Oracle ties a conference organizer at the top, while the pure-play discovery platforms the buyer is comparing sit nowhere in the top ten.
As of August 2026, Oracle and Cambridge Innovation Institute, LLC are tied atop the AI drug discovery ad surface on ChatGPT at 13 placements each. None of the pure-play discovery platforms the buyer is comparing, Absci, Ginkgo Bioworks, or bigHat Biosciences, appear in the top ten.
Cloud, events, and clinical-services vendors are renting the AI drug discovery ad surface on ChatGPT, while the pure-play discovery platforms the buyer is comparing are absent from the leaderboard.
Four of the top five are cloud, events, or clinical-services vendors, not discovery platforms.
| Buyer is comparing | Actually advertising in top 10 |
|---|---|
| Absci | Oracle |
| Ginkgo Bioworks | Cambridge Innovation Institute, LLC |
| bigHat Biosciences | Certara |
| Aidoc | Cypris |
| Zebra Medical | Worldwide Clinical Trials |
| Paige AI | Parallel Fluidics |
The brands the buyer is asking ChatGPT to compare are nowhere on the leaderboard. The surface is being rented by everyone except the platforms themselves, and this window closes the day any of those absent players files a campaign.
The only visible comparison and bottom-of-funnel campaigns are Carta's 20260616-amer-corp-competitor and Comp AI's bofu_frameworks and brand_brand_defense. Neither is an AI drug discovery platform, so the comparison slots the buyer is asking for are uncontested.
The precision-medicine cluster is more than 8x smaller than the clinical and biomarker cluster, with only 10 advertisers covering it. Targeting that gap is cheaper and faster than competing for the parent category.
Inside the larger clinical and biomarker cluster, 'ai biomarker discovery tools for immunotherapy response prediction' shows up in the top fourteen prompts, but the supply behind it is buried across 47 advertisers fighting for the parent term. A sub-cluster play on that single prompt is the cleanest entry point in the data.
Three moves this week: (1) pick one sub-cluster, e.g. biomarker discovery for immunotherapy response prediction, and concentrate spend there instead of spreading thin across the parent category. (2) Launch a comparison-defence or pricing-anchor creative against the 'vs' and 'affordable' prompts before Absci, Ginkgo Bioworks, or bigHat Biosciences files a campaign. (3) Test two or three sub-clusters before committing a single line item, and watch the leaderboard daily for a new competitor campaign entry.
As of August 2026, Oracle and Cambridge Innovation Institute, LLC are tied at the top with 13 placements each (4.91% share apiece), followed by Certara and Cypris with 12 placements each, and Worldwide Clinical Trials with 11. The top five skews toward cloud, events, and clinical-services vendors rather than pure-play discovery platforms.
It is the most fragmented surface in the dataset. The top three advertisers hold 14.35% combined across 265 placements and 115 advertisers, an average of just 2.3 placements per advertiser.
The buyer intent is unusually high and the supply is unusually thin. Eight of the fourteen top triggering prompts are 'vs' comparisons, pricing queries, or 'affordable' budget asks, yet only Carta and Comp AI are running comparison or BOFU campaigns, leaving most comparison slots uncontested.
Comparison and budget queries dominate. Top prompts include 'absci vs bighat biosciences pricing and turnaround', 'Absci vs Ginkgo Bioworks for AI-powered antibody discovery', and 'aidoc vs zebra medical vs paige ai for radiology diagnostics', plus the 'affordable ai protein design platforms', 'affordable computational biology platforms', and 'affordable precision medicine platform' budget queries.
As of August 2026, the visible ChatGPT-built campaigns are Carta's 20260616-amer-corp-competitor (a competitor campaign) and Comp AI's bofu_frameworks and brand_brand_defense. No pure-play AI drug discovery platform has filed a comparison or BOFU campaign on this surface.
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