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Asembia 2025 

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Sales and Marketing

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Loss of exclusivity (LOE) doesn’t have to be the death knell for branded drug revenue streams. The key approaches to preserving meaningful value well into the post-patent-loss future are outlined.

Loss of Exclusivity: Strategies to Maximize Product Value

AbbVie Pedro Valencia ADCs

PE: How is AbbVie using novel cancer biomarkers to develop potential first-in-class ADCs for the treatment of advanced solid tumors?

We're constantly looking for biomarkers that can help us to do two key things. The first is to tackle cancer cells. and spare normal cells. We’re looking for specific antigens that are over-expressing tumor cells, and you see limited expression in normal cells. We want to make sure that target that’s over-expressed is critical for the survival of the cancer cell. Once you block it, you can actually drive a cancer cell death. That’s what we're looking for. In that perspective, c-Met is one of those biomarkers that is over expressing multiple tumor types such as lung, colorectal, gastric, and other GA tumors. We as an industry have tried to tackle c-Met in the past but have been unsuccessful. It would actually be successful to tackle what we call met, which is a gene inside the cell.

There’s this thing called met amplification, where the cancer cell produces multiple copies of the gene, and around 30% of patients have it. We can actually tackle that with small molecules. But once the gene becomes a protein and gets over-expressed in the cell, that over-expression is something we haven’t been able to target. For example, we know that on lung cancer, c-Met over-expression is about 25% to 50% in colorectal cancer, and it could be anywhere from 30% to 70% depending how you measure it, so it’s quite prevalent.

With ADCs, we’re trying to tackle c-Met over-expression on the surface of cancer cells. That was novel, and we can do it through ADCs. 706 has a target called SEZ6, and it’s a target that is over expressed in neuroendocrine cells or neuroendocrine neoplasms. When you think about it, multiple tumor types kind of have a subset of cells that are neuroendocrine driven. Small cell lung cancer is one of the few that has everything driven by neuroendocrine cells. The beauty of SEZ6 is over-expressing those cells and limited expression in normal cells. So, we can tackle it with an ADC and drive the results that we're seeing today.

PE: ADCs have redefined the treatment of cancer in recent years. Can you please discuss the promise of this emerging class and what the future may hold?

At the end of the day, ADCs work like a trojan horse. You have a good antibody that cancer cells are happy to receive, but once you hook into the cancer cell receptor, you deliver the payload, which is pretty much chemotherapy. It’s actually a highly potent version of the regular chemotherapy cancer patients are given on a regular basis. So, from that perspective, our goal is to replace chemotherapy. Our grand goal with ADCs is to replace good old, decades old chemotherapy that is really toxic for some patients. That’s how we see the redefinition of cancer treatment in the future with ADCs. So, what do we see in the future? Well, if you think about it, chemotherapy is being given in combination with other agents. In the future, we see ADCs being given in combination with chemotherapy. There will be one with other agents such as immuno-oncology agents. So, if you combine the ADC and the PD1s, you can start seeing that synergy come together and kind of start really dreaming about cures for the patients. All in all, we're super excited about ADCs replacing chemotherapy. 

In an interview with Pharm Exec Associate Editor Don Tracy, Pedro Valencia, VP, Solid Tumor Pipeline Strategy & Execution, AbbVie, discusses using novel cancer biomarkers to develop potential first-in-class antibody drug conjugates (ADCs) and the promise that they offer. 

Utilizing Biomarkers to Develop First-in-Class Antibody Drug Conjugates to Treat Advanced Solid Tumors

The life sciences industry has witnessed remarkable technological advancements over the past three decades—from groundbreaking therapies to sophisticated marketing approaches. Yet beneath these innovations lies a paradox: The fundamental infrastructure powering our analytics ecosystems has remained largely unchanged. While end capabilities evolve, core data management principles continue to follow frameworks established when digital transformation was in its infancy. This stagnation has created several challenges facing modern biopharmaceutical organizations, including data use limitations.

Leading companies typically allocate millions of dollars annually to maintain and enhance commercial data and analytics ecosystems. Despite this substantial investment, incorporating new datasets or introducing novel key performance indicators (KPIs) remains extraordinarily time-consuming.

When a brand manager wants to integrate insights from market research into their performance dashboard, for instance, they face a timeline of two to five months of development before that single KPI becomes operational.

This implementation delay has a cascading effect throughout commercial operations. By the time insights materialize, market conditions may have evolved, diminishing the relevance of the enhancement. Decision-makers often resort to alternative approaches and use unconnected spreadsheets or separate data sources outside the governed systems. Doing so compromises data integrity and fosters inconsistent versions of the truth throughout the organization.

The issue is further complicated by what experts term the “data-rich, information-poor” syndrome, where valuable information is held in isolated warehouses, leading to poor knowledge management and, subsequently, data utilization. This technological challenge carries a significant opportunity cost for businesses.

Large language models (LLMs) have evolved rapidly, each iteration bringing increasingly sophisticated capabilities to life sciences data management. Early standard LLMs performed with the proficiency of an entry-level data analyst, primarily handling well-defined tasks with clear parameters. As reasoning capabilities emerged, these systems advanced to match senior data analyst competencies, conducting more nuanced data interpretation. Today’s deep-research-capable models operate with the strategic insight of a senior consultant, addressing complex business questions with minimal guidance.

This evolution has dramatically expanded the range of use cases that artificial intelligence (AI) can effectively address. More importantly, with each advancement, these systems have demonstrated an increasing ability to tackle the multifaceted challenges that previously required extensive human intervention across the data life cycle.

The rapid advances in model capabilities have set the stage for a fundamental shift in how AI functions within data ecosystems. This is where the concept of agentic AI emerges as a transformative force in pharmaceutical and healthcare analytics.

Unlike basic generative AI, which responds to specific prompts or executes predefined tasks, agentic AI combines multiple AI streams to operate with greater autonomy. This approach creates a multitiered intelligence ecosystem: Data agents access and prepare information from various sources; analytical agents apply algorithms and statistical methods to this prepared data; and orchestrating agents coordinate these activities to deliver coherent insights aligned with business objectives.

Rather than moving sequentially through distinct systems, this orchestrated approach enables direct connections with data sources, automatic processing and standardization, verification against business rules, and dynamic visualization creation—all with significantly less reliance on traditional development cycles.

Early exploratory work suggests this model can deliver considerable benefits, with initial proofs of concept indicating potential efficiency improvements of 50% to 70% in metric development processes.

While these results are preliminary, they suggest the possible impact agentic AI could have on data management in an information-driven life sciences environment.

Despite these promising possibilities, biopharma companies should approach agentic AI exploration with circumspection. The concept represents a significant departure in how information might flow, and any successful implementation would require both technical preparedness and organizational alignment.

Leaders should understand that while the vision of highly autonomous data systems represents an ambitious objective, the journey would require intermediate milestones. A phased implementation approach should be considered:

Begin with defined proof-of-concept projects that solve a core problem for a single brand or target segment.

Establish transparent metrics for success, focusing on improvements in efficiency and quality.

Document insights and refine the process before expanding to broader applications.

Plan for appropriate human oversight, particularly for business-critical analyses.

This measured approach recognizes that while agentic AI shows transformative potential for data ecosystems, current implementations remain primarily conceptual.

By focusing on small-scale experiments, life sciences organizations can build and foster confidence in the approach while developing institutional knowledge that would support broader exploration.

An important consideration when implementing sophisticated AI systems is their non-deterministic nature. Unlike traditional analytics tools that produce identical outputs given the same inputs, advanced language models may generate slightly different content when asked the same question multiple times.

While key facts and insights remain consistent, variations in presentation or emphasis might occur—such as how different consultants might approach the same business problem with unique perspectives. In regulated environments, this characteristic necessitates appropriate governance frameworks and human oversight to ensure consistency in critical decision-making contexts. Thus, it is important to maintain “human-in-the-loop” validation for sensitive or high-stakes analyses, with AI handling mechanical aspects while domain experts provide context.

For example, when crafting content for executive dashboards, agents might autonomously update metrics and generate preliminary visualizations but have a business analyst examine the outputs before distribution. This would ensure that anomalies receive appropriate investigation and insights align with business context that may not be fully captured in the data alone.

While current conceptual frameworks primarily center on streamlining data workflows and improving insight generation, agentic AI could have other valuable applications, including:

Custom insight narratives that adjust not only to the data but to the preferences and priorities of individual stakeholders.

Recommendation systems that propose not just what occurred but which strategies might most effectively address emerging trends and challenges.

Assistance with assembling briefing documents that compile relevant information before key meetings or decisions.

Support with refreshing forecasts to incorporate new market signals with minimal manual intervention.

Perhaps most significantly, these capabilities might democratize access to analytics. Rather than demanding specialized technical proficiency to create new insights, business users could interact with agents that comprehend their needs and convert requests into appropriate analyses—shifting from tool-centric to purpose-centric analytics.

The 30-year stagnation in life sciences data management principles presents both a challenge and an opportunity. Organizations that successfully explore the development and integration of agentic AI could achieve incremental gains in efficiency and meaningful progress in how insights inform decision-making.

For executives examining this emerging area, here are four guiding principles to consider:

Begin with business challenges instead of technology capabilities and identify specific decisions that would benefit from more responsive insights.

Consider investments in foundational data governance that would allow future AI systems to access high-quality, well-documented information.

Assemble cross-functional teams that combine technical expertise with domain knowledge and change-management capabilities.

Establish appropriate review processes for outputs that require absolute consistency.

The life sciences industry is at a potential turning point in how data is managed and insights are generated. By approaching agentic AI concepts with strategic vision and operational discipline, it’s possible to move beyond decades-old limitations and create analytics ecosystems that enable better and improved data-driven decision-making in complex markets.

Tanveer Ahmed Nasir is Vice President and General Manager, Product Management, IQVIA; William O’Reilly is Director, Product Offering Development, IQVIA

1. Rink, C.; O’Reilly, W. Where to Deploy Generative AI Solutions in Life Sciences. IQVIA white paper. March 19, 2025. 

https://www.iqvia.com/library/white-papers/where-to-deploy-generative-ai-solutions-in-life-sciences

2. Nasir, T.A.; Haslam, T. Inside Agentic AI: Reshaping Decisions and Orchestration in Life Sciences. IQVIA blog. February 28, 2025. 

https://www.iqvia.com/blogs/2025/02/inside-agentic-ai-reshaping-decisions-and-orchestration-in-life-sciences.iqvia.com/library/white-papers/where-to-deploy-generative-ai-solutions-in-life-sciences

Technological advancements in the life sciences industry have not been matched by progress in data management infrastructure, leading to inefficiencies in data utilization. Despite significant investments, incorporating new datasets and KPIs remains slow, causing decision-makers to rely on ungoverned data sources. The emergence of agentic AI offers a transformative potential by enabling autonomous data processing and insight generation, promising efficiency improvements. However, successful implementation requires a phased approach, human oversight, and robust governance frameworks. Agentic AI could democratize analytics, shifting focus from tool-centric to purpose-centric insights.

Strategies for biopharma in integrating agentic AI—to achieve incremental gains in efficiency, while delivering meaningful progress in how data insights inform commercial decision-making.

Approaching Agentic AI Strategically: Life Sciences Data Utilization

When we think about access inequity, we often have the immediate image of a low-income nation unable to afford essential medicines. While this may be partly true, it’s not a problem exclusive to this demographic. IVQIA’s EFPIA Patients W.A.I.T. Indicator 2024 Survey highlights that many European countries also face significant challenges in making innovative medicines available. The issue is bigger than we realize, but it’s not without a solution.

Access inequity is, in general, a death by a thousand paper cuts. It’s rarely only about unaffordability, but rather a multitude of smaller, interconnected operational and bureaucratic challenges that collectively hinder patients from receiving life-saving treatments they desperately need.

For pharmaceutical executives, access inequity is a fundamental business issue. When only a fraction of the target population can access a product, the remaining portion represents a missed commercial opportunity. Understanding and addressing the hurdles of drug access is not merely a humanitarian gesture; it’s a critical strategic necessity to realize the value of R&D investment, enhance corporate reputation, and secure long-term global growth.

Nuances of access inequity beyond the price tag

The landscape of access inequity is highly fragmented and different across various therapeutic areas. Essential medicines, rare disease medicines, oncology drugs, and chronic disease therapies each present unique access challenges with distinct market dynamics and regulatory pathways. For instance, while over 60% of global pharmaceutical revenue traditionally comes from the US, in the highly specialized area of rare disease, this figure drops to just 35%, even as the price differential between the US and Europe can be significant. This figure highlights that the issue extends beyond simple purchasing power.

In my experience, to effectively address and capitalize on these complex issues, the focus should be on specific segments and incrementally resolving issues, rather than attempting a broad, uncoordinated “boil the ocean” approach. We need to rethink our assumptions about affordability, as our current perspective might be a significant blind spot for growth.

Realizing the full value of R&D investment

Contrary to conventional wisdom, there are surprisingly high levels of affordability in lower-income countries for high-unmet-need medicines, particularly in rare diseases. While hard data is scarce, anecdotes suggest that these nations, despite limited overall healthcare budgets, can allocate significant resources and have the capacity to pay top dollar for certain rare disease treatments. This isn’t an issue of limited budgets, but one of different priorities. For many countries, spending focuses on what they perceive as a worthwhile investment, which may be substantially different to what we see in the US. This is why some nations will invest heavily for rare disease treatments while simultaneously allocating zero funds for blockbuster chronic treatments that are commonplace in the US.

While these countries' healthcare systems are not perfect, we often underestimate their willingness to spend significant funds on what they consider a priority. They may have limited resources, but they have a surprising capacity to pay a high price for specific, high-unmet-need medicines, particularly for rare diseases.

While we often think of access to medicine as a problem for low-income countries, these issues exist everywhere, including in developed nations. The reason isn’t a single, major policy failure, but a series of a "thousand paper cuts"—a collection of small, systemic hurdles that make it impossible for small-to-midsize biotech companies to operate effectively. However, many countries are finding innovative ways to fund expensive rare disease treatments, demonstrating that a lack of funding isn't always the issue.

 These governments have made high-cost therapies like Zolgensma for Spinal Muscular Atrophy (SMA) a national priority through dedicated budget allocations and presidential initiatives, ensuring free access for patients.

 Argentina used an outcomes-based deal for Zolgensma, paying a discounted price only if the therapy works.

 Brazil is manufacturing its own CAR-T cell therapy to cut costs for cancer patients, while Thailand has included expensive enzyme replacement therapy for Gaucher disease in its universal health coverage.

 India launched National Policy for Rare Diseases (NPRD) that provides a one-time grant for rare disease treatments, marking a first step towards public funding for orphan drugs, even with its limitations.

Pharmaceutical companies are generally flexible in terms of pricing structures, provided such arrangements do not negatively impact broader market dynamics. The net price of rare disease drugs can sometimes be higher in lower-income countries than in more developed markets. This is not due to exploitation, but to the absence of the sophisticated negotiation infrastructure found in larger, established markets. While managed access programs are common in the West, their lack of presence in these regions necessitates a proactive and transparent approach to pricing.

The thousand paper cuts theory and operational complexity

Innovation, especially in rare disease treatments, comes from small, agile biotechs with limited global commercial infrastructure. This brings us back to the “thousand paper cuts” theory of access inequity. Beyond pricing, there is an overwhelming operational complexity involved in access. Adding to this is the intricate process of actually supplying these treatments across diverse regulatory and logistical landscapes. This is where the issues truly pile up:

Export and Import Permit Procedures: This is often a very difficult process. Even affluent countries with funds to pay top dollar for medications face administrative complexity and delays in simply importing products. This highlights a critical need for small to midsize biotechs to be able to generate the necessary documents to comply with the requirements.

Compliance: Navigating diverse regulatory landscapes adds immense time, cost, and bureaucratic burden, delaying patient access. It is necessary to understand national regulatory frameworks and country-specific submissions and interpretations in order to avoid delays in patient accessibility to life-altering treatments.

Quality Control & Supply Chain Integrity: Maintaining the integrity and quality of products across borders presents ongoing challenges for less developed logistics networks. Upholding stringent GDP standards throughout the supply chain, from manufacturing to patient delivery, is critical for retaining product quality and ensuring complete traceability.

Payments & Financial Logistics: International financial transactions, currency controls, and varied payment systems can be a challenge with inefficiencies and delays, affecting the consistent supply of treatments. As such, a different commercial and financing approach is needed – one that focuses on cash and risk mitigation as opposed to EBITDA.

Individually, these hurdles may seem minor, but their combined effect can transform what should be a straightforward process into a logistical nightmare. For pharmaceutical executives, addressing these “paper cuts” with a strategic approach and innovative operational models is not just about fulfilling a humanitarian mission; it is about transforming untapped patient populations into viable markets, driving sustainable growth, and strengthening a competitive advantage in a globalized industry.

Access inequity in healthcare is a multifaceted issue affecting both low-income and developed nations, driven by operational and bureaucratic challenges rather than just affordability. Pharmaceutical companies face strategic business implications due to limited access, impacting R&D investment returns and market growth. Rare disease treatments highlight disparities, with some lower-income countries prioritizing high-cost therapies despite limited budgets. Operational complexities, such as regulatory compliance and supply chain integrity, exacerbate access issues. Addressing these challenges requires innovative strategies to transform untapped patient populations into viable markets, ensuring sustainable growth and competitive advantage.

Access inequity is a multitude of smaller, interconnected operational and bureaucratic challenges.

Preventing Suffering Through Access: A Strategic Imperative for Global Pharmaceutical Growth

The FDA has issued a second complete response letter (CRL) to Regeneron’s odronextamab based on issues with a third-party manufacturing site purched by Novo Nordisk in December 2024, Catalent Indiana LLC, the company announced in its Q2 earnings report.

FDA Cites Third-Party Site Issues in CRL and Regulatory Delay

Regeneron’s Biologics License Application (BLA) is seeking the approval of odronextamab for the treatment of relapsed/refractory (R/R) follicular lymphoma (FL) and for R/R diffuse large B-cell lymphoma (DLBCL) following two or more prior lines of systemic therapy.

Regeneron also stated that it anticipates regulatory approvals to be delayed for a pending application for Eylea HD (aflibercept) injection 8 mg. The application, which was 

, seeks to expand use of the treatment for patients with macular edema following retinal vein occlusion to permit monthly dosing across all currently approved indications.

 The application was assigned PDUFA target action date of August 19, 2025.

Odronextamab’s Path to Approval Complicated by Evolving Phase III Trial Timelines

These delays are associated with issues raised during an FDA general site inspection at the Catalent Indiana LLC filler site, which was recently acquired by Novo Nordisk A/S. The inspection was completed in mid-July and was not specific to Eylea HD or odronextamab, according to Regeneron.

“Novo has been in communication with the FDA and expects to submit its response next week,” Regeneron stated in a press release. “Based on the Company's review of the observations and Novo's proposed response to the FDA, along with the progress the Company has made with alternate third-party fillers, the Company anticipates an expeditious resolution of the filling issues for Eylea HD.”

The first CRL issued to the BLA for odronextamab in March 2024 was based on the enrollment status of the confirmatory trials, but the FDA did not cite approvability issues related to the drug’s efficacy, safety, trial design, labeling, or manufacturing, according to Regeneron.

The FDA previously granted Priority Review to the BLA for odronextamab based on findings from the Phase 1 ELM-1 trial (NCT02290951) and the pivotal Phase II ELM-2 trial (NCT03888105).

“Regeneron has been actively enrolling patients in multiple Phase III trials for odronextamab as part of the OLYMPIA program—one of the largest clinical programs in lymphoma,” the company stated in a March 2024 press release. “As the OLYMPIA program is intended to change the treatment paradigm of several B-cell non-Hodgkin lymphoma subtypes—including in earlier lines of therapy—in agreeing to the program, the FDA required that the trials include both dose-finding and confirmatory portions. Enrollment in the dose-finding portion has begun, but the CRLs indicate that the confirmatory portions of these trials should be underway and that the timelines to completion be agreed prior to resubmission.”

Regeneron Posts Strong Q2 Earnings with Growth from Dupixent and Eylea HD US Sales

Despite these regulatory delays, Regeneron noted positive momentum across its lines of business. The company’s Q2 revenue increased 4% to $3.68 billion compared to the same period last year. This was powered by an increase in global net sales for Dupixent (dupilumab), which increased 22% to $4.34 billion. US net sales for Eylea HD increased 29% to $393 million; however, total Eylea HD and Eylea US net sales dropped 25% to $1.15 billion.

"Regeneron had a strong quarter, marked by significant growth in US sales of Eylea HD and global sales of Dupixent and Libtayo along with multiple regulatory approvals," Leonard S. Schleifer, MD, PhD, board co-chair, president and CEO of Regeneron, said in the release. "We have made significant progress in our oncology portfolio, including FDA approval for Lynozyfic for relapsed or refractory multiple myeloma, exciting emerging data from the lead-in cohorts of our pivotal programs in myeloma and lymphoma, as well as positive pivotal data supporting a potential upcoming FDA approval for Libtayo in adjuvant CSCC. 

"Dupixent continues to be the world-leading treatment for diseases driven by type 2 inflammation, adding recent FDA approvals for bullous pemphigoid and chronic spontaneous urticaria, the seventh and eighth distinct indications for this important medicine. We are confident in the near- and long-term potential of our diverse pipeline and look forward to additional data and regulatory milestones later this year."

1. Regeneron Reports Second Quarter 2025 Financial and Operating Results. News release. Regeneron. August 1, 2025. Accessed August 1, 2025. 

https://www.globenewswire.com/news-release/2025/08/01/3125690/0/en/Regeneron-Reports-Second-Quarter-2025-Financial-and-Operating-Results.html

2. EYLEA HD® (aflibercept) Injection 8 mg sBLA Accepted for FDA Priority Review for Both the Treatment of Macular Edema Following Retinal Vein Occlusion (RVO) and for Monthly Dosing in Approved Indications. Regeneron. April 17, 2025. Accessed August 1, 2025. 

https://investor.regeneron.com/news-releases/news-release-details/eylea-hdr-aflibercept-injection-8-mg-sbla-accepted-fda-priority

3. Regeneron Provides Update On Biologics License Application For Odronextamab. Regeneron. News release. March 25, 2024. Accessed August 1, 2025. 

https://investor.regeneron.com/news-releases/news-release-details/regeneron-provides-update-biologics-license-application

4. Odronextamab BLA for treatment of relapsed/refractory follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) accepted for FDA priority review. News release. Regeneron Pharmaceuticals. September 29, 2023. Accessed August 1, 2025. 

https://investor.regeneron.com/news-releases/news-release-details/odronextamab-bla-treatment-relapsedrefractory-follicular

Regeneron faces regulatory delays for odronextamab due to issues at a third-party manufacturing site, Catalent Indiana LLC. The FDA's second complete response letter (CRL) cites these site issues, impacting the approval timeline for odronextamab, intended for relapsed/refractory follicular lymphoma and diffuse large B-cell lymphoma. Despite these setbacks, Regeneron reports strong Q2 earnings, driven by increased sales of Dupixent and Eylea HD. The company remains optimistic about its oncology portfolio and anticipates resolving the manufacturing issues swiftly to continue its progress in clinical trials.

Regeneron has received a second complete response letter from the FDA for odronextamab and anticipates delays for Eylea HD due to inspection findings at a Novo Nordisk-owned manufacturing site, despite continued strong revenue growth and pipeline momentum.

Regeneron Faces FDA Setbacks with CRL for Odronextamab, Delays on Eylea HD BLA Amid Third-Party Manufacturing Issues

In the rapidly evolving world of healthcare marketing, one of the biggest challenges that marketers face is reaching and engaging healthcare professionals (HCPs) effectively.

 To overcome this issue, pharma brands have traditionally promoted their products by drawing up partnerships with individual medical journals. However, this strategy hasn’t always yielded great benefits.
In fact, this approach has increasingly proven to be inadequate in delivering the scale, efficiency, and precision required to meet modern marketing goals. In the current context, to enhance HCP reach and engagement, brands must invest in more flexible, smarter and more scalable strategies. Instead of direct partnerships, it’s time they make the switch to solutions that maximize impact through scale, streamlined operations, and advanced targeting capabilities.

The Limitations of Single/Direct Partnership: Capped Reach and Scale

One of the most significant drawbacks for a brand when partnering with individual medical journal platforms is the limitation in reach and scalability they possess. While individual medical journal platforms are a good way to reach niche audiences, because of their nature they only cater to a select crowd of HCPs across limited geographies. This often proves to be a major bottleneck that pushes brands to forge multiple partnerships––each tailored to achieve a specific purpose and reach specific audience segments. In practice, this ultimately ends up creating a fragmented strategy that is extremely difficult to maintain in optimal shape in the long run, leading glaring gaps in HCP coverage and engagement.

The scalability of marketing activities is another major pain point for brands going ahead with such fragmented strategies. Due to the many partners involved in the picture and multiple moving parts because of it, it becomes difficult for brands to scale up their campaigns or for the matter make alterations mid campaign. This is because each new partnership requires fresh negotiations, integrations, and campaign adaptations, making it difficult for brands to streamline processes leading to lower returns on investment. Additionally, the fragmented nature of direct partnerships bottlenecks the potential audience size, making it nearly impossible to engage HCPs at scale.

Solutions that offer support for integrated medical journal publishers stand out as compelling alternatives. Depending on the size of the platform and the partnerships it brings under its umbrella, it can aggregate varied audiences from across a portfolio of medical journals providing access to a diverse and expansive HCP population through a single point of contact. By turning towards such integrated solutions, brands can tap into a pre-existing, broad audience base without the need to manage multiple partnerships. This consolidated approach ensures greater reach without very little fuss.

Resource-Intensive Management: The Hidden Costs of Fragmentation

Beyond the scope of their reach, another disadvantage that brands face when it comes to direct partnerships is the fact that they are extremely resource intensive. This is because under such a partnership, each platform requires dedicated time and effort for even hygiene tasks, let alone slightly complex ones such as contract negotiations, creative approvals, campaign execution, and performance tracking.

Moreover, partnering with individual medical journal platforms can also lead to tackling their unique requirements that spread over multiple partnerships can complicate campaign management. As such for a brand working with multiple medical journal platforms such partnerships could translates into a logistical nightmare.

Solutions that offer an integrated publisher management system do not run into such troubles as they offer a unified interface for campaign execution. So instead of negotiating with multiple publishers, brands can work with a single platform to roll-out campaigns. The major benefit of this in the streamlining of operations which then reduces the need for extensive coordination and allowing teams to focus on strategy and innovation instead.

Such platforms also bring reporting and analytics under one umbrella, thus helping brands to easily and effectively monitor performance across channels. Additionally, by consolidating data from multiple publishers under one platform, brands can easily track what’s working for them and what’s not -- something that also helps them course correct on the fly.

Inefficient Targeting and Personalization

Healthcare marketing is evolving, with traditional partnerships with individual medical journals proving inadequate for reaching and engaging healthcare professionals (HCPs) effectively. These partnerships often result in limited reach, scalability issues, and resource-intensive management. Integrated publisher platforms offer a solution by aggregating diverse audiences, streamlining operations, and enhancing targeting and personalization through advanced data analytics and AI. This shift allows brands to achieve greater scale, efficiency, and impact in their campaigns, moving away from fragmented strategies to more strategic, scalable approaches for HCP engagement.

One of the most significant drawbacks for a brand when partnering with individual medical journal platforms is the limitation in reach and scalability they possess.

Tom Fezza

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