AI Representation Intelligence for Pharma
Visible is not Winning.
How your brand wins in ChatGPT, Claude, Gemini and Perplexity.
Theralexis measures whether AI prefers your brand when treatments are compared, where it positions you, which attributes you own and which sources underpin the answer — followed by channel and content activation to improve your AI representation.
One AI answer, scored the Theralexis way
Illustrative
Cardiologist · Germany
“Which first-line option would you consider for a 62-year-old with uncontrolled hypertension?”
For most patients, guidelines favour starting with Brand B or a combination. Brand A is a more effective alternative, though Brand B is generally better tolerated over the long term…
Sources cited: a society guideline, a medical portal, one KOL review
What Theralexis sees
- Named first
- Brand B
- First-line position
- Brand B
- Preferred when compared
- Brand B
- Associated with efficacy
- Brand A
- Associated with tolerability
- Brand B
- Key message present
- No
The Theralexis intelligence base
300,000+Product mentions
- 25,000+AI responses
- 400+Brands & molecules
- 70+Patient profiles
- 50+Stakeholder types
The shift is already happening
Healthcare professionals are already asking AI to compare medicines.
At ESC Congress 2026, we asked 27 healthcare professionals how they use generative AI for medical information. Their answers describe a channel that now sits between a brand and the people who prescribe it.
93%
said information from an AI system had influenced how they understood a disease or treatment.
25 of 27 respondents
70%
said it had influenced a treatment decision.
19 of 27 respondents
82%
had used generative AI to compare the efficacy of different medicines.
18 of 22 respondents asked
“If the same medical question were answered by both generative AI and a pharmaceutical company, which answer would you generally trust more?”
- Generative AI
- 45%10 of 22
- Pharmaceutical company
- 23%5 of 22
- About the same
- 23%5 of 22
- Neither
- 9%2 of 22
This is already a commercial channel.
HCPs are using generative AI not only to retrieve information, but to compare medicines and inform treatment decisions. That makes how a therapy is represented in AI commercially relevant.
Beyond visibility
Your brand can lead on visibility and still lose the answer.
Visibility tells you whether your brand appears — the layer most SEO and GEO tools report, and more of a hygiene factor than a differentiator. Theralexis measures how AI represents your brand when it does appear: against the competitors that matter, for the stakeholders you serve, in each market and language. Then it tells you where to act.
Cardiologists · Germany · four AI systems
Illustrative
- Your brand
- Competitor
| Measure | Your brand | Competitor |
|---|---|---|
| 01AI VisibilityDo you appear, and where? | ||
| Mentioned in answers | 72% | 64% |
| Share of voice | 38% | 31% |
| Named first | 31% | 46% |
| 02AI RepresentationHow are you represented when you appear? | ||
| Brand Representation | ||
| Positioned first-line | 28% | 52% |
| Preferred when compared | 2 of 8 | 6 of 8 |
| Associated with efficacy | 61% | 48% |
| Associated with tolerability | 29% | 57% |
| More Brand Representation measures | ||
| Strategic Alignment | ||
| Key messages present | 3 of 6 | 5 of 6 |
| More Strategic Alignment measures | ||
| Therapeutic Accuracy | ||
| Evidence represented accurately | 84% | 90% |
| More Therapeutic Accuracy measures | ||
| Source Intelligence | ||
| Advocates for your brand | 12% | 27% |
| More Source Intelligence measures | ||
03ActionWhat actions can you take to improve AI representation?
Channel activation
- Guidelines
- Publications
- Top domains
- Pharma-owned
- HCP / professional
Content recommendations
- Approved claims
- Evidence
- Existing content
Channel and content activationto improve AI representation
High visibility, low preference.
Your brand is mentioned more often, yet the competitor is named first, placed first-line and preferred in six of eight comparisons.
The attribute split.
AI associates your brand with efficacy and the competitor with tolerability — so when a question turns on tolerability, the focus turns on them.
Measured where it happens.
Each stakeholder, market, language and AI system is measured on its own, because each can result in a different answer.
Intelligence Centre
Even the simplest layer shows why visibility is not enough.
Our AI Visibility benchmarks are free and public. They measure whether a name appears and, in some, in what order — and even at that layer, the answers split by system, by molecule and by brand. Real findings, each with its scope.
AI Visibility benchmark
AI names the molecule. The brand, far less often.
Share of answers naming each molecule and its brand. In our ESC survey, 14 of 27 respondents usually ask about a medicine by molecule;3 by brand.
LDL-C Lowering Market, Germany · 596 answers from Claude, Gemini, ChatGPT and Perplexity, asked in German from the perspective of cardiologists · September 2026
AI Visibility benchmark
Consistent on the class. Far apart below it.
- Therapy classesBoth classes, every system
- 80%–99%
- MoleculeLebrikizumab
- 38%–94%
- BrandAdtralza
- 3%–62%
- MechanismIL-13
- 4%–85%
Lowest to highest share of answers across the four AI systems. Every system named both therapy classes; below the class, the widest gap between two systems was 56 points for a molecule, 60 for a brand and 81 for a mechanism.
Atopic Dermatitis Market, Austria · 752 answers, 188 from each of Claude, ChatGPT, Perplexity and Gemini, asked in German from the perspective of dermatologists · 24 September 2026
AI Visibility benchmark
One brand. Four AI systems. Four different pictures.
Dupixent, by AI system
Share of each system's answers naming the brand Dupixent, to the same questions. A brand team looking at one system would see a different market from a team looking at another.
Atopic Dermatitis Market, Austria · 752 answers, 188 from each of Claude, ChatGPT, Perplexity and Gemini, asked in German from the perspective of dermatologists · 24 September 2026
From measurement to action
Four steps. One repeatable cycle.
The same cycle runs in every engagement, so a country scorecard and a global report read the same way — and every result can be compared with the one before it.
01 Align
Mirror your market reality
Business priorities, competitors, stakeholder personas, markets, languages and key messages define what is measured.
02 Benchmark
See where you lead, lag or are missing
Against your direct competitors, against your own trend and across every AI system in scope.
03 Deep dive
Understand what sits behind the numbers
Positioning, attributes, messages and the sources that underpin each answer — by stakeholder, market and system.
04 Act
Know what to change, and who owns it
Gaps prioritised by what they mean for the brand and how actionable they are, then re-measured in the next cycle.
Who it is for
Built for cross-functional pharma teams
Commercial
Are we preferred when AI compares treatments — or only mentioned?
Medical Affairs
Which societies, KOLs and sources underpin the answer?
Digital & AI
Where should owned channels and structured content act first?
Regional Teams
How does representation differ by country, language and stakeholder?
Launch Excellence
How is the disease area represented before launch — and what changes after?
The conversation about your brand is already happening.
The question is whether you’re leading it.
Tell us the brand and the market. We will show you how AI systems represent it, how it compares, and where your teams could act first. No obligation, no sales presentation.
