with the potential to impact drug development and human health.

With initiatives like the FDA Modernization Act 2.0 and EMA’s support for NAM validation, how do you see regulatory acceptance evolving over the next five years?

The FDA Modernization Act 2.0, enacted in 2022, permits the use of alternative NAMs, such as cell-based assays, organ-on-chip technologies and computer modeling for investigating the efficacy and safety of a drug. Over the next five years, I would anticipate the regulatory acceptance of NAMs to continue to grow, transitioning from a supplementary role to a more integrated component of drug development, reinforced by initiatives like the FDA Modernization Act 2.0 and EMA’s support. This shift will be propelled by the demand for more human-relevant and predictive methods, leading to a gradual reduction in animal testing as NAMs become scientifically validated, harmonized and increasingly incorporated into regulatory submissions.

Can you share a real-world example where NAMs accelerated research timelines, improved predictivity or reduced reliance on animal testing?

Across a range of therapeutic areas, NAMs are beginning to have an impact on reducing research timelines and reliance on animal testing, while delivering improved human predictivity.

For example, in neuroscience drug discovery, the paucity of human primary tissue has resulted in the extensive use and reliance of animal models. Research into diseases such as amyotrophic lateral sclerosis (ALS) relies heavily on genetically modified mouse models, which regularly fail to reproduce the complexity of the human disease, leading to poor translation of results to patients. Instead, the NAM that can be employed utilizes human iPSCs derived directly from ALS patients. This in vitro model of patient iPSC-derived motor neurons and microglia maintain the authentic human genetic background of the disease (C9orf72 mutation), making biological findings from this model directly relevant to human biology. The observed hyperexcitability and phagocytosis impairment in this model are hallmarks of human ALS, validating the model’s predictive strength.

The use of patient-derived organoids as NAMs and personalized medicine approaches has accelerated research timelines and improved human predictivity. A notable example is the use of patient-derived intestinal organoids and the development of cystic fibrosis transmembrane conductance regulator (CFTR)-modulator drugs. The effect of current CFTR-modulators in patients with rare forms of the CFTR mutation is scarcely described, and due to extremely low patient numbers, determination of clinical efficacy is challenging. Advancements in stem cell technology have enabled the cultivation of patient-derived organoids that mimic the characteristics and function of their original tissue. Dekkers et al. developed an in vitro forskolin-induced swelling (FIS) assay that can be used to quantify CFTR modulators. This assay has shown correlations between organoid swelling and clinical trial drug responses, accurately predicting individual responses to CFTR modulators. It has identified successful treatments for patients with rare genotypes showing high FIS responses. Additionally, drugs that failed in organoids did not yield clinical benefits, emphasizing organoids’ specificity in detecting meaningful clinical changes. Organoid CFTR function offers a personalized assessment of modulator efficacy, potentially stratifying patients with rare mutations for effective treatments.

What excites you most about the future of NAMs, and how do you see them reshaping the landscape of drug discovery and disease modeling?

The future of NAMs is exciting since they promise to reform drug discovery and disease modeling in several positive ways. With their enhanced predictivity of human responses compared to traditional animal models, NAMs can provide a more relevant understanding of drug efficacy and safety, reducing the risk of failures later in the drug development workflow.

The integration of in vitro models, such as microphysisological systems that use human relevant cells, and in silico computational approaches allow for more advanced and detailed analysis of biological processes, enabling researchers to explore complex disease mechanisms and drug interactions.

Another exciting and rapidly expanding space is the use of patient-derived organoids for personalized disease modeling and drug testing, offering insights into individual responses and paving the way for precision medicine. The application and integration of advanced data analysis and predictive modeling techniques, such as machine learning and AI, supports rapid identification of drug candidates and optimization of therapeutic strategies. Layering multiomic approaches provides a comprehensive understanding of disease mechanisms and drug effects, leading to more targeted and effective treatments.

By minimizing or eliminating the need for animal testing, NAMs provide ethical alternatives that promote human research practices, aligning with the 3Rs principle (replacement, reduction and refinement) and public expectations.

Implementing NAMs can be challenging, requiring technical expertise, rigorous validation, regulatory alignment and seamless integration into existing pipelines. The importance of technological advancements for ensuring the reproducibility and reliability of NAMS is key. Collaborative efforts between researchers and technology providers continuing to innovate and provide solutions aimed at NAMs will help address these challenges and their implementation.

The steer from regulatory bodies is vital for NAM adoption across the breadth of the drug discovery continuum. The FDA Modernization Act 3.0 and the recent announcement by the NIH, which plans to set up a dedicated organoid development center with the aim to standardize protocols for organoid research, further illustrates their commitment. It will be interesting to see if this momentum from regulatory bodies continues at a pace.

Overall, NAMs are reshaping the landscape of drug discovery and disease modeling by providing tools that are more predictive, ethical and efficient, ultimately leading to safer and more effective medicines. They have the potential to streamline the drug development process by reducing timelines and costs associated with traditional methods. This efficiency can accelerate the availability of new therapies for patients. This is an exciting era drug discovery.

About the interviewee

Kalpana Barnes (left) is a highly experienced industrial pharmacologist with over 25 years of experience gained from pharmaceutical, contract research and biotech laboratories. Trained initially as an in vitro pharmacologist, Kalpana specialized in designing and developing plate-based cellular assays to support automated high-throughput screening, compound profiling and mechanism of action follow-up studies. Within Sartorius, she’s applied her extensive experience to the development and validation of cellular assays for quantitative live-cell analysis, with a focus on addressing the challenges and developing solutions for working with in vitro 3D advanced cell models.

The interviewee has no competing interests to report.

The opinions expressed in this interview are those of the interviewee and do not necessarily reflect the views of BioTechniques or Taylor & Francis Group.

This content was supported by Sartorius.