About Us
Training the next generation of AI drug design with living data
Phase I clinical trial success rates have improved from ~50% to ~85% owing to advances in computational drug development tools.
Phase II clinical trial success rates have not improved substantially.
Most AI drug design platforms train with fundamentally limited and
biased data. Data that does not measure drug efficacy in a living system.
Azor Biotek's novel AI-guided drug design platform uses purpose built high throughput robotics to capture training data from live zebrafish, 3D-bioprinted human organoids, and xenograft models combining the two.
Fish with human livers and human tumours.
Such efficacy data is the only data type able to bring a drug to clinical use.
Screening zebrafish naturally selects for therapeutics with high bioactivity and allows for in vivo quantification of concrete physiological hallmarks such as neuroactivity, neuroplasticity and cardiograms.
These screens endogenously provide approximations of the effective dose, PK/Tox and off-target effects before molecular analysis such as our MALI-imaging based PK/PD.
See our background video on what makes zebrafish so amenable to high throughput drug screening. Compared to mice, evaluation is 1% the cost, 10% the time and noninvasive as they are transparent.
Don't look at dead cells when you can image living organs
