As drug discovery grows more sophisticated, one challenge continues to define the industry: translating promising science into successful clinical outcomes. Despite decades of innovation, the vast majority of therapies still fail in clinical trials—often due to an incomplete understanding of how they will perform in humans.
In a recent discussion with Oxford Global, James Keck, Vice President of Innovation and Product Development, The Jackson Laboratory outlined how a new generation of clinically relevant humanised models is helping to close this gap—bringing researchers closer than ever to predicting real patient responses before trials even begin.
Rethinking Preclinical Models
Traditional animal models, while valuable, cannot fully replicate human biology. Meanwhile, non-human primates face ethical and practical limitations.
Humanised models offer an alternative by introducing human immune cells into immune-deficient mice. This creates a system that more closely reflects human disease and immune responses.
“It’s about getting as close to the patient as possible,” Keck noted.
Predicting Real Patient Responses
These models allow researchers to study how therapies perform across both efficacy and safety by recreating patient-specific immune systems. Even small blood samples can be used to simulate individual responses, supporting the shift toward precision medicine.
Addressing the Diversity Gap
A major cause of clinical failure is the lack of diversity in early testing. Many therapies are developed in narrow models that fail to reflect real patient populations—contributing to failure rates as high as 96%.
Humanised models help overcome this by enabling population-level testing, identifying variability and potential risks earlier, and improving trial design.
A More Complete Immune Picture
Newer models now incorporate multiple immune cell types—such as T cells, B cells, and NK cells—allowing researchers to study whole-system responses.
This enables a more integrated view of efficacy, toxicity, and pharmacokinetics, including antibody half-life, within a single experiment.
Toward Predictive Drug Development
As these systems evolve, their predictive power is expected to improve—potentially forecasting outcomes across clinical phases and reducing development risk.
Collaboration Driving Progress
The Jackson Laboratory works closely with biopharma and regulatory partners to refine these models and apply them to real-world challenges.
Looking Ahead
By capturing human biology and patient diversity more accurately, humanised models are reshaping preclinical research—offering a more predictive, efficient path to drug development.
In bringing the patient into the model, the industry may finally be closing the gap between discovery and clinical success.