The End of Empiricism: Merck Bets Big on Biomarker-Led Oncology

Background: ASCO 2025 and the Normalization of Precision

At ASCO 2025, precision medicine no longer presented as an aspirational ideal. It has become a practical necessity. Across tumor types and modalities, the most prominent development programs were those guided by biomarker-driven patient selection. Biomarkers have become central to clinical trial design, regulatory alignment, and commercial differentiation. Their role is expanding from predictive diagnostics into tools for adaptive trial refinement, real-world patient stratification, and even drug lifecycle extension.

The strategic rationale is clear.

• From a regulatory standpoint, biomarker-based enrichment supports accelerated approvals and stronger label claims.

• From a clinical development standpoint, it enables higher responder rates and greater trial efficiency.

• From a commercial standpoint, it underpins value-based pricing by linking therapy to measurable clinical benefit in defined subpopulations.

These signals point to a structural shift. Successful oncology pipelines are increasingly organized not by modality but by the strength of their biomarker-linked development logic.

Context: Merck’s Reorientation Around Precision Oncology

Merck’s June 2nd 2025 investor call, held alongside ASCO, illustrates a deliberate and systematic reorientation of its oncology strategy around precision medicine. Several developments stand out.

Expanding Beyond PD-L1: Toward Multi-Modal Biomarker Strategies

While Merck continues to advance KEYTRUDA’s PD-L1-driven indications, including new formulations such as subcutaneous delivery for improved accessibility, the company is also clearly broadening its biomarker footprint. Across discovery and development, Merck is investing in digital pathology, multiplexed immunohistochemistry, and AI-supported imaging biomarkers. These tools are being applied particularly in bladder, gynecologic, and hematologic cancers, where standard biomarker frameworks remain underdeveloped.

This evolution reflects a broader industry trend toward more integrated, multi-modal biomarker strategies. Rather than relying solely on single-protein expression, companies are increasingly incorporating composite biomarkers and digitally enriched endpoints to improve predictive power and refine patient selection.

However, this shift also highlights the limitations of first-generation biomarkers like PD-L1. Assay variability, dynamic expression across tumor microenvironments, and weak correlation with long-term benefit continue to challenge reproducibility. Similarly, in modalities like antibody-drug conjugates (ADCs), target expression alone does not guarantee efficacy. Payload potency, linker stability, and intratumoral heterogeneity frequently shape therapeutic response more than antigen presence itself.

Merck’s strategy suggests a recognition of these complexities. By expanding its biomarker infrastructure across AI, pathology, and in silico modeling, the company is positioning itself to navigate the next chapter of precision oncology—one that depends less on static markers and more on dynamic, context-aware signatures.

Portfolio Prioritization Through Precision

Merck executives emphasized that portfolio prioritization is increasingly being driven by biomarker viability. The company is focusing on indications where stratification is feasible, scalable, and clinically meaningful. For instance, it is allocating resources toward solid tumors in women’s health, which account for approximately 30 percent of anticipated pipeline revenue by the mid-2030s, and hematologic malignancies, which contribute approximately 15 percent. These areas offer clear opportunities for biomarker-defined subgroups to enhance both clinical outcomes and payer alignment. For example, in endometrial cancer, mismatch repair deficiency (dMMR) and microsatellite instability-high (MSI-H) status guide the use of immune checkpoint inhibitors such as pembrolizumab. In triple-negative breast cancer, PD-L1 expression and BRCA mutation status inform the use of immunotherapy and PARP inhibitors. In hematologic malignancies like diffuse large B-cell lymphoma (DLBCL), CD19 expression determines eligibility for CAR-T therapies, while molecular profiling helps distinguish high-risk subtypes that may require tailored interventions. Even so, resistance mechanisms, tumor evolution, and changes in biomarker expression over time can erode the durability of these strategies. As Merck deepens its investment in precision platforms, these biological realities must inform both trial design and post-marketing surveillance.

Embedding AI and Computational Trial Design

In addition to classical biomarker stratification, Merck is applying AI to pre-trial modeling. By simulating likely responders based on multi-omic and imaging data, the company reduces uncertainty, particularly in early-phase trials. This aligns with a broader trend toward in silico patient profiling as a complement to real-world evidence. Yet Merck is not alone in this space. Roche, AstraZeneca, and several biotechs are also pursuing trial optimization through predictive modeling. The question for investors is whether Merck’s data, infrastructure, or clinical network give it a sustained executional edge. Without clearer articulation of what is proprietary versus commoditized, competitive differentiation remains ambiguous.

Implications: Strategic Consequences for the Biopharma Ecosystem

Merck’s approach offers a set of implications for both incumbents and emerging biotech companies.

Clinical Development Will Become Smaller, Smarter, and More Selective

The assumption that large, empiric Phase III trials remain the gold standard is giving way to leaner, biomarker-enriched studies with stronger signal-to-noise ratios. For companies that can execute this model, time-to-decision shortens and the cost of failure declines. However, the risk-adjusted cost of biomarker validation, companion diagnostic development, and regulatory harmonization remains high.

Companion Diagnostics and Formulation Innovation Will Anchor Competitive Advantage

Merck’s subcutaneous KEYTRUDA program is not simply a delivery optimization. It is part of a broader strategy to enhance access, adherence, and ultimately outcomes in biomarker-defined populations. Companion diagnostics and patient-centric formulations are now strategic assets. Nevertheless, payer resistance to reimbursing diagnostics and new formulations can slow uptake. Regulatory frameworks for co-approval also add complexity.

Data Integration Will Define Differentiation

As biomarkers become more complex, ranging from spatial transcriptomics to AI-derived radiomic signatures, the ability to integrate clinical, digital, and molecular datasets will define future leaders. Merck’s investment in digital pathology and AI-driven stratification positions it well. Yet execution will depend on cross-functional capabilities that are still being built across the industry.

Capital Markets Will Reward Clarity of Biomarker Strategy

From a financing perspective, companies with clearly defined biomarker strategies and demonstrated success in executing stratified trials will attract higher valuations, stronger business development interest, and faster regulatory alignment. Precision is no longer a scientific differentiator. It is a signaling mechanism to capital markets that the underlying asset is clinically de-risked and commercially viable. Still, the cost of being wrong, backing a biomarker hypothesis that fails in Phase III, remains substantial.

Conclusion

Merck’s current oncology strategy exemplifies a broader shift in biopharmaceutical R&D. The industry is moving from population-based empiricism to biologically informed precision. Biomarker-driven development is not a temporary trend. It represents a structural reconfiguration of how therapies are discovered, validated, and delivered. However, precision medicine introduces its own risks. Assay reproducibility, biological variability, and resistance dynamics demand a more adaptive and humble model of drug development. Merck’s long-term success will depend not only on its ability to integrate biomarkers across the pipeline but also on its ability to respond when those biomarkers inevitably fall short. For investors, developers, and policymakers alike, the message is clear. The value chain now begins at the biomarker, but it does not end there.

Source: Merck Investors

Dillon Shokar, (Biostatistics, King's College London; Data Science, Harvard), CFA

Biopharma Venture Partner | Strategy Consultant