Market access consultants face a paradox: there’s more data than ever—but turning it into strategic insight is harder than ever.
Over 30 years' experience revolutionizing strategy within healthcare, pharma and life sciences.
Market access consultants face a paradox: there’s more data than ever, but turning it into strategic insight is harder than ever. Scientific publications, clinical trials, HTA decisions, and stakeholder reports are growing at exponential rates. Yet the tools designed to manage them remain unstructured, inefficient, and blind to the strategic nuance required in market access.
AI offers potential, but generic large language models, trained on internet-scale data, lack the specificity, structure, and context to deliver reliable insights in this domain. They hallucinate. They generalise. They miss what matters.
Knowledgeable changes that.
At its core is a domain-specific ontology. Built by consultants, data scientists, and semantic engineers with over a decade of experience in market access. It reflects how consultants actually think: mapping evidence to decision types, structuring content by strategic value, and aligning AI outputs with real-world workflows like TPPs, GVDs, and stakeholder maps.
The result?
This paper explores the technical foundation, real-world use cases, and strategic implications of Knowledgeable’s ontology-powered platform, offering a glimpse into how evidence-based consulting will evolve, and how the smartest teams are already gaining an unfair advantage.
Because in the future of market access, strategy won’t be slowed down by data.
It will be powered by it.
The challenge facing market access professionals today is an overwhelming surplus of data.
Scientific output is growing at an unprecedented rate. In 2023 alone, over 3.5 million peer-reviewed articles were published globally, adding to an already vast, and fast-expanding, ocean of information. New clinical trials are registered daily. Pricing data, HTA decisions, treatment guidelines, stakeholder commentary, and patient advocacy insights flood in from every corner of the healthcare ecosystem.
And for consultants tasked with turning that information into clear, strategic recommendations, this volume is as much a curse as it is a resource.
The problem isn’t access, it’s usability. Most research tools treat every article, dataset, and document equally. They rely on keyword search and manual review, expecting the user to sift through hundreds of PDFs, Excel sheets, and slide decks just to find what matters.
This means that even the best consultants are forced to act like analysts: reading, filtering, and formatting data before they can think strategically.
“At one point, I had 16 tabs open - each with a different paper. I was copying and pasting into PowerPoint just to make sense of what the story could be. That was my entire Friday night.”
Consultant, global market access agency
This approach is expensive as well as frustrating. For every hour spent manually triaging literature or recreating insights, projects lose margin. Proposals take longer to write. Research cycles slow down delivery. And worst of all, decisions are made with partial visibility, because the signal gets buried in the noise.
There’s also a deeper risk: without structure, teams can’t reuse knowledge. A key insight uncovered last quarter lives in a slide, not a system. An HTA trend spotted in one indication never makes it into the next project. Institutional memory disappears with the consultant who carried it.
The reality is that most traditional tools and knowledge repositories were designed for storage, not strategy. They help you file, but they don’t help you think. And in a space as fast-moving and interconnected as market access, that’s no longer good enough.
What consultants need isn’t more access to information. What they need is a system that organises information intelligently, prioritises what matters, and presents it in ways that accelerate decisions.
Data without structure is like having a library where all the books are blank on the cover. It’s all there, but finding what you need, when you need it, requires far too much luck.
The explosion of unstructured knowledge has created a bottleneck in the very workflows that are supposed to drive strategic value. It’s not a matter of working harder—it’s a matter of rethinking the system. Because until data becomes structured, reusable, and context-aware, even the best minds in market access will spend more time managing information than creating impact.
Over the past few years, large language models (LLMs) have become a cornerstone of digital innovation. They can summarise clinical trials, generate content, answer questions, and even write code. But despite their impressive capabilities, LLMs are not built for strategic work in specialised domains like market access, at least, not on their own.
LLMs such as GPT-4, Claude and Gemini are trained on vast quantities of data from across the internet: books, blogs, code repositories, research papers, Reddit threads, and more. This gives them incredible breadth of knowledge, but little depth in any one field. For highly regulated, evidence-driven domains like market access, that presents a real problem.
Market access consulting depends on accuracy, structure, and traceability. Strategies are built not just on information, but on the right information: interpreted correctly, contextualised appropriately, and backed by a clear data trail. When AI models are applied generically, they often produce outputs that sound plausible but are logically inconsistent, out of context, or just plain wrong.
Without a domain-specific framework, AI becomes verbose, unfocused, and potentially misleading.
In technical terms, this is known as semantic drift and hallucination. Where the model generates information that appears relevant but lacks grounding in verifiable data or domain logic. In market access, where a single misinterpreted outcome or incorrectly summarised value message can derail a strategic recommendation, that’s unacceptable.
To move from “plausible” to “trustworthy,” AI needs more than just data, it needs structure. It needs to know:
That’s where ontology comes in.
Think of an LLM like a brilliant new intern. They’re eager, fast, and know a bit about everything. But if you don’t give them a structured filing system and clear instructions, they’ll waste time, misfile critical information, and slow the team down. Give them the right framework, and they become invaluable.
This analogy maps well to the reality of AI in market access. Without an ontology, a structured system that reflects the logic and language of market access consulting, even the best AI will struggle to deliver meaningful outputs. With one, it becomes capable of interpreting information the way a consultant would, accelerating everything from evidence synthesis to proposal development.
We’ve seen this firsthand. In early prototype testing, we asked a standard LLM to summarise trial outcomes for a cardiovascular product. The model listed endpoints without distinguishing between exploratory and primary outcomes, failed to highlight subgroup relevance, and attributed conclusions to the wrong investigators. It sounded impressive, but would have caused strategic missteps if used unchecked.
Now, using our ontology-first approach, the same task surfaces correctly weighted outcomes, clarifies trial phase and design elements, and ties each result to specific stakeholder-relevant themes. It understands what a consultant needs to see, not just what’s in the text.
AI alone isn’t enough for market access. But AI grounded in a domain-specific ontology, designed by people who understand the work, can be transformative. It allows consultants to move faster, go deeper, and make confident decisions with clarity and context.
There are tens of millions of scientific publications out there and the biggest challenge is not access, it's understanding. Market access professionals don’t need more information; they need the right information, structured in a way that supports decision-making. That’s where ontology comes in.
At its core, an ontology is a structured framework that defines how concepts relate to one another in a particular domain. It’s like a blueprint for how knowledge is organised, connected, and retrieved.
Where a taxonomy might tell you that “clinical trial” is a type of “study,” an ontology tells you that a clinical trial has outcomes, those outcomes are measured by endpoints, those endpoints relate to indications, and those indications are linked to therapeutic areas, pricing decisions, and regulatory pathways. This goes beyond grouping information all the way to making relationships visible, navigable, and actionable.
In short: a taxonomy categorises; an ontology contextualises.
And in complex fields like market access, context is everything.
Unlike traditional search engines or generic AI tools, a domain-specific ontology understands how market access consultants think. Above just finding mentions of a drug, it knows what kind of drug it is, what trial phase it belongs to, what population it targets, and what impact it might have on an HTA or payer decision.
This matters because market access is an interdependent field, where clinical evidence, pricing strategy, stakeholder mapping, and regulatory nuance all intersect. Without an ontology, that web of meaning is lost. With one, it becomes a map.
Consider two users searching for insights around “first-line treatment options for ulcerative colitis in EU5 markets.” A generic AI might surface dozens of loosely related articles: trial results, opinion pieces, pricing databases—all mixed together, without priority or strategic weighting.
A system powered by a domain-specific ontology would:
This is the difference between searching and knowing where to look.
An ontology makes AI a true strategic asset. Here’s how:
Without an ontology, AI operates in a vacuum. With it, AI becomes a domain-native assistant. Faster, more relevant, and dramatically more useful.
One of our earliest testers described the experience of using a traditional research platform as “like having all the right answers - but buried in a filing cabinet someone tipped over.” By applying an ontology-based approach, the same user could find, understand, and act on the data they needed in a fraction of the time.
Another remarked that “it’s the first time I’ve felt like the system actually understands what I’m trying to do.”
That’s the power of ontology. It organises information in a way that mirrors human reasoning, so insights feel intuitive, grounded, and ready for use.
A domain-specific ontology is the engine that powers relevance, speed, and trust in complex environments like market access. By building our ontology around how consultants actually think and work, Knowledgeable transforms AI from a black box into a strategic partner.
It’s easy to build a system about market access. It’s far harder to build a system that actually works for market access. This requires understanding the messy, nuanced, cross-functional reality of what consultants do every day.
At Knowledgeable, we’ve been on the inside. Our team brings over a decade of hands-on experience across market access strategy, data science, semantic engineering, and real-world consulting delivery. We’ve lived the problems we’re solving.
That perspective matters. It’s what allowed us to design an ontology that models the way real consultants think.
Most data systems are designed from the top down, imposing abstract categories onto real-world use cases. We did the opposite. We started with the workflows.
Every aspect of our framework was reverse-engineered from actual market access projects: the documents that consultants deliver, the questions clients ask, and the pathways teams follow from evidence to strategy. The result is an ontology that matches the way consultants structure their work in practice.
Our system doesn’t just “know” about an indication, it understands that an indication:
And this logic runs throughout the platform. Whether structuring a Global Value Dossier, mapping value messages to endpoints, or triaging publications for a Target Product Profile, the relationships between concepts mirror the mental models of high-performing teams.
A key differentiator is how we’ve embedded strategic decision-making pathways into the structure itself. It’s not just what a piece of data is—it’s what it’s for.
For example:
This intent-awareness is what lets our system not only surface information but prioritise and contextualise it, making it genuinely useful from day one.
Early in development, we built a prototype to test how well our ontology could accelerate proposal creation. Traditionally, writing a strong proposal required manually reviewing recent publications, structuring key findings, and crafting arguments aligned with client goals - often across a weekend, often under pressure.
Once we structured those publications by decision relevance (e.g., unmet need evidence, endpoint support, KOL activity), a consultant was able to draft a full proposal (with citations, rationale, and data points) in under three hours.
They described the experience as “like having a strategist who already knows what you need, handing you the skeleton of the project.”
That speed, and quality, comes not from automation alone, but from a system that thinks like the user.
Because we built our ontology from real projects, it’s immediately applicable. But because it’s structured semantically and modularly, it’s also built to scale and adapt. As new therapy types, reimbursement models, and regional frameworks evolve, so too does our structure, without breaking workflows.
We like to think our system is street-smart. It understands the difference between academic precision and commercial practicality. It’s been shaped by timelines, by client demands, by “can you just get this to me by morning?”
This isn’t a lab experiment or a theoretical data model. It’s a platform grounded in the lived reality of market access consulting: built by people who’ve done the work, for people who need to get the work done faster, better, and with confidence. That’s what makes our ontology different. And that’s why it works.
An ontology on its own is just a structure. Its true value is revealed in how it transforms the tools built on top of it.
In Knowledgeable, the ontology is the engine that drives every interaction, every insight, and every decision. It makes AI smarter, search more precise, and strategy faster to execute. It turns unstructured information into structured advantage.
Below, we explore how the ontology shapes the core product experience across discovery, insight generation, and reuse. Giving consultants superpowers they’ve never had before.
Traditional search tools operate like metal detectors: they scan for surface-level matches and deliver whatever contains your keyword. But in a domain as complex as market access, this approach yields an avalanche of noise.
With an ontology-based system, search becomes semantic. It understands intent as well as content.
Ask for “evidence supporting second-line biologics in ulcerative colitis,” and the system won’t just retrieve studies that mention those terms. It will prioritise:
All of this happens because the underlying ontology knows the relationships between indication, treatment line, study design, and regulatory relevance.
"It’s like asking an analyst with years of context, not a PDF indexer." - Consultant, early tester
AI summarisation without structure is like letting someone read 500 pages and guess what you care about. Sometimes they get it right. Often, they don't.
Because Knowledgeable’s ontology tags content based on its strategic role: trial outcomes, pricing decisions, value messages, clinical endpoints. Our summarisation engine knows what to prioritise, and what to ignore.
When a consultant asks for a summary of a study, they don’t get generic text. They get a tailored summary highlighting:
This makes the difference between a decent summary and one that’s presentation-ready in minutes.
Because every data point is semantically tagged and linked, Knowledgeable can surface connections across previously siloed information.
Examples include:
These patterns emerge because the system understands how data is used to make decisions.
In traditional workflows, most of the value created during a project is lost in documents, slides, and inboxes. Even high-quality analysis often becomes siloed, unsearchable, and hard to repurpose.
Because Knowledgeable captures every piece of work in a structured, ontology-backed format, each project becomes a reusable, searchable knowledge asset.
That means:
“It’s like building up institutional memory that's always working to make you better, it's science fiction.” - Market Access Director, pilot program
A well-designed ontology redefines the experience of working with information. In Knowledgeable, it transforms every stage of a market access project: from the first literature scan to the final executive slide.
It gives teams the confidence that they’re seeing what matters, skipping what doesn’t, and building on a foundation that grows stronger with every project. And that’s what strategy should feel like.
Technology is only valuable when it delivers real outcomes. With Knowledgeable, the benefits are more than theoretical, they’re felt in the day-to-day experience of market access consultants, strategists, and business leaders alike.
This is not a system that simply “organises data.” It’s a system that frees up strategic minds, shortens timelines, and strengthens every client interaction. Below, we explore the practical impact on both individual consultants and the business at large.
In market access, confidence is a huge requirement. Whether you're developing a Global Value Dossier or preparing for an HTA submission, decisions need to be backed by clearly traceable, source-linked evidence.
With Knowledgeable, every data point is embedded in a structured lineage:
This traceability doesn’t just protect the team; it builds trust with internal reviewers, regulatory partners, and clients.
Traditional project setup often includes 10–15 hours of desk research just to gather and filter relevant materials before the real work begins. Proposal writing may take days more. That lag eats into margins and delays value.
With our AI-powered, ontology-driven system:
This allows consultants to begin at a level of insight that previously took a full-time analyst days to reach.
“We had a brief on a new asset land Thursday evening. By Friday lunchtime, the team had a full strategic outline, citations included, ready to send. That’s a different category of capability.” - VP Market Access, pilot program
Most consultancies start from scratch every time, even when they’ve done similar projects before. That’s because knowledge is scattered across decks, folders, and inboxes. The insights exist, but they’re not accessible.
Knowledgeable fixes this. Every deliverable, insight, and rationale is structured, tagged, and stored, meaning:
The result is a compounding advantage: each project adds momentum to the next, building institutional knowledge that sharpens over time.
Market access is drowning in information. The hard part is selecting the right signal from the noise and using it to create a clear narrative.
Because Knowledgeable structures everything semantically, from trial endpoints to value propositions to regulatory outcomes, your team can:
This leads to tighter decks, stronger rationales, and less time spent in revision cycles. Ultimately improving delivery and client satisfaction.
Our first pilot partner was faced with a common challenge: a new prospect brief arrived with little context, minimal time, and high expectations. The team had 24 hours to respond with a credible, tailored proposal.
Using Knowledgeable, they:
The result? A successful pitch, a new client, and a team that reported feeling “like we had an extra three analysts working overnight.”
For consultants, Knowledgeable means more strategic headspace, less manual lift, and faster time to value.
For the business, it means higher-quality outputs, stronger margins, and a system that grows more powerful with every project.
In short: this is how expertise scales.
What makes an ontology truly powerful isn’t just how well it works today, it’s how well it adapts to what comes next.
The pace of change in healthcare and pharmaceuticals is relentless. New therapy classes emerge. Regulatory frameworks shift. Reimbursement landscapes vary across geographies and evolve year to year. Static systems can’t keep up. That’s why we’ve built a living, adaptive ontology: designed to evolve alongside the industry it serves.
Every time a consultant uses Knowledgeable, the system becomes more useful. Each project adds new data, refines existing relationships, and improves the system’s ability to distinguish what matters.
For example:
This means the system never stays static. It continuously reflects the real-world decisions, language, and frameworks that define modern market access strategy.
While AI supports this adaptability, we don’t leave evolution to machines alone. Every update to our ontology is overseen by a human-in-the-loop governance model, led by:
This hybrid model ensures the system stays strategically useful, regulator-ready, and compliantly grounded, even as it evolves.
As the ontology grows in richness and flexibility, it does more than support workflows, it begins to coordinate them.
We’re already seeing how structured relationships between data points, stakeholders, and project outputs allow the platform to:
This positions Knowledgeable not just as a research tool, but as a strategic operating system for market access consulting. A platform that helps teams not only act faster, but think more clearly and work more cohesively.
There’s a lot of hype around AI. But the reality is simple: AI is only as smart as the structure it sits on. Without a foundation of clean, connected, domain-specific data, even the best models become unreliable or unhelpful.
We’ve spent over a decade building that foundation—ensuring that our AI capabilities are grounded in structured knowledge, attributable sources, and decision-relevant logic. As new models emerge, we’re ready to integrate them, but always in a way that serves real strategy.
The Knowledgeable ontology isn’t static, academic, or abstract. It’s a living framework. Purpose-built, expert-governed, and strategically aware. It grows as the field grows. It adapts with each new challenge. And it enables consultants to navigate complexity with clarity, confidence, and speed.
In a world where agility is the new edge, this is the next level.
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