The company focuses on disease-specific 3D protein conformations, which exposes new binding sites (epitopes) not present on the same protein in healthy cells. This allows for highly selective drugs that avoid the toxicity common with targets defined by genetic sequence alone.

Instead of testing a single drug candidate in cheap models before moving to expensive ones, Gordian's parallel testing platform makes it cost-effective to use clinically relevant large animals, like horses, at the very beginning of the discovery process. This flips the traditional R&D funnel on its head.

In the competitive oncology market, Step Pharma differentiates itself by highlighting its novel, "first-in-class" mechanism and excellent safety profile. This strategy attracts interest by focusing on a unique therapeutic opportunity and potential for combination therapies, rather than competing directly on incremental efficacy gains.

To offset the impending 2027 patent loss for its blockbuster drug Xtandi, Astellas is not relying on a single successor. The company is betting on five distinct strategic brands across bladder cancer, AML, geographic atrophy, and women's health to collectively replace the revenue and mitigate the impact.

Astellas isn't resting on its first-to-market Claudin 18.2 antibody. It's proactively developing next-generation therapies—a CD3 bispecific to reach more patients and an in-licensed ADC for a potential chemo-free regimen. This multi-asset strategy aims to create an enduring leadership position in this specific cancer target.

Luba Greenwood reframes competition in biotech as a positive force. When multiple companies pursue the same biological target, it validates the target's importance and accelerates discovery. This collaborative mindset benefits the entire field and, ultimately, patients, as the best and safest drug will prevail.

Astellas' R&D isn't defined by therapeutic area or technology. Instead, their "focus area approach" creates a "triangle" of core biology, the best modality, and the right patient population. This model is designed to generate multiple follow-on programs, like their KRAS degraders, by pivoting any corner of this triangle.

A new 'Tech Bio' model inverts traditional biotech by first building a novel, highly structured database designed for AI analysis. Only after this computational foundation is built do they use it to identify therapeutic targets, creating a data-first moat before any lab work begins.

In crowded fields like oncology, most companies flock to a few validated ideas, like kids chasing a soccer ball. Delpha Therapeutics' CEO Kevin Marks argues the real opportunity lies in pioneering novel biology in the wide-open parts of the field, creating a strategic advantage and potential scarcity effect.