Overview
We use computerized DoE, executed through robotic media preparation, to test the entirety of a multidimensional factor space, then we use Multi-Variate Data Analysis (MVDA) to mathematically model the differentiation space and identify effector contributions, interaction terms, and definitions of optimal conditions for reaching specific cell fates.
The Trailhead Bio Difference
Traditional Black-Box Biology
Single factor optimization, highly iterative process
Experiments designed and limited by the human mind
Cell culture is done by hand and prone to error
Results are limited to the original design
Trailhead Systems Biology
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Efficient, multi-dimensional experiments
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Experiments are designed with proprietary mathematical software
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Robots perform precise, scalable experiments
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Design enables results to be used in virtual experiments
Our HD-DOE™ platform allows us to build protocols for making specialized human cells from iPSCs:
Built from Scratch
Built from Scratch
All protocols are based on unique stage-inducing media, not copied from literature or existing IP
QbD
QbD
All protocols adhere to a Quality-by-Design standard, for all stages
Data, Not Hypothesis, Driven
Data, Not Hypothesis, Driven
All protocols are based on empirical data obtained from using HD-DoE™
CPP
CPP
All protocol inputs are statistically qualified as Critical Process Parameters
Universality
Universality
Our protocols typically achieve consistent differentiation regardless of iPSC line/clonal origin
Validation
Validation
All protocols are validated through molecular and histological attributes that are respected and qualified by literature
CTAC
CTAC
All protocols are developed to maximize purity, seeking to attain Close-to-Absolute-Conversion to the desired fate
Mathematics: Meet Biology
We attain response modeling of key cellular parameters through large dimensioned experiments.
By developing machine-augmented scientific processes, we aim to generate novel data types and structures that are information-dense which can be used to attain control over the cell development process in order to build novel cell therapies.