Curriculum
Module 01 · 30 min
Why Pathways Matter
Why every clinician and researcher should think in pathways, not isolated molecules.
CoreClinicalResearch
Topics
What this module covers
- 01Reductionism vs systems biology
- 02Why one drug, many effects
- 03Pathways as the language of disease
- 04How this course is organized
Deep-dive lessons
Open a lesson to study a concept
Learning objectives
By the end of this module you will be able to
- L01Explain why a pathway-level view predicts drug effects better than a single-target view.
- L02Place metabolic, signaling, and genetic pathways on a shared map.
- L03Identify three clinical decisions that change when you reason at pathway level.
Expected takeaways
What you should walk away believing
- →Most drugs hit a node in a network — the network determines the response.
- →Disease phenotypes emerge from pathway dysregulation, not single mutations alone.
- →Pathway thinking transfers across cancer, metabolism, immunity, and neurology.
Core summary
At the Core level
Pathways are the wiring diagrams of cells. Knowing how molecules connect explains why one drug helps one patient and harms another, and why two diseases that look unrelated may share a circuit.
Myth vs reality
Common misconception
Claim
If a drug hits one target, it has one effect.
Reality
Targets sit in pathways with crosstalk. Off-target effects, bypass signaling, and feedback loops mean a clean target rarely produces a clean phenotype.
Evidence-graded claims
Claims, scored A–F
B
Pathway-level reasoning predicts combination-therapy synergy better than target-level reasoning
Supported by network-medicine literature.
F
All cancers can be cured by hitting one pathway
Resistance via bypass and crosstalk is the rule.
E
Pathway databases are complete
Coverage varies by organism and pathway type; gaps are systematic.
Quiz
Check your understanding
Q1. Why do MEK inhibitors cause skin rashes?
Q2. Which best defines a 'pathway'?
Flashcards
Lock it in
1 / 3
Front
Define 'pathway' in one sentence.
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Suggested reading
Primary literature
- Network medicine: a network-based approach to human disease — Barabási et al., Nat Rev Genet 2011 ↗