Instead of relying on finding novel targets, a key strategy in neuropsychiatry is to revisit failed compounds that showed efficacy signals. Companies use modern chemistry and delivery to engineer solutions that separate efficacy from the historical liabilities that halted development, turning past failures into new opportunities.

The degradation mechanism is fundamentally superior to inhibition because it removes the entire protein, addressing both its enzymatic and scaffolding functions. This allows degraders to hit targets harder and more completely, suggesting they could become the dominant modality across oncology and other therapeutic areas.

The discovery-based model of finding highly impactful single targets like HER2 or PD-1 is becoming unsustainable as the low-hanging fruit is picked. The field must shift toward an engineering-first approach, designing complex, multi-functional therapeutics to achieve specific clinical objectives, much like high-tech fields.

Unlike traditional small molecules that need a pocket on a target protein, molecular glues work by changing the surface of an E3 ligase. This modified surface then perfectly matches and binds the target protein, enabling its degradation without requiring a direct drug-to-target binding site.

Biotech companies create more value by focusing on de-risking molecules for clinical success, not engineering them from scratch. Specialized platforms can create molecules faster and more reliably, allowing developers to focus their core competency on advancing de-risked assets through the pipeline.

Beyond sheer scale, China's innovation leads in complex, next-generation drug modalities like ADCs and bispecifics. Chinese biotechs now account for roughly one-third of the global Phase 1 and 2 pipelines for these advanced therapies, indicating a shift from iteration on established targets to leadership in new technology platforms.

While China is known for licensing novel assets, its researchers are also becoming leaders in a more fundamental area: drug delivery and formulation. This is particularly evident in the targeted protein degradation space, where Chinese publications dominate innovations related to improving drug-like properties.

Beyond accelerating timelines, AI's real value lies in its ability to design molecules for targets previously considered 'hard-to-drug.' These models operate on different principles than traditional lab methods and are indifferent to historical challenges, opening up entirely new therapeutic possibilities.

The current, tangible breakthrough for AI in drug discovery is not identifying completely novel biological targets. Instead, it's rapidly designing effective molecules for known targets that have historically been considered "undruggable," compressing years of screening work into a month.