In Vivo Models and NAMs Are Stronger Together—Taconic Vice President Dr. Michael Seiler's view

Preclinical research is changing. Drug developers are under increasing pressure to generate data that is more human-relevant, more predictive, and more aligned with clinical decision-making. At the same time, new approach methodologies, or NAMs, including organoids, iPSC-derived systems, microphysiological platforms, and computational tools, are becoming more prominent in early discovery and translational research.

A recent GEN article, Next Generation Biopharma Innovation, described this shift as traditional in vivo models “joining forces” with NAMs to provide more relevant translational data. In the article, Michael Seiler, PhD, vice president of portfolio management at Taconic Biosciences, noted that model development is being driven by improved translational fidelity, increased demand for study-ready systems that better align with clinical endpoints, and the need to model complex and overlapping disease biology.

For Taconic, this evolution is not about choosing between in vivo models and NAMs. It is about using complementary systems strategically.

NAMs can provide powerful mechanistic insight. They can help researchers evaluate human cell behavior, explore pathway biology, screen hypotheses, and reduce reliance on less informative approaches. But many translational questions still require biological context that isolated systems cannot fully reproduce. Systemic exposure, immune interactions, tissue crosstalk, pharmacokinetic and pharmacodynamic relationships, disease progression, and organism-level tolerability often require an integrated biological system.

That is where advanced, fit-for-purpose in vivo models remain essential. The most informative models are not generic research tools applied late in development. Increasingly, they are engineered, humanized, characterized, and deployed around specific translational questions.

Taconic supports this integrated model strategy across areas where biological complexity is especially important. In immunology and immuno-oncology, complex modalities such as checkpoint inhibitors, engineered cell therapies, and bispecifics require more complete immune context and deeper phenotyping. Taconic’s FcResolv® NOG portfolio, huSelect™ services, and advanced flow cytometry panels are designed to help reduce murine immune interference, manage donor variability, and support more standardized immune profiling.

The integration of TransCure bioServices further strengthens this approach by connecting Taconic’s model access, humanization, and cohort-generation expertise with in vivo pharmacology and immune profiling capabilities. This creates a more seamless path from model selection through study execution and data generation, particularly for humanized immune system and immuno-oncology research.

The same principle applies in neurobiology and cardiometabolic disease. As programs increasingly focus on blood-brain barrier biology, CNS delivery, GLP-1-based therapeutics, metabolic disease, liver biology, and overlapping inflammatory mechanisms, translational confidence depends on models that reflect the biological context of the therapeutic question. 

The future of translational research will not be defined by a single model system. It will be defined by thoughtful model strategies that connect human-relevant mechanistic insight with whole-organism biology. When NAMs and advanced in vivo models are used together, researchers can generate data that is not simply more abundant, but more relevant, interpretable, and decision-ready.