The Pharma Content Benchmark Report 2026

Foreword

Every pharma team we speak to tells us the same thing. The science is ready. The data is strong. But by the time the content is built — the slide deck, the congress summary, the HCP video, the payer dossier — weeks have passed, the window has narrowed, and the team is exhausted.

This report puts numbers to that experience for the first time.

We surveyed more than 200 pharma professionals across medical affairs, commercial, market access, and medical communications to understand exactly how long scientific content production takes, where the bottlenecks are, and what the true cost of slow content looks like when you add it all up.

The findings are striking — not because they are surprising, but because they are, for the first time, documented.

We hope this report gives you the language and the data to make the case for change inside your organisation. Because the gap between the speed of science and the speed of content has never been wider — and the cost of that gap has never been higher.

The VarsaAI Team

Executive Summary

• Only 8% say their current content process gives them a competitive advantage
• Only 14% have meaningfully adopted AI for content creation today

Methodology

This report is based on an online survey conducted in Q4 2025 with 214 pharma professionals across the United Kingdom, United States, Germany, and France. Respondents were recruited via LinkedIn and pharma industry networks, and screened to ensure they held direct responsibility for, or significant involvement in, scientific content production.

All figures are self-reported. Where ranges were provided, midpoint values were used in aggregate calculations. Company revenue and agency spend figures were validated against publicly available financial disclosures where possible.

Section 1: The True Timeline of Pharma Content Production

How Long Does It Actually Take?

We asked respondents to estimate the end-to-end production time for six common content types — from data or brief in hand to final, approved asset ready for use. The results reveal a consistent pattern: scientific content takes far longer than most organisations budget for, and far longer than the pace of the science demands.

The variance between the fastest and slowest teams is particularly striking. The fastest 10% of respondents share several characteristics: smaller teams, clearer internal approval processes, and in most cases, some degree of templating or AI-assisted content creation already in place.

The slowest 10% share a different set of characteristics: multiple agency touchpoints, fragmented approval chains, and content briefs that are rewritten multiple times before production even begins.

Where Does the Time Actually Go?

When respondents were asked to break down where production time is spent, the results challenge some common assumptions about where the real bottleneck lies.

The finding that stops most pharma leaders in their tracks: regulatory and MLR review — the stage most commonly cited as the bottleneck — accounts for only 12% of total production time on average. The real time sink is in the three stages that precede it: alignment, creation, and revision.

"We always blamed MLR for everything being slow. When we actually tracked it, we realised MLR was taking four days. We were taking three weeks to get something to them that was good enough to submit."

Section 2: The Cost of Slow Content

The Agency Spend Problem

The majority of pharma companies continue to rely heavily on external medical communications agencies for content production. Our survey found that respondents' organisations spend an average of £340,000 per year on agency fees for what respondents themselves categorise as "standard" or "template-driven" content.

When asked whether they believed this spend represented good value, only 31% of respondents said yes. The most common criticisms were:

• Slow turnaround times despite high cost (67%)
• Over-reliance on generic templates requiring significant reworking (54%)
• Insufficient scientific understanding requiring extensive correction rounds (49%)
• Inability to respond quickly to data updates or competitive developments (44%)

The Opportunity Cost Nobody Calculates

Agency fees are the visible cost. The invisible cost is the value of the engagement opportunities that slow content production causes teams to miss entirely.

"We had Phase III results that were genuinely differentiated. By the time we had the HCP materials ready, the competition had already been in front of our key accounts for three weeks telling a different story. We never fully recovered that ground in that quarter."

The Hidden Internal Cost

Beyond agency fees and missed opportunities, there is a third cost category that receives almost no attention: the internal staff time consumed by content production.

The average respondent spends 14.3 hours per month on content production tasks — writing, reviewing, reformatting, chasing agencies, and correcting errors.

For a professional whose fully loaded cost is £80,000–£120,000 per year, that represents approximately £10,500–£15,750 of salary cost directed at content production each year — per person. Across a team of ten, that is over £100,000 per year before a single agency invoice is raised.

Section 3: The Quality Problem

The Translation Gap

Speed and cost are the most measurable dimensions. But our survey also surfaced a consistent and troubling finding about quality — specifically, the gap between the scientific rigour of the data and the quality of the content that reaches the audience.

"Our clinical team produces brilliant science. Then it goes into the content machine and comes out looking like every other pharma slide deck. The data deserves better than that."

The Update Burden

A frequently overlooked quality issue is the cost of keeping content current. The average time to update and re-approve a standard slide deck: 11 working days. For a video asset: 18 working days.

43% of respondents admitted to presenting audiences with content they knew was not fully current, because the update process takes too long.

Section 4: The AI Opportunity

Where Pharma Stands Today

Awareness of AI-powered content creation tools is near-universal — 97% of respondents are aware such tools exist. Actual adoption tells a very different story.

The gap between awareness and adoption is driven by consistent concerns:

1. Scientific accuracy — concern about errors or misrepresentation (78%)
2. Regulatory compliance — uncertainty about MLR standards (71%)
3. Data security — concern about proprietary data (64%)
4. Quality of output — scepticism about scientific and visual quality (58%)
5. Organisational resistance — internal stakeholders not yet comfortable (43%)

What Early Adopters Are Experiencing

"We used to spend six weeks building our congress package. We now do it in four days. That's not an exaggeration. The science hasn't changed — but the way we turn it into content has completely transformed."

The Three-Year Horizon

91% of all respondents — adopters and non-adopters alike — believe AI-powered content creation will be standard practice in pharma within three years. The implication is clear: this is not a question of whether pharma adopts AI. It is a question of which teams move first.

Section 5: What Best-in-Class Looks Like

Section 6: The Benchmark Scorecard

Use the following scorecard to assess where your team sits relative to the benchmarks established in this report.

Conclusions & Recommendations

The pharma content production challenge is not a niche operational issue. It is a strategic problem that affects commercial performance, HCP and payer engagement, and the ability of scientific teams to compete at the pace the market demands.

Our Three Recommendations

1. Audit your actual production timeline across the five stages identified in this report. Track it for one month. You are likely to find the upstream stages consume more time than you realise.
2. Calculate your true content cost — not just agency fees, but internal staff time and the value of the opportunities you have missed or delayed in the past 12 months.
3. Evaluate purpose-built AI tools for pharma content production. General AI tools will not address your accuracy, compliance, or quality concerns. The right platform — one built specifically for scientific content — will.

© 2026 VarsaAI. All rights reserved. This report may not be reproduced in whole or in part for commercial purposes without written permission.