Ora Biomedical develops longevity and resilience-enhancing therapies by integrating high-throughput live animal screening with machine learning. The company utilizes the WormBot-AI platform, which combines robotics, computer vision, and deep learning for automated drug screening in live models. This intelligent automation allows for the discovery of therapeutic candidates by analyzing subtle biological effects and phenotypic changes at scale.
Funding
$720K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Aging is the primary risk factor for many chronic diseases, leading to a decline in healthspan and lifespan. Traditional drug discovery methods are slow and inefficient in identifying interventions that target the fundamental mechanisms of aging.
Solution
Ora Biomedical utilizes a high-throughput screening platform, WormBot-AI, to identify small molecule therapeutics that modulate the aging process and extend healthy lifespan. The platform combines automated robotics with AI-driven data analysis to screen interventions in _C. elegans_, measuring health and survival across numerous populations simultaneously. By focusing on evolutionarily conserved aging mechanisms, Ora Biomedical aims to discover broad-acting gerotherapeutics applicable to both age-related and rare diseases. These interventions are then validated in mammalian models, paving the way for clinical development and preventative medicine strategies.
Target Audience
Ora Biomedical partners with academic and commercial clients interested in evaluating novel therapies and accelerating their drug discovery pipeline.
Features
- WormBot-AI: A high-throughput robotics platform for preclinical drug screening in _C. elegans_.
- AI-based data analysis: State-of-the-art algorithms for measuring health and survival metrics.
- Small molecule and natural product analysis: Unbiased compound screening to identify novel interventions.
- Normative aging and disease models: Analysis of lifespan and healthspan measures, including age-associated movement and behavior changes.
- Mechanistic and translational validation studies: Characterization of drug targets using genetic, biochemical, and multi-omic approaches.