When designing multi-factor experiments, group compounds by their biological function. This prevents a dominant compound from overwhelming the signals of others and keeps dilution effects manageable. It ensures you capture the subtle effects of all factors, leading to more reliable and informative results.

In preclinical drug development, choosing the right biological model is the most critical initial decision. Selecting an inappropriate model, such as the wrong PDX or organoid line, guarantees the research program will fail as it will be designed to answer the wrong question from the outset.

Simple cell viability screens fail to identify powerful drug combinations where each component is ineffective on its own. AI can predict these synergies, but only if trained on mechanistic data that reveals how cells rewire their internal pathways in response to a drug.

Incorporate well-characterized compounds with known, consistent effects into every separate experimental group. These "anchors" act as internal calibration points, enabling reliable comparison of results across different experimental sets that would otherwise be difficult to correlate directly.

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.

An analysis of over 17,000 oncology drug development trajectories revealed that trials incorporating biomarkers had almost twice the overall success probability (10%) compared to those without (5%). This success boost is most significant in early-phase (Phase 1 and 2) trials.

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.

Molecular glue degraders allow for direct measurement of target protein elimination in patient blood samples. This provides a more accurate pharmacodynamic marker of drug effect than the flawed pharmacokinetic calculations (plasma exposure vs. in-vitro activity) often used for inhibitors.

A significant, often overlooked, hurdle in drug development is that therapeutic antibodies bind differently to animal targets than human ones. This discrepancy can force excessively high doses in animal studies, leading to toxicity issues and causing promising drugs to fail before ever reaching human trials.