My team at AlphaSense advises life sciences buyers looking to license or acquire drug programs from pharmaceutical companies. In this business, leads come from all over: investment bankers working on behalf of sellers, conversations with other drug companies, and industry whispers about who is buying what. The amount of information coming at teams every day means it’s important to be able to separate the signal from the noise, yet harder than ever to do so.
The teams I advise use AI agents like SuperAnalyst to turn due diligence into a standing capability. SuperAnalyst fully automates the initial review process by uncovering the drug programs that match the buyer’s profile, running each program through the same set of questions, and linking every finding to its source so teams can check its work before putting their weight behind a recommendation.
SuperAnalyst In Action
Consider: A midsize drug company already sells treatments for liver and metabolic conditions. It’s looking to add a drug for MASH, a liver disease linked to obesity and diabetes. It wants a drug that has already shown results in patients, at a price it can afford.
On top of those criteria, the company has a five-question framework that it wants to apply to gauge each in-licensing opportunity:
- Does the opportunity fit our portfolio strategy and priorities?
- How differentiated is the asset, and is that reading backed by hard evidence?
- What do we know about the deal context, and what remains unclear?
- Which gaps matter enough to investigate before moving forward?
- Does the opportunity warrant deeper diligence, and why?
The company’s business development lead starts by saving these criteria and questions as a custom skill in SuperAnalyst. Because SuperAnalyst remembers conversations and decisions made in one session and carries them forward to future sessions, it gives a solid foundation for the team’s next project. In just over two minutes, the skill is saved and ready to deploy.
From there, the business development lead simply gives SuperAnalyst an acquisition or licensing mandate and asks it to run through the newly created skill. SuperAnalyst pulls from expert transcripts, broker research, and company documents in AlphaSense, using the latest insights to build the candidate set.
In this example, SuperAnalyst returns a dozen independent drug candidates, each one graded across the business development lead’s criteria and questions, shown in a side-by-side table view for quick comparison. It also narrows down that list of 12 into a shortlist of three especially promising drug candidates. Running the skill takes just over eight minutes.
A quick glance at the shortlist reveals that one of the candidates is a single-asset company weeks away from a Phase 3 readout. This looks promising as an acquisition target, yet SuperAnalyst flags that the asset’s rights are already licensed out in parts of Asia. Further reading shows that the asset’s value hinges on a readout that hasn’t happened yet, so this candidate goes on the business development lead’s watch list rather than straight into formal due diligence.
That leaves two drug candidates to focus on. For the first one, SuperAnalyst surfaces published biopsy results from a mid-stage trial, along with broker research reporting that the owner intends to license the drug. The second candidate met both of the main goals of a recent mid-stage trial. SuperAnalyst surfaces a recent company filing where management said further drug development was contingent on receiving outside funding, flagging this as a sign of openness to a deal.
That’s 12 drug candidates that may have otherwise gone into costly traditional diligence — turned into two high-conviction candidates and a third to watch closely.
Shortlist in hand, the business development lead recommends moving the two leading candidates into deeper review. For the waitlisted third candidate, SuperAnalyst re-runs the review using the pre-built skill and criteria, and shows what changed. If the trial results hold up, the candidate is ready to move straight into the next round of review.
Key Proof Points
Before SuperAnalyst, a first-round review meant pulling from multiple databases, reading white papers and press releases, and checking each claim manually. Existing licenses and funding terms often came up late in the process, changing the valuation math and sending teams back to the drawing board. SuperAnalyst compressed that entire early review process from several weeks into less than 15 minutes — and it all happened in the background while the team worked.
With SuperAnalyst taking on the heavy lifting of discovery and first-pass diligence, teams are free for higher-order decision-making. Instead of pulling data and checking sources manually, the team spends that time on the ground with the prospective seller, or building a more defensible business case for leadership.
Want to try SuperAnalyst for yourself? Log in to AlphaSense and start exploring how SuperAnalyst can transform your life sciences workflow, or sign up for a free 2-week trial today.
