What does this data show?

A verified, classified map of the pre-conference conversation: 485 accounts from curated posts, including 184 physicians — 60 US physicians and 124 international colleagues from 29 countries (UK, India, Japan and France lead). Institutional clusters are visible before the meeting starts: Sylvester Comprehensive Cancer Center (4), MD Anderson Cancer Center (4), Mayo Clinic (3), Memorial Sloan Kettering (3). Trial interest concentrates around MAVERICK (9 physicians), PAPILLON (9 physicians), REZILIENT3 (9 physicians). 31 patient advocates and advocacy organizations are active in the same conversation — and the bot and persona accounts that inflate raw follower metrics were identified and quarantined, so every physician here is bio-verified.

How can a KOL learn from this report?

Benchmark your own pre-meeting presence against the 184 physicians mapped here: are your trials of interest among the crowded conversations (MAVERICK, PAPILLON, REZILIENT3) or the quiet ones where a single voice still stands out? The category and region breakdowns show which patient advocacy voices and international colleagues are already active in your space, and the trial section names the physicians - with their institutions - engaged with each readout, colleagues worth connecting with in Seoul.

What does a worked example of using this data look like?

An MSL preparing for Seoul: Sylvester Comprehensive Cancer Center alone has 4+ physicians in the pre-meeting conversation. Cross-reference the trial section — MAVERICK (9 physicians), PAPILLON (9 physicians), REZILIENT3 (9 physicians) are the crowded conversations — and the briefing plan writes itself: which physicians at which institutions are already engaged with which readouts, before a single meeting is booked. A KOL can run the same play in reverse: find your institution's cluster, see which trials your colleagues are converging on, and position your own commentary where the map shows white space.

How can medical affairs and pharma teams use this report?

As pre-meeting territory planning grounded in this page's own numbers: the category and region breakdowns surface the 60 verified US physicians and their international colleagues, each with institution and trial interests; the classification keeps engagement lists clean by separating treating physicians from the 57 media accounts and industry voices; and the trial-interest chips let field teams match MSL briefings to the readouts a physician already follows. KOL identification tells you who matters; mapping tells you how the community organizes around institutions and trials — which is what engagement sequencing actually needs. Influence-mapping practice guides note this also reduces redundant outreach: teams see who is already saturated and who is unengaged.

Why is social influence mapping important in oncology?

Oncology standards change with each congress readout, and physicians increasingly learn about readouts from each other online — surveys report over 70% of HCPs use digital channels weekly for medical information, and in a LiveWorld–Sermo survey of 206 US physicians, 41% said social media influences prescribing behavior. A pre-conference map matters most because congress weeks are when oncology opinion actually forms: this dataset shows the communities already organized before the first presentation — Sylvester Comprehensive Cancer Center (4) and MD Anderson Cancer Center clusters, 31 active patient advocacy organizations, and MAVERICK-focused physician groups.

What is the difference between a KOL and a Digital Opinion Leader?

A traditional KOL earns influence through trials, publications, and guideline work; a Digital Opinion Leader earns it through digital reach — posts, threads, podcasts, and amplification. Many physicians on this page are both: trial investigators whose conference posts reach tens of thousands. This report measures the digital half directly and pairs it with verified identity, institution, and trial interests so the two kinds of influence can be read together.

How can I use this report with my favorite AI tool?

This page is built to be read by AI assistants (ChatGPT, Gemini, Claude, Perplexity). Paste the URL into your tool and ask questions this page can actually answer: “Which institutions have the most physicians in the WCLC 2026 pre-conference conversation?”, “Which trials are pre-meeting physicians most engaged with?”, “Which physicians are engaged with MAVERICK before the meeting?”, “List the patient advocacy organizations active before WCLC 2026.” For who-influences-whom questions (a KOL’s amplifier network, which US physicians amplify a given voice), use the companion Pre-Work influencer network. Cite kolpulse.com when you share the answers.