How AI and real-world data generate predictive insights for drug development
Predictive AI depends on clinically rich real-world data. Learn how organizations generate predictive insights for drug development.
Using real-world evidence to pressure-test oncology target product profiles
What is needed to define an oncology target product profile?
Organizations need to know whether a target product profile (TPP) reflects real-world clinical practice before committing significant time, resources, and investment to an oncology program. To do that, they must pressure-test patient selection, unmet need, standard-of-care assumptions, differentiation potential, and future evidence requirements before the strategy becomes difficult to change.
Key questions for oncology target product profile development include:
- Which patient populations remain underserved?
- What are the limitations of current standards of care?
- Which outcomes matter most to patients, providers, and payers?
- How do treatment pathways vary across patient populations?
- What level of clinical benefit would represent meaningful differentiation?
- Which evidence will likely be required to support regulatory, HTA, and reimbursement decisions?
To answer those questions, teams need evidence that supports:
Together, these evidence inputs help convert the target product profile from a planning assumption into a testable strategy grounded in real-world clinical practice and future stakeholder expectations.
Why this matters for early oncology development
Early oncology development decisions can shape the entire trajectory of a program. Target population, differentiation strategy, evidence requirements, and investment priorities are often defined before trial data is available, which makes it critical to test whether the opportunity is clinically meaningful and commercially viable in the real world.
Without a robust view of real-world clinical practice, organizations risk:
- Prioritizing patient populations with limited unmet need
- Pursuing differentiation strategies that may offer insufficient value to clinicians, payers, or regulators
- Selecting endpoints that do not align with future stakeholder expectations
- Overlooking variability in treatment pathways, biomarker use, and patient outcomes
- Underestimating future regulatory, HTA, and reimbursement evidence requirements
- Allocating resources toward lower-priority opportunities while higher-value opportunities remain unexplored
As a result, organizations may commit significant investment to strategies that are less likely to demonstrate value, achieve differentiation, or support future market access. That risk makes early evidence alignment essential before programs advance and strategic flexibility narrows.
Why oncology target product profiles are difficult to validate
Even when teams know which questions to ask, validating an oncology target product profile can be difficult. The evidence needed to test those assumptions is often fragmented, inconsistent, or slow to assemble across patient populations, care settings, and markets.
How real-world evidence supports target product profile development
That is where real-world evidence can play a more strategic role. When the data and methods are matched to the TPP question, RWE can help teams test whether the proposed profile is realistic, differentiated, and aligned with future evidence expectations.
Together, these analyses help teams pressure-test the target product profile, reduce uncertainty, and focus development resources on opportunities with stronger clinical and market rationale.
For RWE to support TPP decisions, more data is not enough. The evidence must be clinically relevant, harmonized across sources, integrated into a research-ready structure, supported by clear provenance and governance, and available through secure, compliant environments. Without those foundations, teams may have data access without the decision-ready evidence they need.
How RWE supports biomarker-driven NSCLC strategy across Europe
A global biopharmaceutical company developing a targeted therapy for non-small cell lung cancer (NSCLC) needed clearer evidence on biomarker-defined patient populations, treatment pathways, and clinical practice across multiple European markets. Variability in biomarker testing, patient identification, and treatment sequencing made it difficult to size the addressable population and assess differentiation opportunities.
Working with BC Platforms, the organization established a multi-country real-world evidence cohort spanning the UK, Germany, and Spain. The study analyzed biomarker testing practices, patient identification, treatment pathways, and outcomes across different healthcare systems.
The resulting evidence provided greater visibility into biomarker-defined populations, treatment dynamics, and unmet need. These insights helped inform evidence strategy, market planning, and product lifecycle decisions.
Why choose BC Platforms for oncology real-world evidence
BC Platforms helps life sciences organizations pressure-test oncology target product profiles using clinically rich real-world data, harmonized datasets, analytics, secure research environments, and scientific and technical expertise. Depending on the development question, organizations may use curated data, custom datasets, or built-for-purpose evidence networks. These resources can be designed around specific patient cohorts, geographies, and governance requirements.
These capabilities help teams move from assumption-based planning to evidence-informed oncology development strategy. They provide the data foundation, analytics, governance, infrastructure, and expert support needed to answer complex TPP questions.
Conclusion
Teams make some of the most consequential oncology development trade-offs before a patient enters a clinical trial. The risk is not simply choosing the wrong patient population or missing an unmet need. Teams may discover too late that the TPP relies on assumptions about testing, treatment sequencing, outcomes, or evidence expectations that do not hold up in routine care.
As a result, delayed timelines, additional analyses, protocol or evidence-plan rework, higher development costs, and weaker alignment across clinical, regulatory, market access, medical, and commercial teams can follow. However, decision-ready RWE can surface these issues while the strategy remains flexible.
Ultimately, the strongest evidence strategies start with the TPP question. They then bring together the data sources, cohorts, methods, secure access, and analytics needed to assess the opportunity. This helps determine whether it is meaningful, differentiated, and ready for the next investment decision.
Is your oncology TPP built on the right evidence for the decision you need to make?
BC Platforms helps organizations use fit-for-purpose real-world data, analytics, and expert support to pressure-test oncology TPP assumptions before key development decisions are finalized.
FAQs
A target product profile (TPP) is a strategic framework that outlines the desired characteristics of a future therapy, including target patient populations, clinical outcomes, safety expectations, differentiation strategy, and evidence requirements. It helps align development, regulatory, medical, and commercial planning.
Real-world evidence supports target product profile development by showing whether assumptions about patient identification, biomarker testing, treatment sequencing, outcomes, and evidence requirements reflect routine clinical practice. It is most useful when the data sources, cohorts, methods, secure access, and analytics are matched to the specific TPP question.
Real-world evidence is important in early oncology development because many high-impact decisions are made before clinical trial results are available. RWE can help teams test assumptions while the strategy is still flexible, reducing the risk of late-stage evidence gaps, rework, timeline delays, and avoidable costs.
Real-world data can reveal where current therapies fall short by connecting treatment patterns, outcomes, patient subgroups, and unmet need. Those insights help teams determine whether a future therapy has a credible path to meaningful clinical or market differentiation.
BC Platforms supports oncology development strategy by providing access to clinically rich real-world data, including curated data, custom datasets, and built-for-purpose evidence networks, along with data harmonization, analytics, trusted research environments, and consulting and technology services. These capabilities help teams pressure-test core TPP assumptions when defining or refining an oncology target product profile.
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