Introduction

Speaker: 

Ihab Fakhouri, HLS GTM Lead, Salesforce 
 
Key Takeaways: 
• Patient data is the strategic lifeline of effective care delivery, linking it to measurable business and health outcomes is essential for closing the engagement gap. 
• Fragmented care pathways, reactive programme design, and misaligned incentives are the root causes of chronically low patient support programme adoption. 
• A flexible, 80/20 platform architecture, globally consistent yet locally configurable, reduces point-solution costs while enabling scalable, personalised patient engagement. 
• AI agents can be deployed strategically around care use cases and patient preferences, not as a default solution. 
• When data, empathy, and omnichannel design converge, measurable outcomes follow, from Rx adherence and time-to-therapy, even to IT cost reduction and desired business outcomes. 
  
The $5 Billion Paradox  
The pharmaceutical industry is spending more than $5 billion on patient support globally, yet only 8% of patients across therapy areas are actively using the programmes that this investment funds. With IDC projecting 300% growth in DTP spend by 2030, and patients consistently reporting that they want more help navigating their care journeys, the gap between intention and impact has never been more glaring. 
 
As Fakhouri put it: "How do we close the gap between the 75% and the 8%, and how do we actually meet patients at every touchpoint throughout the journey?" 
  
Four Reasons Programmes Fail  
Fakhouri identified four structural failures driving the disconnect: 
• Fragmented care, patients are left to manage complex handoffs between GPs, specialists, caregivers, and health systems, often feeling "confused, passed on, and full of uncertainty." 
• Tunnel vision, programmes are designed reactively, addressing crises rather than enabling prevention early on for better outcomes. 
• Misaligned value, only 18% of business outcomes are explicitly linked to patient value, undermining the strategic case for investment. 
• Passiveness, the burden of navigation remains on the patient, rather than on the systems designed to support them. 
  
The 80/20 Platform Model  
The intelligent care platform that Salesforce has developed with its customers is a globally consistent infrastructure with local configurability, what Fakhouri described as "not a one-size-fits-all, but a platform that fits the patient." The core 80% provides standardised foundations for engagement, data management, and journey orchestration. The remaining 20% allows regional teams to adapt, integrating local vendors, extending care teams, and configuring for market-specific needs. 

The business case is clear: this approach has not only delivered better patient outcomes but also delivered IT cost reductions of up to 26%, eliminating the overhead of managing fragmented point solutions across markets. 
  
Deploying AI With Intent  
On agentic AI, Fakhouri urged caution over enthusiasm. "Let's just put an AI agent there" is a reflex the industry must resist. Different patients need different things, some want human empathy, others prefer anonymity, others want speed. Agents should function as a configurable layer within the journey, switched on or off according to patient preference and clinical context, always underpinned by the right data. 
  
When done well, the results speak for themselves. University of Chicago Medicine used data-driven engagement to achieve a 185% increase in patient engagement within just four months, identifying around 100 distinct patient segments to drive meaningful improvements in preventive care uptake. A case published by Salesforce on their website or view on YouTube here. 
  
The Bottom Line 
Patient data is the foundation. Decisions should be patient-led. And if journey design genuinely reflects patient preferences and needs, Fakhouri argued, "agents can become caregivers." The technology exists, the harder work lies in re-architecting industry priorities to match. 
 
To get you highlights of Pharma 2026 faster, we are using generative AI technology to summarise the transcripts of the sessions. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com:.

Discover more on this topic at Pharma Commercial Data & Tech Europe 2026 (4-5 November, London) Europe’s collaborative home for data and tech pioneers. Visit the website here.

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HCP Fatigue Redefines the Value Proposition 
The consumerization trend Jeppe described, where patients arriving at physician appointments with LLM-generated treatment preferences, prepared to seek another opinion if rebuffed, is reconfiguring who pharma needs to engage and what that engagement must deliver.  

"If your company can bring some value to your customer beyond just an email campaign, then you are going to counterbalance the consumerization. But if your company, your tactics consist only to send 10 emails per month, then yes, you will be replaced," said Florent. The examples he cited are instructive: supporting an HCP navigating drug access for an asylum seeker, enabling a physician to organize community upskilling sessions for regional colleagues. Neither is a digital engagement play. Both are high-touch interventions that no AI-mediated channel can replicate, and both generate reciprocal loyalty that insulates a company from being disintermediated by Medscape, ChatGPT, or a competitor's next campaign. 

Sameer extended the stakeholder map to capture the structural shift underneath the consumerization trend. Patients increasingly arrive at pharmacies before they go to HCPs, self-medicating or seeking first-line OTC alternatives informed by LLM queries. Engagement strategy now requires pharmacy-level touchpoints at the awareness stage, HCP coaching on handling patient-initiated objections, and patient-facing content early enough in the journey to shape the conversation before it reaches the clinic. Most pharma commercial models have not fully operationalized any of these three. Sameer noted the social dimension bluntly: in markets with weak prescription controls, LLM-driven self-medication is not merely a commercial challenge but a public health one, and the industry's engagement needs to be matched by policy intervention. 

Florent surfaced a finding from Roche's real-time HCP feedback capture that reframes the competitive risk. "There is a digital fatigue from the HCPs. After COVID we have been doing a lot of webinars, a lot of remote meetings. They are bombarded with email campaigns and they just don't want to receive 50 emails per week. They just want sometimes to talk to a human." Engagement volume, measured as a proxy for engagement quality, is producing measurable deterioration in the customer relationship it is designed to strengthen. 

The Structural Fix Is Organizational 
The three prescriptions offered across the session, enterprise data governance, decision system architecture, product owner accountability, look like alternatives. They are not. Each addresses a different failure mode in the same organizational system. 

Phoebos was direct about the sequencing: "A lot of the time we think that we fix the technology problem and then automatically we will improve the way we do precision engagement. But actually, in my opinion, it's more about people, process and technology, and in that right order of importance." Technology scales effective organizational design. It does not substitute for it. 

Jeppe's closing provocation sharpened the boundary condition: are there barriers between R&D and commercial that need to be maintained? Florent's answer was instructive. At Roche, data domain lakes enforce access by organizational role, with workflow-governed permissions for cross-domain requests. The architecture does not eliminate boundaries; it makes them precise and navigable rather than blunt and impenetrable. Medical inquiry content stays within medical. Sales pricing data stays within its domain. But insights that can legitimately cross domains, clinical patient journey work, for instance, have a governed pathway to do so. Sameer's partial defense of silos acknowledged the CFO logic that created them: "The cost of a breach will overwhelm any additional cost of maintaining those silos." The problem is not that the logic was wrong. The problem is that it was applied without precision, producing blanket fragmentation where selective permeability would have served better.

Florent described a production-deployed pipeline at Roche that illustrates what the organizational architecture enables. HCP master data records are linked to public social media accounts via fuzzy matching. Real-time posting activity feeds into next best action content recommendations through natural language processing. If an HCP is publicly posting about a specific mechanism or molecule, the system surfaces relevant content for the next interaction. That capability exists because Roche built the data domain architecture, the product owner accountability model, and the cross-functional governance that makes it operational. The pipeline is the output of the organizational design. 

Companies still treating precision engagement as a technology procurement question are solving for the wrong constraint. The question worth asking before the next planning cycle is not which AI platform to invest in, but whether the organizational architecture exists to make any prediction actionable before the clinical moment it was designed to address has already passed. For most organizations, that answer is currently no, and no model update will change it. 

To get you highlights of Pharma 2026 faster, we are using generative AI technology to summarise the transcripts of the sessions. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com. 

Discover more on this topic at Pharma Commercial Data & Tech Europe 2026 (4-5 November, London) Europe’s collaborative home for data and tech pioneers. Visit the website here.