Our unique genetic algorithms harness the power of natural selection enhanced through deep learning neural networks. We use this proprietary process to create predictive analytic models that massively reduce research costs and speed time-to-market for early-stage drug discovery and pre-clinical studies.
We have a small but dynamic team of industry experts guiding our approach.
Team
Stephen Permison, MD
Chief Medical Officer
Alec Permison, MBA
Chief Executive Officer
Kenneth Rehm, DPM
Director of Research
Kimberly Baker
Support
FAQ
What is genalytics?
Genaltyics is the use of genetic algorithms for solving both constrained and unconstrained optimization problems based on natural selection, the process that drives biological evolution. A genetic algorithm repeatedly modifies a population of individual solutions.
What is unique about your process?
We have coupled genetic algorithms with the power of artificial intelligence machine-learning models. This allows us to investigate potential drug interactions ex situ, saving vast amounts of wasted research efforts and dollars before entering clinical trials.
What stage of research do you support?
Our model is optimized for early-stage drug discovery and pre-clinical studies. We build our machine-learning models by studying chemical properties of potentially active compounds and predicting in vitro performance.
What is your target market?
We are currently focused on the multi-billion dollar opportunity created by the diabetic pandemic and associated peripheral neuropathies. We are building predictive models to support drug discovery in this space.
