Project Overview:
The field of longevity research is rapidly advancing, with numerous potential interventions being proposed to extend healthspan and lifespan. However, evaluating the effectiveness of these interventions remains a time-consuming and resource-intensive process. In addition, the traditional model of scientific research often lacks collaboration and accessibility for a wider audience, limiting the potential for collective wisdom to drive breakthroughs in this field.

Problem Statement:
The primary challenge is to accelerate the evaluation of novel aging interventions and foster collaboration among researchers, data scientists, and enthusiasts. This would enable the scientific community to prioritize research efforts, allocate resources efficiently, and harness diverse perspectives to advance our understanding of aging-related processes.

Solution:
Our project, LabPredict, is a prediction market platform designed to make longevity research engaging, accessible, and collaborative. By focusing on surrogate model organisms with relatively short lifespans, LabPredict enables participants to make predictions on aging research experiments based on published scientific findings, evaluate studies, and place predictions on third-party validated experiments. Accurate predictions are rewarded, promoting active participation and knowledge contribution.

Roadmap:
1. Development Phase (2 months): Design and build the LabPredict platform, incorporating a user-friendly interface, dynamic market structure, and blockchain technology for transparency and security.
2. Beta Testing Phase (1 months): Invite a select group of users to test the platform, provide feedback, and refine the user experience based on their input.
3. Launch Phase (1 month): Officially launch LabPredict, inviting researchers, data scientists, and aging enthusiasts to participate in the prediction market.
4. Expansion Phase (2 months): Continuously improve the platform and increase user engagement through marketing efforts, collaborations with research institutions, and integration of new features based on user feedback.