Insight: When the Decision Rests on What We Provide

Earlier this month, U.S. Health Secretary Robert F. Kennedy Jr. announced the termination or restructuring of close to half a billion dollars in federal funding for 22 mRNA vaccine research projects. His reasoning centred on concerns over the effectiveness of mRNA vaccines for upper respiratory infections such as COVID-19 and influenza.

In the days that followed, many voices from the scientific community expressed alarm - not just at the potential impact of the decision, but at the reasoning behind it. Their concern? That the Secretary had been influenced by misinformation or disinformation about the technology’s performance and potential.

I’m not here to debate the politics of that decision, nor to argue whether it was right or wrong. My interest lies in the mechanism behind it. Because at the heart of this situation is a decision-maker, far removed from the research bench, relying entirely on the information made available to him.

And that got me thinking: in our own work in pharmaceutical R&D, we are the people providing that information. And our decision-makers - whether they are project sponsors, principal investigators, regulators, or company executives - are just as dependent on the integrity, completeness, and clarity of what we give them.

Could Misinformation Be Closer to Home Than We Think?

When we hear the term “misinformation”, it’s easy to imagine it happening out there - in the public arena, in press statements, in social media posts with dubious sources. It feels like something external to our own well-controlled, scientifically-driven environments.

But what if misinformation, in a much subtler form, exists right here in our workspaces?
Not because of malice, but through omission, assumption, or lack of perspective.

The Landscape We Work In

Pharma R&D is a complex ecosystem. Data comes from many places:

• Non-regulated discovery work

• Regulated GLP preclinical studies

• GCP-compliant clinical research

The people involved are just as diverse: scientists, medical doctors, statisticians, project managers, sponsors, vendors, QA professionals, healthcare providers, and more.

Each of us has a role in ensuring that the information we produce is accurate, reliable, transparent, and complete. Yet we operate under a set of pressures that can cloud our ability to make fully objective decisions:

• Budgets - managing finite resources, sometimes to the point where data collection or reporting shortcuts are tempting

• Career progression - wanting to be seen as productive, efficient, or successful can subtly shape what we emphasise or omit

• Timelines - regulatory submissions, study milestones, or investor expectations

• Personal responsibilities - family commitments, travel, health; the human factors that make us choose expediency over completeness

• Familiarity bias - being so close to a system, dataset, or process that you stop seeing its gaps, assuming “it’s obvious”

Individually, these pressures might seem minor. Collectively, they can create a slow drift away from full clarity.

When Small Slips Add Up

Let me give you a few examples - situations I’ve seen repeatedly across preclinical and clinical settings.

1. The missing context
   A preclinical researcher omits a small procedural deviation in a report because “it had no impact on results”. But a principal investigator reading the dossier later misses the subtle signal this deviation might have revealed about a safety risk.

2. The lost nuance
   A subcontracted lab understands that a particular assay’s reproducibility is variable at the low end of its range. But that nuance is not captured in the sponsor’s summary report, and when those results feed into a go/no-go decision, the risk is misunderstood.

3. The overlooked inconsistency
   A clinical site notes a data discrepancy but assumes it’s too minor to bother clarifying before submission. Months later, a regulator raises it as a compliance concern, delaying trial approval.

None of these are examples of deliberate deception. But each represents information that didn’t make it to the decision-maker in a usable form. And the outcome of those decisions can be just as profound as if the information had been intentionally distorted.

The Parallel with the mRNA Decision

RFK Jr’s decision was based on the information available to him - and, if the scientific community’s concerns are valid, that information may have been incomplete, misleading, or misinterpreted.

In our sector, the stakes are no less real. Decision-makers in pharma R&D - whether they are choosing to progress a candidate drug, halt a trial, allocate funding, or approve a marketing application - are making those calls based on what we give them.

And here’s the uncomfortable truth: if we omit, downplay, or fail to contextualise key information, we’re shaping those decisions in ways we might not intend.

The Hidden Cost of Incomplete Information

When we think about poor data or reporting in R&D, the risk that springs to mind is usually wasted resources - the cost of developing compounds that later fail. That’s certainly a concern.

But I’d argue the greater risk is this: terminating a promising compound too early because the data available painted an incomplete or misleading picture.

That can mean:

• A potentially transformative medicine never reaches the patients who need it

• An organisation misses out on a breakthrough therapy - and the reputation, revenue, and societal impact it could bring

• An entire therapeutic area is deprioritised based on flawed or partial evidence

In other words, the damage isn’t just to the current project. It can ripple across years of strategy and investment.

The QA Perspective: Being the Objective Voice

As QA professionals, we’re in a privileged - and sometimes awkward - position. Our role is to ensure that the story the data tells is complete, verifiable, and interpretable by all the audiences who will rely on it.

That means stepping back from our own familiarity with the systems and processes and asking:

• Would this report make sense to someone who has never set foot in our facility?

• Could they understand it without knowing our SOPs or unwritten practices?

• Does the presentation of this data allow a regulator, sponsor, or clinician to make an informed decision?

Importantly, that doesn’t mean ensuring they make the “right” decision. Even with full and accurate data, people can still reach different conclusions. Our role is to make sure their decision is informed - not limited by what we failed to communicate.

Practical Ways to Keep Perspective

Here are a few techniques I’ve seen work well:

1. Read Like a Stranger
   Review key reports as if you were seeing them for the first time. If something feels like “common knowledge”, ask whether it’s documented for someone outside your circle.

2. Peer Reviews Across Teams
   Invite colleagues from unrelated projects to review documents for clarity and completeness. Their fresh perspective will surface blind spots.

3. Narrative Context
   Don’t just present the numbers - explain their boundaries, limitations, and origins. The “why” and “how” can matter as much as the “what”.

4. Challenge Assumptions
   If you find yourself thinking “they’ll know what this means”, treat that as a red flag to explain it.

5. Audit for Decision-Readiness
   Before finalising a report, ask: could this document stand on its own if it was the only source available to a decision-maker?

Why This Matters More Than Ever

In an age where public debates over science can be swayed by incomplete or misleading narratives, our internal decision-making processes need to be even more robust. The mRNA funding story is a public example of what happens when contested information drives a major policy call.

In pharma R&D, the audience is different, but the mechanism is the same: decisions are only as sound as the information they’re based on.

Every one of us - from the lab bench to the sponsor’s office - is a link in that chain.

A Final Thought

I’m sharing this not as a warning from the sidelines, but as a colleague who’s seen how easily good intentions can be undermined by unexamined assumptions.

We are the custodians of information. We decide what context, caveats, and detail are passed upward. We can’t control every factor influencing a decision-maker - but we can control the quality, clarity, and completeness of what we give them.

So here’s my question to you: is there a gap, however small, in what you’re providing? Could that omission - multiplied across the chain - be our own quiet form of misinformation?

Because the next “RFK moment” in our world won’t play out in the headlines. It will play out in a boardroom, a regulator’s office, or a project review meeting. And the decision made there will be shaped by what we chose to say… or not say.