When you read the Pharma news sites and analysis on LinkedIn about drug patent cliffs, you might think pharmaceutical companies are sitting on their hands waiting for the inevitable. However, in addition to internal R&D, all the companies have large teams scouting for the next big thing, engaging biotechs and academics directly, and using consultants to support research into new areas.
Today’s history comes from an interesting asset identification/landscaping exercise I did for a search and evaluation team.
It’s written with early-stage biotechs and academic groups in mind—those curious about how their science might land before a big pharma / medtech decision-maker. However, some process and tool tips might also be helpful for those conducting this work.
The Scope and the Challenge: A Wide Net, Well Cast
Most pharma Business Development, Search & Evaluation, and Insights teams aren’t just focused on what’s inside the walls of their current portfolio and future competitors. They’re actively scanning two additional spaces:
- The adjacent: new indications within their core therapy areas
- The bold: they may want to enter entirely new therapy areas—or at least keep tabs on in case a competitor does.
This project sat right at that intersection.
Our client—a top-tier pharma—had a marketed asset and several pipeline candidates in one therapy area, and they were starting to explore expansion opportunities into adjacent indications. That included potential in-licensing, partnerships, or acquisitions. My task? Build a comprehensive landscape to help them make informed decisions.
It was one of the most expansive scopes I’ve taken on since founding Sivan Consulting:
- ~20 indications
- Five therapy areas
- Four emerging modalities: targeted protein degraders, bispecific antibodies, antibody-drug conjugates, and antisense oligonucleotides
That last point helped narrow the scope —traditional small molecule inhibitors and regular monoclonals were out—but we were still casting a wide net because of the first two points.
Standard tools like GlobalData, AdisInsight, or ClinicalTrials.gov give you a solid baseline for clinical-stage assets. You can filter for the indication quickly, pull a dataset, clean it up and cross-check with another source, and have a good initial list of assets to begin review of data and websites.
But here’s where this project got more interesting—and more manual.
We also needed to uncover preclinical developments, which meant moving beyond databases into the messier world of academic research, stealth-mode biotechs, and unstructured sources. These early-stage players aren’t exhaustively covered in the subscription databases and finding them requires some digital detective work:
- Scouring conference abstracts
- Reviewing academic articles
- Digging through patent filings
- Searching for small biotech companies from their websites or press releases
Search smart, capture smarter: How I built the asset universe
To build the initial asset list, I started with one indication. I began testing searches across multiple sources: PubMed for academic publications, Google for broader discovery, and AI tools like ChatGPT and Perplexity to help uncover less obvious connections between modalities, mechanisms, and disease subtypes. I used various search terms—combinations of modality, MoA, and target pathway—and manually screened hundreds of hits to identify assets.
Once I had a feel for the patterns that worked, I scaled the approach across the complete list of indications, refining as I went. New keywords would emerge in one area —especially when I stumbled on assets I hadn’t expected—and I’d use these for earlier searches to fill gaps and catch potential misses.
I relied on my go-to tool for capturing all this data: Notion.
It’s so much better than Excel for this type of activity. It’s flexible enough to let you build a relational database on the fly, with linked tables for assets, developers, and indications.
Each drug or asset becomes a page, not just a spreadsheet line, allowing easier visualization of clinical data, storage of website screenshots, and embedding of articles or investor documents.
The best part? The built-in filtering, sorting, and “View Layouts” in Notion let me storyboard and compare information before writing slides. If I wanted to quickly view assets by indication or see how many TPDs are preclinical vs. Phase I, it’s a click away.
How to Get Noticed (for the Right Reasons): A Note to Early-Stage Biotechs
Let me digress from the main project history for a moment, because this part matters—especially if you’re an early-stage biotech or device startup hoping to partner with, license to, or eventually be acquired by a big pharma or medtech company.
Landscaping exercises like this are often the first time your company appears on a pharma’s radar. And first impressions… well, they stick.
What surprised me most was the sheer variety in quality of company websites and materials—and I don’t mean scientific quality, I mean presentation. Crucially, this didn’t correlate with the stage of development.
- Some preclinical biotechs communicated well: they provided clear explanations of the science, published data on relevant models, well-articulated hypotheses for use cases, and thoughtful commentary on where they could fit into future treatment landscapes—all supported by credible medical advisors or independent collaborators.
- Then there were companies in Phase 2 that looked like they borrowed their cousin’s school IT project. Either vague marketing fluff with no technical detail, or a dump of dense science with zero framing for how the asset might be used or commercialised. Some hadn’t updated their site in years, leaving the impression they might be dormant—or worse, defunct.
The hard truth is that whether you’re in IND-enabling studies or running a pivotal trial doesn’t matter. If your public-facing materials aren’t explicit, current, and professional, you will be harder to track, harder to understand, and—frankly—easier to overlook.
So what should you do?
- Have a clear, current website. Explain the science and commercial potential in plain language and scientific depth—ideally, both.
- Keep it updated. Regular news posts, even small ones, show momentum and life.
- Use visual storytelling. Graphics, videos, mechanism-of-action animations—hundreds of talented freelancers on platforms like Upwork, Fiverr, or LinkedIn can bring your story to life without draining your seed or Series A funding.
- Be searchable. SEO matters. If you’re invisible on Google, you’re invisible to BD teams.
- Publish if you can. Conference posters, peer-reviewed articles, and even preprints help validate your science and increase your visibility.
In short, you never know when a landscaping analyst (like me) is building a table that might land before a pharma exec. Make it easy for us to find you—and even easier to understand why you matter.
From Data to Direction: Making Research Work for Pharma BD
Given the scope and the fact that this was a solo effort, the desk research phase took around 4–5 weeks. During that time, I built the database, identified assets, dug through publications, pieced together developer backgrounds, and flagged any edge cases or ambiguous fits for discussion.
Throughout the process, I met regularly with the client team. These check-ins served three critical purposes:
- To review progress and validate inclusions
- To discuss how the final report would be used internally
- And to refine how we’d present the findings
As the asset list grew—eventually topping 150 distinct programs—it became clear we’d need a careful approach to data presentation. A standard “BD radar plot” wasn’t going to cut it. There was too much data, too many dimensions.
An example radar plot for a single therapy area (Alzheimer’s). This format would have quickly been overwhelming with the number of indications and modalities on the project. Reproduced from Cummings et al under the Creative Commons Attribution-NonCommercial-NoDerivs License https://doi.org/10.1002/trc2.70098.
We used Notion views to prototype different structures, and I shared early sketches with the team to explore:
- Disease-focused views
- Modality-focused views
- Development-stage breakdowns
- Big pharma activity
- Types of cell-targeted
Each session refined the structure so the right people could quickly find what mattered to them. We wanted the report to be usable by multiple internal groups: the core BD/search team, insights colleagues, R&D scouts, and leadership.
After several iterations, we settled on a format that balanced clarity with depth: layered summaries supported by a complete asset database, which lets users zoom in on their area of interest while still seeing the broader picture.
Beyond the Deck: Turning Research into Conversations
The final deliverable did more than map the landscape. It became a shared internal reference point—one that helped the team:
- Prioritise follow-up with biotechs they hadn’t previously engaged with
- Sense-check internal assumptions about the competitive environment
- Spot white spaces in their modality/indication matrix
- Anticipate potential acquisition moves from rival pharma companies
- Have more informed conversations with medical and scientific experts
Crucially, it armed them with the context to approach external discussions from a position of knowledge, not just asking, “What do you do?” but, “We noticed you’re one of only three players working on X in Y indication. Can you tell us more about your approach?”
Wrap up
Let me know what you thought about the article, if it helped you learn more about asset scouting, or if it was helpful for how to update your biotech’s marketing materials!