A new way to improve potency needed the right scientific audience
QuanMol was offering something more specialized than a general-purpose discovery service: an AI-powered approach to small-molecule potency optimization. The outreach had to reach people close enough to discovery and lead optimization work to judge whether that approach might fit a real program.
We started by targeting small and mid-sized drug developers who had small-molecule assets in discovery or lead optimization. At smaller companies, the list centered on founders, CEOs, CSOs, CTOs and other C-suite leaders. At larger organizations, we focused on more specialized roles, including medicinal and computational chemists, R&D leaders, chemistry department heads and program leaders.
Calls opened the door; pipeline-specific emails carried the context
The campaign was primarily phone-based. Calls gave us a direct way to introduce QuanMol and learn whether potency optimization was relevant to any of the prospects’ drug candidates. We supported those conversations with targeted emails personalized to assets in each prospect’s pipeline. That mattered for an offer tied to a specific stage of drug discovery: a generic “AI can speed up discovery” message would have said very little about why a particular team should pay attention.
As the campaign progressed, we shifted more attention toward larger companies. Early-stage startups could be scientifically relevant, but larger teams often had more budget and room to test a new technology. We kept the scientific fit at the center of the list while putting more effort behind accounts with a stronger path to a commercial project.
The meetings were a start, not the finish line
In the first three months, the campaign booked 19 meetings. Roughly three-quarters were deemed qualified leads, and two prospects progressed to final vendor selection. One of those became the signed six-figure pharmaceutical deal. That sequence matters: the booked meetings created opportunities, but the contract was the commercial result behind the reported return.
The 1,200% ROI figure reflects the first three months as reported by QuanMol and excludes potential milestone and royalty payments. It describes this campaign, not an expected outcome for every scientific service provider.
What this case shows
For a specialized discovery offer, the account list and the conversation have to be just as specific as the science. QuanMol’s campaign combined program-stage targeting, calls to the people closest to the work, emails grounded in individual pipelines and a shift toward companies better positioned to buy.