Neither Should Your Research
TemporalBio is the first comprehensive operating system for time-aware biology. Our framework transforms how researchers design studies, analyze data, and understand biological systems across seven interconnected temporal scales.
Why do clinical trials fail despite promising preclinical data? The answer often lies in temporal misalignment.
Traditional research treats time as a simple axis on a graph. But biological systems operate across multiple, interconnected temporal scales—from milliseconds to years. When we design studies that miss critical temporal windows or fail to account for how processes at different time scales influence each other, we lose crucial insights.
TemporalBio provides a systematic framework for designing temporally-aware studies, a diagnostic tool (TRS Agent) that scores your study's temporal coverage, and a growing toolkit of methods for analyzing time-aware data.
A comprehensive classification system defining seven distinct temporal scales in biology, from molecular events (T0: milliseconds) to evolutionary processes (T6: millions of years). Each scale has distinct dynamics, measurement requirements, and causal relationships.
Explore Framework →An AI-powered diagnostic tool that evaluates your study design across temporal scales. Get a Temporal Resolution Score (TRS), identify missing time windows, and receive specific recommendations for improving your protocol.
Try Agent →Practical methods and tools for temporal analysis: dynamic time warping for aligning patient trajectories, wavelet analysis for multi-scale patterns, and causal inference frameworks that respect temporal ordering.
View Resources →Optimize checkpoint inhibitor studies by capturing T1 immune activation, T2 tumor response, and T3 durable response windows.
Identify early predictive markers by understanding how T0-T1 molecular events cascade into T2-T3 clinical outcomes.
Design GLP-1 studies that capture immediate effects (T0), short-term weight loss (T2), and long-term cardiovascular benefits (T4).
Map Alzheimer's progression from molecular dysfunction (T1) through synaptic loss (T2) to cognitive decline (T3).
Identify patient subgroups based on temporal response patterns to heart failure treatments across multiple time scales.
Combine multi-omic data across time scales to build predictive models of disease progression and treatment response.
Start with our framework guide to understand temporal scales, then use the TRS Agent to evaluate and optimize your study design.