Revisto joined Fierce Pharma for a panel discussion on one of the most pressing challenges in life sciences marketing: how pharma and agency teams can build a smarter, faster, and more connected content engine, from initial brief all the way to omnichannel distribution.
We were joined by Imogen Marouillat (Head of Solution Delivery, Merck Group), Jane Wallach (VP MLR Solutions, Havas Health Network), Tamisha Raqib (Director Marketing Operations, Supernus Pharmaceuticals), and Ferry Tamtoro (CEO and Co-Founder, Revisto) for an honest, wide-ranging conversation. Here are the key takeaways across each topic.
What does the end-to-end content lifecycle look like today?
The picture that emerged was consistent across pharma and agency: a process that is fundamentally linear, fragmented, and reliant on manual handoffs between teams. Several recurring themes came through:
The lifecycle is still largely sequential: brief to strategy to creation to review to distribution, with each stage owned by different stakeholders and limited visibility across them
Collaboration happens, but often informally and outside of formal workflows, which makes it hard to sustain
Bringing MLR reviewers into the process earlier was discussed as an ideal practice to improve the workflow and reduce downstream revisions
"One way we are trying to make the process smooth is bringing in our reviewers early on so they can give high level guardrails on the key messages. That way when it lands in their queue in PromoMats, it's not a surprise." — Imogen Marouillat, Head of Solution Delivery, Merck Group
"The process is very linear. A start, stop, handoff type of process. There's a lot of hard work happening today from a collaboration standpoint, but I'd like to see it become more fluid."
— Tamisha Raqib, Director Marketing Operations, Supernus Pharmaceuticals
What does the ideal future state look like?
The common thread appeared in the conversation: a connected, continuous system that can handle the volume and personalization demands of modern omnichannel marketing without the waterfall architecture that currently slows everything down.
A few main points stood out:
HCP and patient expectations have shifted. Personalized, omnichannel content is now the baseline, which means pharma needs to produce content at a scale the industry has never had to manage before
A single piece of content can require hundreds of channel-specific variations while the current MLR process was designed for a world where you produced one thing at a time
The ideal future state requires a fundamentally different architecture: continuous, connected, and AI-assisted from brief to distribution
"If you want to personalize a rep-triggered email, you're slowly multiplying versions by 10, 100, a thousand permutations of the same content. The MLR process today is not set up to manage that." — Imogen Marouillat, Head of Solution Delivery, Merck Group
"My blue sky is one system, or systems, that speak to one another — from the brief through content development, check-ins, approval, and reuse so that the entire process is less disjointed." — Tamisha Raqib, Director Marketing Operations, Supernus Pharmaceuticals
How mature are claims libraries in practice and what role will they play in AI-assisted content creation?
Claims libraries emerged as one of the most underestimated levers in the content lifecycle. The panel surfaced a clear tension: everyone knows claims libraries matter but maintaining them is genuinely hard.
Most organizations have a claims library in some form, but they often go stale as labels change, new data emerges, and approvals evolve
The manual effort required to keep libraries current is more than most teams can sustain, which erodes trust in the library over time
Finding the balance between structured claims and creative flexibility remains a real challenge
A well-maintained claims library is the foundation that future AI enabled processes will rely on. Without it, AI recommendations are only as good as the underlying data
"In order for us to work in AI, we have to be data ready. And to this day, we are still a little too reliant on our claims libraries being, for lack of better terms, on paper." — Tamisha Raqib, Director Marketing Operations, Supernus Pharmaceuticals
"In order for AI to assess MLR aspects properly, it cannot hallucinate. It needs to be grounded in truth. A consistently maintained claims library is the foundational first step to getting to that blue sky." — Ferry Tamtoro, CEO and Co-Founder, Revisto
Where does MLR sit within current marketing workflows, and where does it break down?
MLR is still functioning as a gate and bottleneck at the end of the content lifecycle rather than a collaborator throughout it. The panel identified several specific points where the current model creates friction:
By the time content reaches formal review, it is often too late to course-correct without significant rework. Often, fully baked concepts arrive at MLR when earlier alignment could have prevented downstream issues
The demand for content is growing. Reviewer headcount is not. Teams are being asked to review more, across more channels, with the same resources
Pre-checks, whether through early MLR engagement or AI-assisted screening before formal submission, were consistently cited as one of the highest-leverage opportunities to reduce downstream friction
"We get our briefs, we move at the speed of light, and we lose the opportunity to engage with our MLR teams earlier. This means we're going into review with fully baked concepts at times that should have gone to an earlier MLR discussion." — Jane Wallach, VP MLR Solutions, Havas Health Network
"In the future, we should not be treating MLR as a gate at the end. Bring it up front. Identify regulatory requirements, brand guidelines, claim substantiation, fair balance as much as possible upfront. That way the content lifecycle becomes much cleaner and smoother throughout and reduces revisions and iterations" — Ferry Tamtoro, CEO and Co-Founder, Revisto
How do you build trust in AI-assisted MLR review?
This question generated some of the richest discussion of the session. The consensus was clear: trust doesn't come from the technology alone.
Transparency matters. Reviewers won't trust what they can't interrogate. This means that AI needs to show its reasoning, link recommendations back to source claims or regulatory requirements, and give reviewers enough context to evaluate and override a suggestion
Integration within existing workflows is critical. When AI operates outside the systems reviewers already use, it creates extra work rather than reducing work.
Safe environments to learn are essential. Structured opportunities to test, make mistakes, and build judgment before go-live will produce better adoption outcomes
"Give reviewers the evidence. Have a system that justifies its output. Make sure the reviewer is always in charge. An AI the system is there to augment their job, not the other way around." — Jane Wallach, VP MLR Solutions, Havas Health Network
"People need a safe environment to try new things, to make mistakes and get things wrong. This allows people to feel like they’ve already used the AI and understand it before they go to use it live." — Imogen Marouillat, Head of Solution Delivery, Merck Group
What are the most common barriers to AI adoption, and how do you get past them?
The barriers to AI adoption in pharma are less about resistance to technology than they are about change management. The panel identified three themes that surface consistently:
Concern that AI will replace roles rather than augment them. Instead, AI should be seen as a tool that scales reviewer capacity rather than replaces it
The challenge of building the business case. Defining KPIs upfront, tracking the right metrics from the start, and celebrating early wins are what turn a pilot into an organizational capability
Change management complexity. Co-creating solutions with the teams who will use them, rather than rolling out tools top-down, is what drives sustained adoption
"It's not about replacing roles. It's about helping to scale them” — Tamisha Raqib, Director Marketing Operations, Supernus Pharmaceuticals
"Just in the past year, by creating that safe space and the training, I've seen a total shift — from 'it's taking my job' to 'look what I can get done in a day.' That shift is real." — Jane Wallach, VP MLR Solutions, Havas Health Network
"The users themselves — mainly the reviewers and coordinators — need to see the value for themselves. We need to find a way to track and show value, so they get that dopamine hit of: I can see how this is working and making my life better right now." — Imogen Marouillat, Head of Solution Delivery, Merck Group
Closing thoughts
AI has genuine potential to accelerate content creation, structure claims management, and reduce the MLR burden without compromising rigor. But the path forward is not a single transformation. It is a series of well-placed bets at the moments that matter most within the content and marketing lifecycle.
The conversation is just getting started. Watch the full webinar recording here or request a demo at revisto.com to see how Revisto is helping pharma and agency teams close the gap today.