Evaluating vast search spaces with small data AI and experimentally derived datasets

The Optim.AI™ platform is disease-agnostic and can be applied across a spectrum of biological models to help provide scientists and healthcare professionals with the ability to efficiently evaluate large combinatorial search spaces without traditional limitations.

Since we do not use high throughput screening or require vast amounts of external data, our technology is versatile and can be used from preclinical drug development through clinical trials, and for clinical decision support.

KYAN Technologies, a pioneering leader in the field of functional precision medicine for oncology. Our company is dedicated to revolutionizing cancer care by leveraging cutting-edge technology and expertise.

Input Data

Our data comes from designed experiments that are carried out on minimal amounts of the chosen biological model. This enables the generation of maximal insights even when using models that are more relevant but limited in amount such as patient samples or organoids. Our proprietary Optim.AI™ arrays are also designed so that our data properly fits the computational analysis for accurate results.


The core of Optim.AI™ utilizes small data AI to expand the universe of each phenotypic response dataset to solve for every possible combinatory outcome. This is a key benefit as we are not forced to pre-select a limited number of combinations within a drug panel for evaluation
and we eliminate potential holes of knowledge.


Optim.AI™ results include all predicted drug-drug interactions which can represented by a 3D parabolic response map that indicates an optimum
with 2 drugs. Rather than providing a binary YES/NO output, Optim.AI™ ranks all outcomes by an assigned normalized cell viability value so that
relative efficacy and ranges of likely sensitivity and resistance can be gauged.