💜pivot game -> biotech investors, serial entrep (beachhead's customer)

[hyunjimoon]

• david saul working in gene therapeutics and have goals to start his own startup
• my WT mate

	Parameter	Hypothesis on Time to Change Market Segment (T2CD) w.r.t. Parameter = $\frac{\text{Time to change implemented desirability}}{\text{Time to change implemented feasibility}}$	Example in Biotech
within one row, across columns	DB: Diffuseness of prior belief	Hypothesis DB2T2CD: The more diffuse the prior belief on the segment (i.e., higher uncertainty), the longer the startup will stick with the chosen market segment before pivoting. Rationale: With higher uncertainty, the startup will require more experiments to reduce the uncertainty and make a confident decision about pivoting.	A biotech startup focusing on developing a novel gene therapy for a rare genetic disorder may stick with this market segment longer if there is high uncertainty about the therapy's efficacy and market potential. They may conduct more preclinical and clinical trials to gather evidence and reduce uncertainty before considering a pivot to a different therapeutic area or indication.
	DR: Market Stability	Hypothesis DR2T2CD: The more unstable the market is, the time to pivot would be longer as the startup needs to account for noise in the data generating process. Rationale: In a stable market, the deterministic mapping allows for quicker decision-making, while in an unstable market, the added noise requires more time to gather accurate information.	In an unstable market, such as during a global pandemic or significant regulatory changes, a biotech startup developing a COVID-19 vaccine may take longer to pivot to a different product or market segment. The instability in the market may require the startup to gather more data, assess the changing landscape, and adapt their strategies before making a pivoting decision. In contrast, in a stable market, the startup may be able to make quicker decisions based on clear market signals and trends.
	SR: Size of market segment	Hypothesis SR2T2CD: Time to pivot would be longer if in a bigger market. Rationale: - higher expected revenue (expected future revenue is higher for a bigger market) - lower cost (cheaper to get bigger sample from a bigger market) N is the number of customer a startup can get from unit cost of experiment	A biotech startup targeting a large market segment, such as developing a novel cancer immunotherapy, may take longer to pivot compared to a startup focusing on a smaller market segment, like a rare disease. The larger market size offers higher potential revenues and allows for larger sample sizes in clinical trials, which may encourage the startup to persist longer in this segment before considering a pivot.
across rows and columns	BR: belief and real gap	Hypothesis BR2T2CD: The larger the gap between belief and real market conditions, the longer the time to pivot. Rationale: When there is a significant discrepancy between the startup's beliefs and the actual market conditions, it may take longer for the startup to gather enough evidence to challenge their assumptions and make the decision to pivot. The larger the gap, the more experiments and data points are needed to bridge the difference and trigger a pivot.	A biotech startup may initially believe that there is a high demand for a new type of antibody-drug conjugate (ADC) for treating solid tumors. However, if the actual market demand is lower than expected or if the development of the ADC faces unexpected scientific challenges, there will be a gap between the startup's beliefs and reality. In this case, the startup may need more time and experiments to validate their assumptions, potentially leading to a longer time to pivot to a different approach or market segment.
	ER: Experiment opportunity (function of capital)	Hypothesis ER2T2CD: Higher capital would allow the startup to have patience and wait until its experiment passes the threshold. Rationale: With more capital, the startup can afford to conduct more experiments and gather more evidence before making a pivoting decision.	A well-funded biotech startup with a large capital base may have the resources to conduct more extensive preclinical and clinical trials for their lead drug candidate. This financial cushion allows them to gather more comprehensive data before deciding whether to pivot to a different drug candidate or therapeutic area. In contrast, a startup with limited capital may need to make pivoting decisions earlier based on a smaller set of experimental results.
	CT: Lower capital threshold before pivot market segment	Hypothesis CT2T2CD:** A higher capital threshold before pivoting to a new market segment will lead to a shorter time to pivot." Rationale: With a higher capital threshold, the startup will be more impatient and less tolerant of the current market segment's performance. They will pivot faster to a new segment when the current segment fails to meet the higher capital threshold. This aligns with the idea that startups with higher expectations and lower patience are more likely to pivot quickly.	A biotech startup with a high capital threshold (e.g., requiring a high return on investment or a large market size) may have a shorter time to pivot if their current market segment fails to meet these expectations. For example, if a startup is developing a cell therapy for a specific cancer indication but the early clinical trial results do not show a significant improvement over existing treatments, the startup may quickly pivot to a different cancer type or therapeutic modality to meet their high capital threshold and maintain the interest of their investors.
note		- Pivot is changing target desirability or feasibility during nail phase - Feasibility distribution is fixed to Logistic(0, 1) - Time to pivot implemented feasibility is uniformized to 1

[hyunjimoon]

이성환 이사님
small molecule (product 70%을 big pharma가 유리 -> large molecule; 신약 70%가 스타트업; new scientific approach (complexity: chemistry < biology) 30만/40만불; 대장균 생산, 퀄리티 냉동해야함)

bio sec act (manufacture) / vaccine supply chain (화합물: 인도, 중국 / 생물: 셀트리온+삼성바이오스텍)

카이스트 김원중 (삼성 경영 연구소 부원장; 페이퍼 science 신약 성공확률)

product-market fit (약 component 다양, delivery platform; lnp (rna, crisp, adeno associated virus); cell (망가진 세포 복원 - 물리/화학적), gene, 키투르바, 혈액암 타겟 -> 폐암, 간암;

Q. product-market fit 라는

• 15년 간 $2B; 임상3상, sponsor있어야; B형간염 치료제 - 완치되버리면 마켓이 작아짐 (길리어드; stfarm))

Q. 피벗의 빈도 비교:
폐암만 타겟하려했는데 (면역항암제; 요격미사일 (antibody drug conjugate; 항체 (폐암근처)))
탈모약 (전립선 치료제), gnp1(당뇨치료제), 간암(폐암)
플랫폼 회사: adc, nlp, aav

항생제 (인류가 개발한 마지막 항생제 25년 전; 제약회사가 개발안함; price driven)
똑똑한 사람 -> 새로운 아이디어 막 나옴
small molecule (65%) > biotech

3. 시장 정보로 인한 기술 피벗:

• rare disease (유전병)뜨고 있음 (임상 많이 안해도 되고, 긴 독점기간)
• 동물실험 없이 승인된 케이스 (동물 권리 -> 스타트업 아이디어; 랩스 on the chip; organoid; 동물 실험 (10,100배 비싸짐), 정확성 높아지)

5. 정보원

• 암: asco (poster 대표기술 뉴트랜드; 항암제 경쟁사 (데이터 어떻게 나옴; 효용성 20% 높음); 12년 전 간암치료 12억불, https://www.sec.gov/edgar/browse/?CIK=875045&owner=exclude)
• 헤지펀드 (public fund); https://www.google.com/search?q=edgar+crawling+public+fund+
• market: end point news (twitter) - nature/cell/science (monthly) 저널 (어떤 딜이 있었는지; pharmavoice https://www.pharmavoice.com/) 주요논문 (뉴스)
• https://www.biocentury.com/analysis/podcasts-webcasts-webinars (youtube)

dominant 약과 combination 시 효과 (키트루다 병용), 칵테일

[hyunjimoon]

June 12th
Christine Hsieh

I need feedback (e.g. biotech's usecase, source of data) on the project below:

To help biotech operations, I developed pivot game/flight simulator (https://www.youtube.com/watch?v=L1GlDGN8nEo&ab_channel=AngieMoon%F0%9F%8C%99).

During summer, i wish to add an ai module that understand the world (https://www.youtube.com/watch?v=8j2S7BRRWus&ab_channel=TEDxTalks) using probabilistic programming.