Inceptive utilizes large-scale deep learning to design RNA molecules that perform specific functions within biological systems. This approach enables the development of novel synthetic molecules for creating accessible medicines and biotechnologies that were previously unattainable.
Funding
$120M 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.
NFounders
Product
Problem
Traditional drug discovery and biotechnology development face limitations in designing RNA molecules with specific functions within biological systems, hindering the creation of novel medicines and biotechnologies. The complexity of RNA structure and function makes it difficult to engineer molecules that can effectively perform desired tasks in vivo.
Solution
Inceptive employs large-scale deep learning to overcome the challenges of RNA molecule design, enabling the creation of biological software—synthetic molecules that execute complex functions specified from a program within a biological system. This approach facilitates the development of accessible medicines and biotechnologies that were previously unattainable due to the limitations of traditional methods. By leveraging machine learning, Inceptive can design RNA molecules with greater precision and efficiency, opening new possibilities for therapeutic interventions and biotechnological applications.
Target Audience
The primary audience includes pharmaceutical companies, biotechnology firms, and research institutions seeking innovative solutions for drug discovery and development, as well as researchers interested in advancing the field of RNA-based technologies.
Features
- Large-scale deep learning models for RNA molecule design
- Development of synthetic molecules that execute complex functions
- Creation of biological software for novel medicines and biotechnologies