Team Activities

ACHIEVING PRODUCT-MARKET FIT THROUGH COMMUNITY PROJECTS​

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PROJECT SUMMARIES

 

A. Building relationship opportunities with biotechs, by consultants partnering with vendors

• Problem to be solved: Consultants in biotech often rely solely on their biological expertise to secure deals with companies. However, there is an opportunity to expand their scope by collaborating with vendors (e.g., AI and data solution providers). Building these partnerships can create value for both consultants and vendors by establishing relationships that can be leveraged for future opportunities.

• Deliverable: A best-in-class process for partnering/ networking and for building actionable relationships with biotechs.  With case examples.  With tips & tricks on how to get started.

Project lead: Nina Truter, nj.truter@gmail.com ​​

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B. A market penetration diagnostic tool (LLM-driven) to help vendors understand why they are struggling and to make actionable suggestions  -- UPDATE: see the free LeadgenAgent app for progress on this initiative.

• Problem to be solved: Many AI-focused consultants and vendors are challenged when monetizing their offerings in drug discovery.  There are numerous theories about this - from scientist skepticism, to failed drug discovery programs, to lack of vendor science skills. But no real market analysis has been done on this, including talking to suppliers and buyers.

• Deliverable: Diagnostic & suggestions app, with description detailing causes and ideas to breakthrough them.  With anecdotal data points.

Project lead: Raminderpal Singh, raminderpal@hitchhikersai.org 

C. Going from data to quality decisions, fast

• Problem to be solved: Drug discovery (pre-clinical) often involves generating large amounts of data, which must then be analyzed and interpreted to make decisions about how to proceed. When there are barriers between data generation, analysis, and interpretation, the decision cycle can be drastically slowed down. A variety of software tools address different bottlenecks, but new problems are introduced when teams try to integrate multiple solutions. This project will take a holistic view of how pre-clinical research teams can take advantage of their data to get to insights more quickly, and how vendors can establish interoperability across offerings.

• Deliverable: A flexible architecture of how best-in-class data tools will work together, with the goal of reducing decision cycle time from data generation to interpretation. Users should be able to select what they need based on their current systems. Vendors involved in the project should decide on interoperability standards.

Project lead: Eli Pollock, eli@ontologic.ly 

 

D. Helping scientists cost-effectively construct decisions from large sets of research papers

• Problem to be solved: There is a massive amount of research know-how in existence, but it is very expensive to buy / build systems to structurally extract value from it.  A “live” community-managed knowledge base, which scrapes large amounts of papers and turns them into a knowledge graph. 

• Deliverable: As a first instance, a community managed knowledge graph extracted from medical literature. Consultants and domain experts in HHAI will work to extract valuable information and use-cases.

Project lead: Andre Franca, andre@ergodic.ai  

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How to learn more or participate?  The simplest way is to sign up below and join the community.  Also, if you have any questions and/or ideas, feel free to reach out to Raminderpal (raminderpal@hitchhikersai.org).