[[09-24|25-09-24]] | Time Period | Mission Focus | Description | | ------------------ | ----------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | 2010 Founding | Broad mRNA Platform | Built an ambitious mRNA technology platform aiming to develop transformative medicines across multiple disease areas including cancer, infectious disease, rare diseases, and autoimmune disorders. | | 2013 - Early 2010s | Focus on Vaccines & Practical Goals | Pivoted to prioritize vaccine development for infectious diseases (e.g., flu, Zika) as more immediate and attainable targets to validate clinical potential. Secured key partnerships like AstraZeneca. | | 2016-2019 | Clinical Pipeline Expansion | Expanded pipeline with more mRNA therapeutic candidates in oncology, rare disease, and personalized cancer vaccines; became a clinical-stage company. | | 2020-2021 | COVID-19 Vaccine Emergency Focus | Rapid development and deployment of COVID-19 mRNA vaccine (mRNA-1273) demonstrating breakthrough speed and scale; Moderna became a major commercial vaccine company. | | 2022-Present | Diversification & Long-Term Growth | Post-pandemic strategy focuses on diversifying mRNA pipeline including RSV, flu, cancer vaccines, and rare diseases, while leveraging AI and digital innovation to accelerate drug discovery. | ### 2. **실제 사례: Moderna vs Theranos** **Moderna (τ 우선 전략)** - 초기 μ: "개인맞춤 암 백신" (과도한 목표) - 낮은 τ 유지: "pivot fearlessly" 문화 - 결과: mRNA 플랫폼으로 피벗 → COVID 백신 성공 **Theranos (μ 우선 전략)** - 완벽한 μ: "한 방울로 모든 검사" (기술적으로 명확) - 극단적 τ: 비밀주의, 피드백 차단 - 결과: 90억 달러 가치 → 0 - **"τ First, μ Second" 원칙** 1. 먼저 학습 능력 확보 (low τ) 2. 시장 피드백으로 목표 조정 (μ calibration) 3. 검증 후 precision 증가 (τ↑) **역순은 치명적**: - High τ → Low learning → μ 고착 → 실패 �� 비대칭성의 본질 ### 1. **정보 처리 계층** ``` τ = 정보 처리 능력 (HOW to learn) μ = 처리할 정보 내용 (WHAT to learn) HOW가 망가지면 WHAT은 무의미 HOW가 건전하면 WHAT은 교정 가능 ```