Biotech & MedTech
How biotech and medical-device companies work, and the finance, marketing, data and AI that run them.
The programs
Five programs, one per domain of the Biotech & MedTech sector. Every one is readable straight away, without an account, and you can gauge your level on any of them whenever you want.
Biotech & MedTech
This block builds foundational fluency in the biotech and medtech sector, covering how value is created from discovery through clinical development, manufacturing, and commercialization.
18 lessons · about 4h
- Map the biotech and medtech value chain and locate where margin and power concentrate
- Identify major player types and analyze competitive and power dynamics across the chain
- Apply the key US and EU regulatory requirements (FDA, EMA, MDR) to real compliance situations
Finance for Biotech & MedTech
Finance in Biotech and MedTech operates under conditions few other sectors face: long pre-revenue horizons, binary clinical outcomes, patent cliffs, and reimbursement uncertainty.
31 lessons · about 6h
- Map the biotech and medtech value chain and locate where margin and power concentrate
- Identify major player types and analyze competitive and power dynamics across the chain
- Apply the key US and EU regulatory requirements (FDA, EMA, MDR) to real compliance situations
Marketing for Biotech & MedTech
Marketing in biotech and medtech operates under tight scientific and regulatory constraints that separate it from consumer sectors.
31 lessons · about 6h
- Map the biotech and medtech value chain and locate where margin and power concentrate
- Identify major player types and analyze competitive and power dynamics across the chain
- Apply the key US and EU regulatory requirements (FDA, EMA, MDR) to real compliance situations
Data for Biotech & MedTech
Data is the operational backbone of biotech and medtech, spanning clinical trial datasets, genomic and molecular readouts, electronic health records, device telemetry, and adverse event reports.
31 lessons · about 6h
- Map the biotech and medtech value chain and locate where margin and power concentrate
- Identify major player types and analyze competitive and power dynamics across the chain
- Apply the key US and EU regulatory requirements (FDA, EMA, MDR) to real compliance situations
AI for Biotech & MedTech
This block builds practical AI fluency for the Biotech and MedTech sector, where AI touches drug discovery, target identification, clinical trial design, diagnostics, medical imaging, and manufacturing quality control.
31 lessons · about 6h
- Map the biotech and medtech value chain and locate where margin and power concentrate
- Identify major player types and analyze competitive and power dynamics across the chain
- Apply the key US and EU regulatory requirements (FDA, EMA, MDR) to real compliance situations
Biotech and MedTech turn science into products through long, risky development and hard regulatory gates. From the science-to-market path to device and drug approval, this vertical gives you the big picture, then finance, marketing, data and AI applied inside it.
Key terms
Why specialize in Biotech & MedTech?
Cross-cutting skills are not enough in the Biotech & MedTech sector. It plays by its own rules: a distinct value chain, specific players and balance of power, dense regulation, and key figures you won't find anywhere else. This vertical gives you that sector fluency: first the big picture, then finance, marketing, data and AI applied concretely to Biotech & MedTech, with the calculations, benchmarks and checklists you actually need on the ground.
What you'll be able to do
- Understand how the Biotech & MedTech sector works: value chain, key players and balance of power
- Know the major regulations and laws, the sector's acronyms and vocabulary
- Run the key calculations and read the benchmarks specific to Biotech & MedTech (US and Europe markets)
- Apply finance, marketing, data and AI to the realities of Biotech & MedTech
- Gauge your level with 5 sector assessments and a competency radar
70 lessons across 16 modules and 5 blocks, with a test per lens and a sector competency radar. Free to read, no account required.
The curriculum in detail
Biotech & MedTech: how the sector works
Generalhow biotech and medtech work: the science-to-market path, the difference between drugs and devices, regulatory approval (FDA/CE, 510(k)/PMA), and the role of evidence.
4 Modules · 18 Lessons
Finance in biotech and medtech
Financebiotech/medtech finance: burn rate and runway, milestone-based funding and partnerships, valuing pre-revenue pipelines, and reimbursement as the real gate.
3 Modules · 13 Lessons
Marketing in biotech and medtech
Marketingcommercializing devices and therapies: clinical evidence as the message, key opinion leaders and reference sites, payer and provider adoption, and regulated claims.
3 Modules · 13 Lessons
Data in biotech and medtech
DataR&D and clinical data, device telemetry and real-world performance, quality systems, and regulated data integrity.
3 Modules · 13 Lessons
AI in biotech and medtech
AIAI in biotech/medtech: discovery and design, diagnostics and imaging devices, and the validation/regulatory reality for AI-enabled products.
3 Modules · 13 Lessons
Prefer to place yourself first?
Five short assessments, one per domain of the Biotech & MedTech sector. Ten questions each, three minutes, and a competency radar once you have taken more than one.
All sector assessmentsLatest articles
What the blog publishes on Biotech & MedTech, across every discipline.
- FinancePharma partnership terms that protect your pipeline when the science goes sidewaysMilestone-based deals are how most biotech companies survive long enough to see their drug approved, but poorly structured agreements can leave a CFO holding the downside while the partner captures the upside. This playbook shows how to build deal terms that align incentives across a decade-long development arc.
- DataOne HCP, six records: why identity resolution is pharma's most expensive data problemA single cardiologist can exist as six different entities across a pharma company's CRM, claims data, and prescriber analytics systems, and none of them match. Until identity resolution works in practice, every downstream decision, from sampling allocations to pharmacovigilance reporting, is built on a fractured foundation.
- FinanceRisk-adjusted NPV for pre-revenue biotech pipelines: how the math actually worksMost valuation frameworks break down when applied to a drug candidate that has never generated a dollar of revenue and may never reach patients. Risk-adjusted NPV fixes that problem, but only if you understand what the model is actually doing and where it quietly fails.
- DataGxP integrity, 21 CFR Part 11, and GDPR: what happens when three regulatory regimes collidePharma CDOs operate at the intersection of three distinct regulatory systems, each with its own logic, its own enforcement body, and its own definition of what a data record actually is. Understanding where those systems conflict, not just where they overlap, is the difference between audit readiness and a consent notice architecture that accidentally destroys your audit trail.
Frequently asked questions
What does the Biotech & MedTech track actually cover?
It covers how biotech and medical-device companies work, then the four functions that run them: finance, marketing, data and AI. Five blocks in total, starting with the science-to-market path and regulatory approval, then one block per lens. The aim is to understand the sector's economics and constraints, not to train you as a scientist.
Do I need a scientific background to follow it?
No. The Biotech & MedTech content is written for executives, investors and operators who have to make decisions about products they did not invent. Scientific concepts are explained only to the depth needed to understand approval paths, evidence requirements and funding milestones.
Where should I start if I've just joined a medtech company?
Start with the sector block on how biotech and medtech work: the science-to-market path, the difference between drugs and devices, FDA/CE approval, 510(k) versus PMA, and the role of clinical evidence. Without that base, the finance and marketing blocks won't make sense, because both are driven by regulatory timing.
What's the difference between a drug and a medical device from a business standpoint?
They follow different approval routes, different timelines and different revenue models. Drugs go through clinical phases and long exclusivity built on patents; devices often move faster through pathways like the 510(k), face iterative product versions, and depend heavily on provider adoption. The Biotech & MedTech sector block treats both paths side by side.
How do you value a company with no revenue?
By its pipeline, its milestones and the cash it has left. The finance block on biotech and medtech covers burn rate and runway, milestone-based funding and partnerships, and how pre-revenue pipelines are valued against probability of success at each regulatory stage.
Why is reimbursement treated as more important than approval?
Because approval lets you sell, reimbursement decides whether anyone buys. A product cleared by the FDA or CE-marked but not covered by payers has no viable market, which is why the Biotech & MedTech finance block frames reimbursement as the real commercial gate.
How does marketing work when your claims are regulated?
Clinical evidence becomes the message, since you can only claim what your data and your label support. The marketing block on biotech and medtech covers how key opinion leaders and reference sites build credibility, how payer and provider adoption works, and where the limits on regulated claims sit.
What's specific about AI products in this sector compared to other industries?
An AI-enabled diagnostic or imaging device is a regulated product, so it needs clinical validation and an approval pathway before it reaches patients, and changes to the model raise the question of revalidation. The AI block on biotech and medtech covers discovery and molecular design, diagnostics and imaging, and this validation reality, alongside the data block on regulated data integrity and quality systems.