Understanding the Starting Point: Unmet Medical Need
Building a new cancer therapy begins not with a molecule, but with a clinical problem that has not yet been solved. In hematologic malignancies such as multiple myeloma and acute leukemia, the starting point is often disease relapse, resistance to existing treatments, or a lack of durable response in specific patient populations. As a translational scientist, I have learned that the most important early step is defining this unmet need with precision. Without a clear clinical question, even the most sophisticated biological discoveries risk lacking direction or relevance.
Identifying a Biological Target That Matters
Once the clinical problem is defined, the next step is to identify biological systems that drive disease persistence or progression. This requires deep investigation into tumor biology, including surface antigens, intracellular signaling networks, and epigenetic regulators. In multiple myeloma, targets such as CD38 and CD84 represent examples of molecules that are not only present on malignant cells but also functionally relevant to their survival or immune evasion. The challenge is to distinguish between markers of disease and drivers of disease, as only the latter provide meaningful therapeutic opportunities.
Validating the Target Through Functional Science
A potential target must undergo rigorous functional validation before it can be considered therapeutically actionable. This involves experimental strategies such as gene knockdown, antibody blockade, or pharmacologic inhibition to determine whether disrupting the target affects cancer cell viability, proliferation, or interaction with the microenvironment. This stage is essential because it separates correlation from causation. In translational oncology, only targets that demonstrate reproducible biological dependency are advanced toward therapeutic development.
Designing a Therapeutic Strategy Around Biology
Once a target is validated, the focus shifts toward therapeutic design. This is where biology begins to intersect with engineering and clinical science. Depending on the nature of the target, a therapy may take the form of a monoclonal antibody, antibody drug conjugate, radiolabeled compound, bispecific T cell engager, or cellular therapy such as CAR T cells. Each platform has distinct advantages and limitations, and selecting the appropriate modality requires careful consideration of tumor biology, tissue distribution, and immune system engagement. In my own work, particularly with CD38 directed strategies and radioimmunotherapy, therapeutic design is guided by a continuous exchange between laboratory findings and clinical constraints.
Translating Preclinical Evidence into Predictive Models
Before a therapy can be considered for human testing, it must demonstrate activity in preclinical systems that approximate human disease. These include in vitro cell systems, xenograft models, genetically engineered mouse models, and increasingly organoid platforms. Each model provides a different level of biological complexity, and together they help predict efficacy, toxicity, and pharmacokinetics. While no model fully captures the complexity of human cancer, they are essential for de risking therapeutic candidates and refining dosing strategies prior to clinical exposure.
Navigating the Complexity of Early Clinical Trials
Early phase clinical trials represent the first opportunity to evaluate a new therapy in patients. These studies are designed primarily to assess safety, tolerability, and appropriate dosing rather than definitive efficacy. However, they also provide critical insight into biological activity in humans. Designing these trials requires close collaboration between laboratory scientists and clinical investigators to ensure that translational hypotheses are embedded into study protocols. Patient selection, dosing schedules, and response criteria must all reflect both scientific rationale and clinical feasibility.
Integrating Biomarkers to Measure Biological Impact
Biomarkers are essential for understanding whether a therapy is functioning as intended. They provide measurable indicators of target engagement, pathway modulation, and disease response. In multiple myeloma, biomarkers may include circulating tumor components, immune profiling, or molecular signatures derived from tumor cells. These data allow researchers to interpret clinical outcomes in a mechanistic context, ensuring that observed responses are not only measured but understood at a biological level.
The Iterative Cycle Between Laboratory and Clinic
Drug development is not a linear progression but an iterative cycle. Observations from clinical trials often return to the laboratory, where they refine hypotheses and guide the next generation of experiments. Similarly, unexpected laboratory findings can reshape clinical strategy, trial design, and therapeutic combinations. This continuous feedback loop is one of the defining features of translational oncology and is essential for meaningful innovation in cancer therapy development.
Why Building Cancer Therapies Requires Scientific Persistence
Ultimately, developing a new cancer therapy requires persistence, interdisciplinary collaboration, and a willingness to navigate uncertainty. Each stage, from target identification to clinical validation, involves complex decision making and repeated refinement. The process is long and often unpredictable, but it is also deeply purposeful. The goal is not only to create new treatments but to meaningfully improve outcomes for patients facing life-threatening disease.