Improves access to hard-to-find content
Biopharma does not have a content problem; it has an access problem. Most brands have a substantial library of clinically reviewed, MLR-approved materials covering dosing, efficacy, access, and support. But brand teams could keep generating new content indefinitely and it would not solve the core issue: Namely, that patients and HCPs cannot find what already exists.
That’s because content is scattered across brand sites, PDFs, and patient portals, organized for storage rather than retrieval. HCPs do not have time to dig through a website while a patient is waiting. Meanwhile, patients often cannot parse complex clinical documents on their own, as only 12% of Americans have proficient health literacy skills. And traditional keyword-based search struggles to accurately answer nuanced, clinically specific queries. Some of the most valuable approved content produced by a brand goes largely unseen.
The right AI solution turns existing MLR-approved content into a dynamic, queryable knowledge base accessible from any channel. An HCP asks a clinical question and gets an accurate, approved answer in seconds. A patient describes their experience and is guided to the right resource.
This is also where the omnichannel promise becomes real, in the form of a single compliant knowledge base powering web, email, and SMS. That means the same accurate, approved content is available whenever and wherever someone engages, without the inconsistencies that come from managing separate assets across channels.
How to Evaluate
Can it work with real-world content like unstructured PDFs, image-heavy documents, and complex regulatory materials?
Does it adapt content to patients and HCPs based on intent?
Does it reduce the need to create new assets and surface the value of what already exists?
Escalates to human expertise when AI can’t answer
The best AI solutions are built with human involvement as a core part of the experience, rather than an afterthought, and are smart enough to know exactly when to defer to those expert people. Off-label inquiries, dosing questions that go beyond approved statements, complex coverage denials, and anything requiring clinical assessment all fall outside the scope of what AI should handle.
Just as important as the handoff is the context. AI should provide the human expert, whether it’s a nurse navigator, commercial rep, or MSL, with a clear summary of the question and where AI couldn’t resolve the inquiry.
Throughout the entire journey, the HCP and patient should always have a clear understanding of whether they’re interacting with AI or a human. Failing to disclose this is both a compliance and trust issue.
How to Evaluate
Does the system know when to escalate to a human, and can it route users to different pathways based on the nature of their inquiry?
Does the handoff provide the human expert with full context and intent?
Does the solution clearly tell patients and HCPs when they are interacting with AI?
Does it route adverse event queries to humans instead of attempting to answer?
Case Study
Human-in-the-Loop Done Right: An Oncology Brand Story
Delivering seamless human support beyond approved assets with Veeva Ostro
A brand team supporting 1,000+ patients needed higher-touch support for administration questions, side effects, and coverage complexity. The brand implemented Ostro Sites for HCPs plus Ostro Live Nurse Navigator, combining AI-based guidance with 1:1 nurse support embedded directly on the patient site. When a patient’s needs go beyond what approved content can address, they are routed to a trained nurse navigator who provides direct support. Veeva Ostro stood up the complete system in just two weeks.
Improvement in brand sentiment
Of patients received live 1:1 support
Faster to launch than building in-house
The patient support service is embedded directly onto the patient brand.com for live guidance whenever needed — reducing a 4+ month build to just 4 weeks.
Shifts engagement from channel-first to experience-first
When HCPs and patients have a question, they look for an answer wherever they happen to be, whether on brand.com or in an email or in a conversation with a rep. The problem is that most of those touch points still behave like static content libraries.
It’s no surprise that, according to a recent survey, 65% of HCPs reduced or stopped engaging with biopharma because digital communications felt over-promotional and unhelpful.
The right AI solution puts the HCP and patient first, operating as a conversational intelligence layer that provides a continuous, high-quality experience regardless of channel. This approach shifts engagement from static to conversational. Instead of pushing content out, the right AI solution enables real dialogue.
How to Evaluate
Does the platform maintain context across channels?
Can HCPs and patients ask follow-up questions and get precise, approved answers? Or does the experience “dead-end”?
Does it focus on answering specific HCP/patient questions, or does it prioritize pushing promotional content at them?
“Why don’t we just build AI in-house?”
Given the complexity of these requirements, some organizations have pursued internal AI builds. But building from scratch is a far more demanding undertaking than it appears, and comes with significant challenges:
Content Governance
Ensuring the AI only serves current, MLR-approved content and reflects updates immediately when claims change or assets are pulled falls entirely on internal teams.
Content Orchestration
Engineering an AI system sophisticated enough to match the right approved content to the right person based on intent and journey stage is a genuinely complex technical challenge.
Keeping Pace with AI Regulations
AI guidance is emerging from multiple directions, not just from the FDA. This is layered on top of an increasingly complicated patchwork of privacy and security requirements.
Specialized Talent
Building an in-house tool requires hiring advanced AI talent across engineering, product, and UX/UI who must navigate the nuances of biopharma commercialization.
Ongoing Cost
The upfront build is expensive, but ongoing maintenance, updates, and infrastructure costs are often what catch teams off guard. Total cost of ownership is much higher than expected.
Pace of AI Evolution
AI technology is moving fast. Whatever gets built today may need significant rearchitecting within 12 to 18 months just to stay current.
For most organizations, the better path is partnering with a solution purpose-built for the compliance and clinical complexity of life sciences.
The promise of AI: from static to intelligent engagement
The omnichannel promise that has anchored biopharma commercial strategy for years is no longer out of reach. The tools exist to get HCPs and patients the right approved content, at the right moment and across every channel, with humans in the loop when it matters.
The key is finding a solution that operates as a true intelligence layer, one that orchestrates the full experience to drive better outcomes for HCPs and patients.
That is what we built Veeva Ostro to be. From AI-powered web and email engagement to live nurse navigator support, Veeva Ostro helps advance HCP and patient engagement.
Learn more