Our mission:

dramatically change the way large-scale biological and medical data are analyzed for more efficient drug development and personalized medicine

Welcome to Pharmatics, a new startup company founded by scientists from the University of Edinburgh.

Our goal is to speed up the process of drug development, from early-stage drug discovery to bringing new drugs to market more efficiently.

We are developing software products based on probabilistic machine learning and high-dimensional statistics for validating phenotypic biomarkers as surrogate end-points for shortening clinical trials. Our tools may also be used for uncovering novel unconfounded biological pathways.

We are also developing products for personalized health risk predictions from high-dimensional data that overcome key limitations of existing methods.

Research

Pharmatics is exploring the problems of:

causal discovery: inference of the direction of causation between biomarkers and complex traits (disease outcomes)

learning network structures: inference of complex dependencies between multiple markers, disease outcomes, treatments, and adverse effects from high-dimensional data with hidden variables

predictive inference: personalized predictions of health risks and adverse reactions for subgroups of patients automatically determined from high-dimensional observational data

Products

A major issue in biomedical research is the lack of intelligent methods to interpret data from clinical trials. Pharmatics is developing pioneering products and services that can help to find useful structure in such data by exploiting cutting-edge advances in probabilistic machine learning and systems biology.

The key feature of our products is that wherever possible, the measurements are analyzed jointly rather than independently of each other, with mathematical models substituting the unobserved or unmeasured factors.

OUR PRODUCTS: intelligent software and services for accelerating drug development, from discovering novel predictive biomarkers to bringing new drugs to market more efficiently

OUR METHODS: based on cutting-edge machine learning techniques for analyzing high-dimensional, incomplete, noisy biological and medical data

OUR KEY APPLICATIONS: discovery and validation of causal pathways , prediction of in vivo toxicity, prediction of health risks and individual response to treatment

Company concept

Modern drug development techniques create vast arrays of biological data that need to be analyzed to speed up the discovery and testing of new drugs. Researchers and pharmaceutical companies want to identify which parts of these data arrays are of interest to their target conditions in order to analyze this data rapidly and effectively.

Pharmatics is a startup company aiming to change the way large-scale biological and medical data are analyzed. We provide intelligent software and services to uncover useful structure in complex and incomplete biological measurements.

Pharmatics is developing tools which will help to discover causal biomarkers, focus clinical trials, and accelerate drug development by exploiting genotypic variation. We are also developing intelligent software which will help to predict drug response for varying patient groups from very large arrays of -omics data. By applying cutting edge machine learning techniques, we reduce very complex data to manageable combinations of the most promising factors.