Vevo Therapeutics utilizes its Mosaic platform to generate scalable, high-resolution in vivo data, enabling the analysis of drug effects on patient cells at single-cell resolution. This approach addresses the limitations of traditional in vitro models by capturing patient diversity and uncovering novel drug targets and mechanisms of action that are often undetectable in existing drug discovery methods.
Funding
$50M 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
Traditional drug discovery relies heavily on *in vitro* models that often fail to accurately represent the complexity of *in vivo* conditions and patient diversity. This can lead to the identification of drug targets and mechanisms of action that are not effective or relevant in living organisms, resulting in high failure rates in clinical trials.
Solution
Vevo Therapeutics is developing the Mosaic platform to generate scalable, high-resolution *in vivo* data, enabling a more accurate and comprehensive analysis of drug effects on patient cells. By leveraging proprietary methods for pooling cells from multiple patients in a single experiment and single-cell RNA sequencing, Mosaic captures drug action across a diverse patient population. This *in vivo* approach uncovers previously undetectable mechanisms of action and resistance, leading to the identification of novel drug targets and drug candidates that are more likely to succeed in clinical development. AI models are trained on the *in vivo* atlas to capture the diversity of patients and uncover novel targets and drug candidates.
Target Audience
Vevo Therapeutics' primary customers are pharmaceutical and biotechnology companies seeking to improve their drug discovery process by leveraging high-resolution *in vivo* data and AI-driven insights to identify more effective drug candidates.
Features
- Scalable *in vivo* data generation with single-cell resolution, measuring both phenotypic and transcriptomic changes in cell states
- Ability to pool cells from tens to hundreds of diverse patients in one experiment, capturing patient diversity in drug response
- Identification of novel drug targets and mechanisms of action undetectable by traditional *in vitro* models
- AI models trained on the *in vivo* atlas to capture the diversity of patients