The push away from animal models is a technical necessity, not just an ethical one. Advanced therapeutics like T-cell engagers and multispecific antibodies depend on human-specific biological pathways. These mechanisms are not accurately reproduced in animal models, rendering them ineffective for testing these new drug classes.

Traditional 2D cell cultures can be misleading. Advanced 3D models, by reconstituting the tumor microenvironment with stromal cells, can uncover mechanisms of drug resistance (e.g., to ADCs) that are completely invisible in simpler systems, providing more clinically relevant data.

Only 5% of investigational cancer drugs reach the market due to the gap between lab models and human biology. Dr. Saav Solanki highlights organoids, which use real patient tissue, as a key translational model to improve the predictive accuracy of preclinical research and increase the low success rate.

Contrary to the perception that drug development is all about human trials, the first five years of the typical decade-long journey are dedicated to rigorous preclinical work. This foundational stage involves chemistry and non-human testing before a molecule ever reaches a patient.

With over 5,000 oncology drugs in development and a 9-out-of-10 failure rate, the current model of running large, sequential clinical trials is not viable. New diagnostic platforms are essential to select drugs and patient populations more intelligently and much earlier in the process.

Unlike using genetically identical mice, Gordian tests therapies in large, genetically varied animals. This variation mimics human patient diversity, helping identify drugs that are effective across different biological profiles and addressing patient heterogeneity, a primary cause of clinical trial failure.

The temptation is to use the most advanced technology available. A more effective approach is to first define the specific biological question and then select the simplest possible model that can answer it, thus avoiding premature and unnecessary over-engineering.

The NIH will no longer award funding to new grant proposals that rely exclusively on animal models. This policy forces a shift towards New Approach Methodologies (NAMs), such as organoids and organ-on-chips, serving as a major catalyst for innovation and adoption in the preclinical testing space.

The company intentionally makes its early research "harder in the short term" by using complex, long-term animal models. This counterintuitive strategy is designed to generate highly predictive data early, thereby reducing the massive financial risk and high failure rate of the later-stage clinical trials.