Daniel Tran, PharmD
Oncology Marketing Manager
HCP Omnichannel Marketing & Commercial Intelligence
Pharma Strategy, Written in Code
Oncology marketing professional (PharmD) who designs data-driven omnichannel strategies that accelerate HCP adoption for high-stakes launches — with direct experience in ADC commercialization, AI-driven marketing, and building the commercial intelligence tools I wished I'd had as a brand marketer, on real data from CMS Open Payments, the NPI registry, PubMed and ClinicalTrials.gov.
Selected Work
Flagships
Built on real data or running in production.
The Deal Desk
Primary-source retrospectives on landmark biopharma acquisitions — each deal reconstructed from SEC, FDA, FTC and court filings, and graded twice: was the bet reasonable, and did it pay?
Oncology Intelligence Dashboard
Live pipeline and publication intelligence — ClinicalTrials.gov, PubMed, CMS Open Payments and the NPI registry, unified for any oncology indication.
KOL Influence Network
Opinion-leader mapping over real CMS Open Payments records — PageRank centrality, Louvain communities, and an interactive force-directed graph.
NCCN Guideline Monitor
A scheduled Cloudflare Worker that watches NCCN oncology guideline versions and records every change, with per-guideline version history.
Platforms
OncStrata
Full-stack commercial intelligence — FAERS safety, CMS spend, provider utilization, FDA labels, trials, publications and Open Payments, all on real data in Cloudflare D1.
vMLR
AI-assisted Medical-Legal-Regulatory review of promotional pieces from five reviewer perspectives, with coordinate-based annotation and Veeva PromoMats integration.
Strategy
Comparative Launch Dynamics in Desmoid Tumors
Second-entrant strategy for varegacestat vs. nirogacestat — cross-trial placebo-arm vulnerability, revenue forecasting, and risk-weighted positioning.
ReadinessLaunch Readiness Scorecard
A risk-weighted, failure-benchmarked 7-dimension framework with a fully worked lower-risk MDS case study against Reblozyl.
Methods & Models
Quantitative and ML methods applied to commercial and clinical questions — illustrative builds on synthetic data.
Writing
Recent essays
Once a first-in-class drug is approved, the remaining patients eligible for the second entrant's trial are different. Enrollment-era bias means placebo arms in sequential trials are not comparable — and cross-trial superiority claims built on that foundation are weaker than they appear.
Conventional pharma wisdom assumes oral beats injectable. But Part B buy-and-bill economics create financial incentives for community oncologists to maintain infusion-based prescribing — and the patient cost math can actually favor the needle.
In rare disease, the standard launch playbook assumes the market exists. But when class penetration is below 30%, the majority of eligible patients are undiagnosed. The real competitor isn't the incumbent drug — it's diagnostic inertia.
About
I'm a PharmD (UC San Diego) who has spent a career at the intersection of clinical science and commercial execution. From HealthTech product management at PrecisePK to Pfizer Oncology brand marketing, my arc has always been about closing the gap between what clinicians know and what technology can deliver.
Today I design and execute data-driven omnichannel strategies for high-stakes oncology launches — managing a ~$10M brand budget, directing AI-driven marketing platforms, leading SEO/SEM transformation, and building the commercial intelligence tools I wished I'd had as a brand marketer.
Marketing Manager, Heme/Onc. Interim Omnichannel Lead directing the AI-driven EMPOWER platform launch; Brand Budget Captain over ~$10M OPEX; +38% SOV while cutting media spend 2%; led the $2M Seagen→Pfizer portfolio integration (600+ assets, $400K saved).
Sales & Marketing Manager. Secured VA VISN 22 federal adoption; led Epic/Cerner EHR integration roadmap; directed white papers on Bayesian dosing and AKI reduction.
Doctor of Pharmacy, UC San Diego. Veeva CRM/Vault, GA4, Tableau, IQVIA, SEO/SEM, Bayesian statistics, Astro, React, Cloudflare Workers & D1.