How Should Oncology Drug Targets Be Chosen?

How Should Oncology Drug Targets Be Chosen? Selecting drug targets in oncology requires balancing scientific ambition with development risk. While novel targets promise transformative therapies and major commercial returns, real-world data show that target novelty declines sharply along the R&D pipeline. Although around 60% of preclinical programs pursue new targets, only about 25% of approved oncology drugs are truly first-in-class. Different modalities display distinct risk profiles, with ADCs and cell therapies favoring validated targets, while early pipelines remain more exploratory. Intense crowding around fashionable targets further amplifies systemic risk, as failures can erase massive investments. Ultimately, oncology R&D reflects a pragmatic tension between innovation and de-risked execution.

Chasing Novelty or Playing It Safe?

Drug development is almost synonymous with high investment, high risk, and high reward. Discovering a truly novel and clinically effective target is akin to winning the lottery—it can give rise to an entirely new therapeutic class. The most emblematic example is immune checkpoint blockade: PD-1/PD-L1 inhibitors generated approximately USD 55 billion in global sales in 2024 alone. Unsurprisingly, the entire oncology industry appears obsessed with the hunt for “new targets.”

But is this obsession reflected in reality?

A recent article published in Nature Reviews Drug Discovery, “Trends in target novelty in oncology R&D,” tackles a fundamental yet uncomfortable question:

Are industry resources truly being devoted to first-in-class targets, or are most efforts concentrated on incremental innovation and fast-following within already validated biology?

From Ambition to Attrition: Novelty Declines Along the R&D Pipeline

The data reveal a striking pattern.

At the preclinical stage, roughly 60% of oncology programs pursue novel targets. However, this proportion declines steadily as projects advance through development. By the time drugs reach the market, only ~25% can be classified as first-in-class therapies.

This attrition highlights a harsh reality:

novel targets carry substantial biological uncertainty and significantly higher failure rates. While many are explored early on, only a small fraction survive the long and costly journey to approval.

Modality Matters: Different Technologies, Different Risk Appetites

When approved drugs are analyzed by modality, the divergence becomes even clearer:

Small molecules: only 26% target novel biology

Conventional monoclonal antibodies: around 32%

Fusion proteins: nearly 70%—the most “adventurous” class

Cell therapies (e.g., CAR-T): just ~10%, overwhelmingly focused on well-validated targets such as CD19 and BCMA.

Cell therapies, despite their technological sophistication, are paradoxically among the most conservative in target selection, reflecting the enormous manufacturing, safety, and regulatory risks layered on top of target uncertainty.

Pipelines vs. Products: Idealism Meets Reality

Looking at clinical pipelines, a different picture emerges.

With the exception of ADCs and cell therapies, 40–60% of pipeline programs across most modalities still pursue novel targets—a much higher proportion than seen among approved drugs.

This contrast reflects the tension between scientific ambition and commercial reality. Early-stage R&D is driven by bold hypotheses and unmet needs, but late-stage success disproportionately favors programs built on established biology.

ADCs: Standing on the Shoulders of Giants

Antibody–drug conjugates (ADCs) offer a particularly instructive case.

Unlike most modalities, ADC pipelines are even more conservative than their approved counterparts, with a heavy bias toward validated targets. This reflects a deliberate and arguably rational strategy: “stand on the shoulders of giants.”

HER2 exemplifies this approach. With the success of trastuzumab firmly establishing HER2 as a viable target, subsequent innovation focused not on reinventing the antibody, but on optimizing payloads and linkers, leading to breakthrough ADCs such as T-DM1 and T-DXd.

Rather than gambling on unproven targets, ADC developers often choose to de-risk target biology and innovate elsewhere in the molecule. This is why the most common ADC “targets” today include familiar names like HER2 and TOP1, both long-validated components of oncology therapeutics.

“Me-Too Before the First Me”: Crowding Around the Same Novel Targets

Even when the industry does pursue novelty, it is far from evenly distributed.

The article aptly describes the phenomenon as “me-too before the first me.” In many cases, crowding begins before the first drug against a target is even approved.

In the antibody space, CD137 (4-1BB) has become the hottest emerging target, with 42 programs currently in development, including 30 multi-specific antibodies.

This reflects attempts to balance efficacy and safety by combining immune co-stimulation with tumor targeting.

In small molecules, CDK2 leads the pack with 17 active programs, largely driven by efforts to overcome resistance to CDK4/6 inhibitors and to target specific genetic contexts in solid tumors.

In ADCs, novel targets are comparatively rare—but CD276 (B7-H3) stands out, with 12 programs in development. Earlier monoclonal antibodies against CD276 failed clinically, but ADC developers are betting that a “precision payload delivery” approach may unlock efficacy in hard-to-treat cancers such as small-cell lung cancer.

First-in-Class vs. Fast-Follow: A False Dichotomy?

There is no question that first-in-class drugs offer outsized rewards. However, history shows that second- or third-in-class agents can be equally, if not more, commercially successful.

EGFR inhibitors illustrate this well.

The first-generation drug gefitinib achieved modest success, while later generations—erlotinib and especially osimertinib—went on to dominate the market. Such examples continue to reinforce confidence in fast-follow strategies, particularly when the market is large enough to support multiple blockbuster products.

The Hidden Cost of Herd Behavior

Yet concentration around a handful of fashionable targets carries enormous systemic risk.

When a target ultimately fails—as seen recently with TIGIT inhibitors, where multiple phase III trials collapsed in quick succession—the consequences are severe. Billions of dollars in R&D investment can evaporate almost overnight, representing not just corporate losses, but a profound inefficiency in the allocation of scientific resources.