Interview with: Nida Khan, Founder &

President, Arya Consulting Partners

"The most successful teams treat launches as an adaptive process rather than a fixed plan. With increasing complexity and multiple stakeholder journeys to consider, success today requires earlier, cross-functional coordination. Organizations must start by mapping the full patient and stakeholder journey for a therapeutic area and design the launch strategy around that reality," says Nida Khan, Founder & President, Arya Consulting Partners.

Arya Consulting Partners is a service provider at the Marcus Evans PharmaMarketing Summit 2026.

What major shifts are you seeing in how companies

plan and execute launches?

Launches have become a continuous strategic process that starts much earlier in the development cycle. Success now depends on cross-functional coordination early enough to shape evidence generation, patient identification strategies, and stakeholder engagement, before critical decisions are locked in and become difficult to unwind. Therapeutic areas are increasingly complex, particularly in rare disease and specialty markets, where diagnosis pathways, referral networks, and treatment infrastructure often determine whether patients ever reach therapy, not just how quickly adoption occurs. The launch strategy needs to account not only for product positioning, but also for how patients are identified and cared for.

Analytics and AI are also changing the launch playbook by accelerating the speed at which insights are generated. Launch teams have access to more data than ever before and must learn how to interpret weak and early signals. This represents a fundamental shift away from static launch plans toward continuous decision-making as market dynamics evolve.

Therapeutic areas differ dramatically in their

pathways to launch success. How should

companies adapt their strategies when data is

limited while stakeholder needs are unique?

It is important to recognize that the pathway to adoption varies significantly by therapeutic area, so launch strategies must be tailored. With rare diseases, patient identification is often the biggest challenge, requiring a focus on diagnostic pathways, referral networks, and the readiness of specialized treatment centers to help with patient care. Patient advocacy organizations often also play a critical role in connecting patients to information and appropriate care.

Evidence generation must also be rethought in these environments. When programs involve small clinical data sets, companies need proactive strategies to supplement clinical evidence with natural history studies, real-world evidence and ongoing post-launch data generation. Without this foresight, uncertainty at launch can slow access decisions and delay adoption in already narrow patient populations.

What separates high-performing launch teams in

how they integrate medical, access, commercial,

digital and data functions in the launch process?

One of the clearest differentiations is the ability to move from a functional to an integrated launch model. Success increasingly depends on how different capabilities are coordinated from the very beginning. They must create shared governance structures and common strategic objectives early in development. What patient journey are we aligned around? What stakeholder engagement model will support it, and what is the unified value proposition, not just for payers, but for the brand as a whole?

In addition, digital and data capabilities are playing an even bigger role in how functions coordinate. They help teams align around shared information and make decisions from a consistent view of the market rather than fragmented interpretations.

Ultimately, the most effective launch teams treat launch as something that must be actively orchestrated across the organization, rather than managed through various parallel work streams.

How is AI reshaping the way launch teams generate

insights, forecast adoption and make early strategic

decisions?

AI is helping teams generate insights faster, and test strategic scenarios more effectively. AI-enabled tools can synthesize large volumes of data from multiple sources, allowing teams to identify patterns and signals more quickly. AI-driven forecasting is helping organizations to quantify how referral patterns and patient identification dynamics directly shape adoption. The most valuable use of AI is scenario planning, allowing teams to evaluate how pricing, access, and competitive dynamics influence uptake. Ultimately, AI enhances decision-making but human expertise is essential for interpreting insights and shaping strategies.

Looking ahead a few years, what will define launch

excellence? What capabilities should organizations

be building now to stay competitive?

Launch excellence will increasingly be defined by an organization's ability to operate in a dynamic, data-driven environment. They need to build stronger, cross-functional operating models, which is not an easy job in big teams, and combine it with advanced analytics capabilities to detect signals early. It needs to function as a launch command center that integrates multiple data sources, generates actionable insights, and tests strategic scenarios. We expect AI to play a bigger role in forecasting and scenario planning.

Many companies are investing in AI tools but not enough on how their teams should interpret or act on that information. Putting the infrastructure in place now will set them up for long-term success.

Any final words of advice?

The traditional approach has been to initiate launch planning 18-24 months before approval, but that timeline is no longer sufficient. We believe that it's better to start earlier, at early phase I, aligning the development team with market access, medical affairs and the commercial teams. Focusing on whether the asset works and is commercially viable: will there be coverage and adoption? The science may be compelling, but if the market won't adopt it, you won't have an asset that generates demand.

Coordinating functions as early as possible is key. It's not just about positioning. You need to identify where your patients are, how you access them, what treatment centers have the capabilities, or help centers build those capabilities before your asset comes to launch.

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