The data decisions that make or break co-promote partnerships

Key takeaways

• Co-promote partnerships are an operating model challenge, not just a data integration challenge.
• Governance works best when teams split decisions cleanly: What needs joint sign-off, and what can each partner decide on its own?
• Data access should be based on role and business need, not company affiliation, and it’s rarely a simple yes-or-no decision.
• Before investing in new technology, evaluate whether existing systems can be extended to meet the partnership’s needs.
• Investing early in governance and data foundations pays off later, freeing partners to focus on execution instead of firefighting as launch approaches.

Co-promote and co-commercialization deals are becoming a more common way for biopharma companies to expand reach, but they bring a distinct set of challenges that a traditional single-company launch doesn’t. Two organizations, each with its own systems, governance and culture, suddenly need to operate like one team, at least from the outside looking in. That raises hard questions: What data actually needs to move between the partners? Who owns and governs it? And when do you build new infrastructure instead of stretch what you already have?

ZS recently worked on the co-promote partnership between Kite Pharma and Arcellx for anito-cel, a CAR-T cell therapy for multiple myeloma. Kite brought years of mature commercial infrastructure built within the broader Gilead ecosystem; Arcellx was preparing for its first commercial launch. That mismatch, common whenever an established company partners with an earlier-stage one, pushed both sides to work through exactly the kinds of questions above, and it’s a useful lens for the broader patterns that show up across most co-promote deals.

The case for a partnership-first operating model

The instinct in most co-promote deals is to negotiate everything through the lens of “our company versus theirs.” A more effective approach is to design the operating model as if it belonged to the partnership itself, not to either individual company. That means starting with the business outcomes both partners need, identifying which teams are needed to achieve them and then determining what those teams need to execute effectively (for example, what do commercial, medical and field teams need to succeed?) before building only the minimum structure required to support those outcomes, expanding later as the partnership matures.

In the Kite and Arcellx example that meant aligning on the critical data needs of the launch, things like time to first infusion, turnaround times and patient drop-off rates, before either side touched a system or a contract. Once each team defined what it needed and why, disagreements became easier to resolve, because the conversation shifted from “whose process wins?” to understanding the underlying constraint: was it legal, technical, procedural or simply a matter of resourcing? Establishing a common data model and shared business definitions early can significantly reduce the effort required to reconcile metrics and reporting later.

Splitting governance cleanly

The most durable governance models draw a hard line between decisions that require joint sign-off and decisions that stay within each organization. Shared data standards, data-sharing terms and launch response plans typically need joint governance because they directly affect the success of the partnership. Internal reporting, escalation paths and day-to-day business processes can stay independent. That separation reduces process overhead without sacrificing alignment.

Standardization helps too, but only where it makes sense. Common needs, like governance processes or reporting formats, benefit from a shared standard. Areas where the two organizations genuinely differ in business requirements need room for customization instead of a forced fit.

Data sharing is not a light switch

One of the more persistent misconceptions in co-promote planning is that data sharing is a binary decision: shared or not shared. In practice, the more workable models create tiers of access based on role and business need rather than which company someone works for. A field rep, a medical affairs colleague and a leadership stakeholder may all need different levels of visibility, regardless of which partner employs them. Framing the conversation around what decision needs to be enabled, and what information is genuinely required to enable it, keeps teams from over-restricting access on one end or over-exposing data on the other. This approach is easier to implement when the underlying technology supports role-based access aligned to business responsibilities rather than organizational boundaries.

Build versus buy, reframed

Rather than asking “Do we need a new platform?” the better starting question is “What capabilities does the partnership need, and can the existing technology landscape support them?” That means assessing each partner’s current systems, running a capability gap analysis against launch requirements (data integration, reporting, governance, security, scalability) and only then deciding whether to extend what exists or bring in something new.

Third-party platforms tend to create the greatest value in capabilities that both partners rely on but neither views as a competitive differentiator, such as data integration, shared analytics or standardized workflows. This is where platforms such as ZAIDYN® can provide the greatest value—as a neutral collaboration layer that enables shared governance, standardized data and common workflows without requiring either partner to replace its existing commercial ecosystem. Even so, the strongest models are usually hybrid: keep the internal systems that already work, bring in a platform where it accelerates the partnership and stay flexible as the deal evolves.

Why the early investment matters

Every partner underestimates, at first, how disruptive unresolved questions about ownership or data sharing will feel if they surface in the final weeks before launch. The organizations that build in a real buffer, such as a technical readiness milestone several months ahead of commercial launch, and run recurring cross-functional risk reviews, consistently spend less time firefighting and more time optimizing execution once launch arrives.

The right platforms can accelerate readiness by providing prebuilt governance workflows, standardized commercial data models and reusable integration capabilities, allowing teams to focus on validating the operating model rather than building foundational infrastructure.

The bigger lesson

The single biggest predictor of success isn’t the technology stack; it’s whether both organizations treat the co-promote as a genuine transformation of how they’ll work together, rather than a one-time launch readiness exercise. That means testing the operating model with real people before go-live, not just confirming that systems are technically connected. Workshops and process maps can only reveal so much; the “unknown unknowns,” like how field reps actually submit data change requests or how conflicting updates get resolved in practice, tend to surface only once real users are in the system. The partnerships that invest in validating their operating model—not just their technology—are the ones that spend launch focused on execution rather than alignment.

The real challenge in a co-promote isn’t integrating two technology stacks. It’s creating enough trust, governance and operational discipline for two independent organizations to function as one where it matters most, while remaining independent where it should. Technology can accelerate that journey, but only when it enables the operating model rather than defining it. The organizations that recognize this early spend launch focused on execution instead of alignment—and ultimately deliver a better experience for healthcare providers and patients.

To learn more about practical approaches to designing co-promote operating models, watch our webinar featuring leaders from Kite Pharma and Arcellx. You can also explore how ZAIDYN helps organizations accelerate data governance and collaboration across commercial partnerships.