ModernVivo provides a comprehensive software environment that enables researchers to design in vivo experiments with precision and efficiency. By integrating advanced literature review tools with AI-driven analytics, ModernVivo helps researchers identify study parameters that align with both established practices and emerging methodologies.
Researchers can streamline the process of study planning by accessing curated insights on endpoints, assays, housing conditions, treatment dosages, scheduling, species selection, strain choice, bedding material, light cycles, noise levels, ventilation, controls, duration, monitoring characteristics, and routes of administration. This integrated knowledge base reduces the time required for literature reviews from months to a single day, allowing researchers to rapidly progress from hypothesis to experiment.
The platform supports evidence-based decision making by drawing on a wide range of published data and delivering context-specific recommendations. With ModernVivo, experimental design becomes not only more efficient but also more reproducible and aligned with best practices across the scientific community.
GeneScreen, the next addition to the ModernVivo toolkit, focuses on one of the most critical aspects of in vivo research: selecting the appropriate genetic model. By analyzing thousands of published studies, GeneScreen identifies the most consistent models for specific research questions. Researchers gain access to detailed summaries that describe genetic modifications, their phenotypic effects, and their influence on experimental outcomes.
This functionality enables investigators to make informed choices about model selection, ensuring that genetic variability and its implications are clearly understood during study planning. GeneScreen is currently available by waitlist, and researchers are invited to register their interest in gaining early access.
ModernVivo and GeneScreen together establish a modernized toolkit for in vivo research. They support scientists in designing experiments that are efficient, reproducible, and aligned with the latest validated methodologies. With these platforms, researchers can confidently move from concept to experiment with a higher degree of clarity and precision.
