ModernVivo
AI-powered software for preclinical in-vivo study design.
| Date | Investors | Amount | Round |
|---|---|---|---|
| investor | €0.0 | round | |
| investor | €0.0 | round | |
$15.0k | Convertible | ||
| Total Funding | 000k | ||
Related Content
ModernVivo is a Seattle-based software company developing an AI-enabled platform to optimize in-vivo experiments for drug development. Founded in 2023 by Colin Small and CEO Ian Levine, the startup addresses critical inefficiencies in preclinical research. Over 90% of novel drugs fail in human trials, often due to the poor predictive power of preclinical animal studies, which are designed using slow and manual literature review processes.
ModernVivo's platform leverages machine learning and natural language processing to analyze vast amounts of published research, helping scientists design superior preclinical in-vivo models. This data-driven approach accelerates experimental protocol development, reduces costs, and improves the likelihood of clinical success. The software distills key insights and experimental parameters from thousands of papers, allowing researchers to design studies in a fraction of the time compared to traditional methods. The company's mission is to enhance the success rate of new therapeutics and promote more ethical research by refining and reducing animal use.
The founding team possesses a strong background in biomedical research. Ian Levine holds a B.S. in Experimental Neuroscience from Virginia Tech and an M.S. in Pharmacology from the University of Michigan, with his academic career focused on therapeutic development and in-vivo study design.
ModernVivo serves pharmaceutical companies, contract research organizations (CROs), and academic institutions. Its business model consists of tailored software licenses. The company has received backing from investors including the University of Michigan, Debiopharm Innovation Fund, and Merck Digital Sciences Studio, having participated in the latter's accelerator program to advance its technology.
Keywords: preclinical research, in-vivo study design, AI drug discovery, pharmacology, biotechnology, animal models, translational success, clinical trials, experimental design, literature review, pharmaceutical software, contract research organizations, data-driven drug development, machine learning, natural language processing, therapeutic development, research automation