Gero develops therapeutics by applying physics-informed AI models trained on extensive longitudinal patient data to understand the root causes of aging. This platform distinguishes between irreversible aging and reversible disease processes to pinpoint targets that restore systemic resilience. The company focuses on designing interventions that delay age-related diseases and extend healthy human lifespan.
Funding
$8.2M 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
The development of effective therapeutics for chronic, age-related diseases is hindered by the complexity of aging and the difficulty in identifying the root causes of these diseases. Traditional drug discovery methods often fail to address the underlying mechanisms of aging, leading to limited success in treating these conditions.
Solution
Gero leverages physics-based Large Health Models (LHMs) and unsupervised training methods to analyze longitudinal human data and predict future health outcomes, akin to Large Language Models. Unlike LLMs, LHMs are physics-based and interpretable, revealing potential treatments for chronic age-related diseases and enabling patient stratification. By integrating genetics with LHMs, Gero aims to identify novel drug targets and develop therapeutics that address the root causes of aging and age-related diseases. The company collaborates with leading global institutions to validate its findings and develop new therapies.
Target Audience
The primary target audience includes pharmaceutical companies seeking novel drugs targeting age-related diseases, as well as researchers and clinicians focused on understanding and treating chronic diseases and aging.
Features
- Physics-based Large Health Models (LHMs) for analyzing longitudinal human data
- Unsupervised training methods to predict future health outcomes
- Integration of genetics with LHMs to identify novel drug targets
- Identification of new means of patient stratification
- Collaboration with leading global institutions for research and development