Translating Clinical Trial Insights into Commercial Strategy: Leveraging Study Data Across the Product Lifecycle

The pharmaceutical product lifecycle has traditionally been segmented into discovery, development, and commercialization. However, this linear paradigm is increasingly inadequate in a landscape defined by complex stakeholder expectations, payer scrutiny, and real-world evidence requirements.

The return from innovation in research and development (R&D) seems to present a downward trend based on the current business and operating model across biopharma companies.¹ Thus, the R&D productivity has been put into challenge: how efficiently an organization converts resources into defined outputs (i.e., new drug launches or product commercial value).

Key factors may contribute to low R&D productivity: high complexity of science and technology, high regulatory hurdles for drug development and new drug approval, long R&D timelines, increase in discovery and development costs, expensive technology, and asset acquisition and low (clinical) success rates.²

According to an analysis performed with several pharma companies, nearly 50% of new product launches fail to meet sales expectations within the first year.³ Sustainable sales growth of a new product has been a challenge based on various factors, including potential loss of exclusivity of high-value drugs, rising supply and diagnoses costs, and rapid pace of scientific advances.⁴

Nevertheless, internal operational models that encompass early insights from commercial stakeholders can contribute to shifting strategies in order to optimize a new product’s performance within the health care environment.⁵ This discrepancy in reaching sales plan goals reflects a transition gap between clinical evidence and market adoption.

An operating model-assisted change is needed in pharmaceutical research to reverse long trend of declining returns while continuing to deliver innovation for patients. A well-thought, integrated evidence generation plan to capture insights from investigators, drug handling experiences, patient profiles, and clinical outcomes is essential to comprehensively demonstrate a therapy’s value.

A holistic approach that addresses the needs of various stakeholders—including regulatory, payers, healthcare providers, and patients—can systematically translate into actionable commercial strategies post-approval.

In response to this challenge, reshaping R&D business models by streamlining operational activities and decision-making, along with rethinking the logic of value creation through more innovative data garnering, is essential to enhance launch success and improve commercial planning.

Clinical trials generate a rich ecosystem of insights beyond primary endpoints; thus, four key domains of translational values can be considered:

1. Investigator’s experience and perception of the drug.
2. Operational feasibility and drug handling constraints.
3. Patient heterogeneity-profile, adherence, and treatment patterns.
4. Contextual interpretation of clinical outcomes.

Investigators act as intermediaries between protocol design and real-world clinical practice. Their experiential knowledge includes perceived positioning of the investigational drug, comparisons with standard of care and barriers to adoption (e.g., complexity, safety concerns).

Studies show that investigator engagement improves trial quality and generates valuable qualitative insights.⁶ Innovation cannot only be translated by the efficacy and safety of a new asset, but also by how investigators perceive the new technology and its improvement in the existing treatment.

Structured capture of investigator insights supports refinement of value propositions, identification of key opinion leaders (KOLs), and development of scientific narratives aligned with clinical practice. Qualitative methodologies (e.g., structured debriefs, advisory boards) should be taken into consideration throughout the clinical trial to collect investigators’ feedback and complement quantitative trial data—specifically on how the proposed “innovation” is considered and enhance commercialization readiness.

As a second domain, insights into drug handling and operational feasibility during clinical trials can provide early signals regarding drug administration complexity, storage and logistics requirements, and site workflow integration. Operational inefficiencies often predict real-world adoption barriers.

Evidence suggests that therapies requiring complex administration face slower uptake unless supported by robust infrastructure and training.^5,7 Moreover, logistical hurdles may impact drug delivery in remote healthcare institutions where deficiencies in transportation lead to a risk in the product integrity.

Adaptions and extra support may apply in specific regions that could impact in additional costs to the product, influencing market availability and sales. Such barriers could result in a negative outcome on market access due to operational complexity as a direct influence on physician prescribing behavior, hospital inclusion of the new asset, and reimbursement negotiations.

Another important area to be considered is the patient profiles and segmentation. While trials define populations via inclusion/exclusion criteria, deeper analyses may also reveal differential efficacy across subgroups and adherence variability per patient characteristics (i.e., demographics, age intervals, social class).

Patient-reported outcomes are part of a patient-centric framework that must be considered in the study design to emphasize integrating early and continuous insights.

Health authorities across the world (i.e., FDA, EMA, INVIMA) are extending their analysis of new products registration based on the perception of clinical trial subjects on improvement of quality of life related to the proposed treatment. This may give ammunition to direct commercial strategies on the product position within the existing market.^8,9

Patient-level insights enable identification of high-value target segments, tailored market access strategies, and design of patient support programs. Segmentation based on real response patterns improves both clinical outcomes and commercial performance.

Lastly, a broader view of clinical outcomes and operational insights is a cornerstone to product value translation. Gathering the impression of investigators during the development phases, it is possible to evaluate whether healthcare professionals (HCPs) are well prepared to deal with using the new technology within the therapeutic area (TA).

This encompasses awareness of the disease to be treated and the patient journey, as well as understanding the new mechanisms of actions to treat the target disease. It is important to understand whether the medical field is prepared to receive a new technology to be used for a specific purpose.

This helps the internal medical affairs (MAs) team and commercial to discuss and influence HCPs on the findings of a new drug and how it may improve the existing treatments. Such educational support can be identified in the beginning of clinical trials based on doubts and questions from investigators and site staff in investigators’ meetings and initiation visits, as well as throughout the study during recruitment period.

Furthermore, understanding the patient journey is crucial to identify where the subject to be treated with the new drug is situated within the healthcare system. This evaluation starts during the recruitment phase of a clinical trial and may serve as an area to direct strategies toward during the marketing phase of contacting HCPs to present the drug. Such assessment is essentially implemented in rare disease studies, which in many cases show gaps in diagnosis and may delay the start of patients’ treatment.

Lately, besides the research of a new drug, new biomarkers are being developed to be associated with the diagnosis and efficacy of the proposed treatment.¹⁰ This type of technological improvement may become a point of attention to commercial plans as the TA environment could be unprepared to receive new assets for diagnosis, prescription, and treatment.

This is directly associated with early intervention by the medical and commercial team (i.e., starting in phase II) to prepare and turn laboratories and image services capable of using the new diagnosis technology. Educational aspects are also involved as HCPs need to interpret and understand results for diagnosis, efficacy, and safety purposes.

All aspects described are very important as a larger view of clinical trials outcomes; however, results described in tables and numbers should be translated into clinical practice evidence in order to clarify the benefits of a new drug. Unclarified results and misunderstandings can lead to a lack of trust in the use of the new treatment by HCPs and patients.

Consequently, the main clinical outcomes aspects observed by investigators during clinical trials should be what the MAs team focus on teaching to HCPs in scientific events. This builds trust in the product and may reflect in prescriptions to gain market share.¹¹

As the scenario of longer cycle times to have newly approved drugs enter the market does not change, there is increased pressure to optimize the process and resources to bring products faster to market. Consequently, much is said about the speed up of clinical trials to shorten timelines and costs.

Nevertheless, pharma companies may take advantage of the development environment to collect as much data and insights as possible to drive medical and commercial strategies post-marketing. Complexity of regulatory requirements may lead to an evaluation of how prepared the healthcare system is to receive new treatments and time to companies to invest in the proper actions for commercial efficiency.

An integrated translation framework is proposed:

Cultural barriers between scientific and commercial teams exist that can lead to each area working in silos. Hence, organizational implications are needed to reduce the distance between areas (clinical, medical, and commercial), as is the implementation of a structured insight capture system and leveraging of advanced analytics in AI-driven platforms. Cross-functional integration is consistently associated with improved launch outcomes.

Clinical trials generate multidimensional insights that extend far beyond efficacy and safety. When systematically captured and translated—always based on ethical terms with the focus on the benefit of the patient—these insights can significantly enhance commercial strategy, enabling:

• More effective product positioning.
• Improved patient targeting.
• Stronger value demonstration to payers.
• Increased likelihood of launch success.

Enhancing customer and patient experience is essential to building trust, loyalty, and sustained engagement with a therapy. By adopting a patient‑centric approach and delivering personalized communications alongside comprehensive resources for healthcare professionals, pharmaceutical and biotechnology companies can effectively differentiate their therapies, strengthen brand reputation, and promote long‑term utilization and advocacy.

Future pharmaceutical success will depend on the ability to integrate scientific evidence with real-world context into a unified strategic framework.

About the Author

Giovanni Guzzo, PhD, Sr. Clinical Country & Site Lead

Associate Director, Global Clinical Operations, Biogen

References

1. Deloitte. “Seeds of Change: Measuring the return from pharmaceutical innovation 2020”. May 2021.
2. Schuhmacher, A. et al. The R&D productivity challenge: transforming the pharmaceutical ecosystem. Drug Discovery Today. Volume 30, number 11. November 2025.
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4. Deloitte. “Deloitte pharma study: R&D returns are improving – regulations could stifle innovation”. Jun 2024.
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6. Nebie EI et al. Operational Differences in Clinical Trials. Trop Med Infect Dis, 2024.
7. McKinsey & Company. Reshaping pharma strategy in the next normal. 2022.
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