Biomedical Machine Learning Starts Here

BioSymetrics Artificial Intelligence software empowers healthcare and biomedical R&D innovation.

 

We created the first biomedical specific machine learning framework to increase precision, shorten timelines, and improve discovery.

The Augusta™ software platform significantly improves time-to-market and drives innovation.  Augusta Architect (v2.0) enables data scientists to automate the tasks of pre-processing and management of disparate data, with integrated analysis, feature engineering, and predictive modeling in a single, easy-to-use framework.

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Life science companies tend focus on machine learning, ignoring the impact of the decisions they made in collecting and processing their data.

BioSymetrics has built AugustaTM , a fundamentally different approach to Data Science, optimizing every step of the process

Pre-processing Artificial Intelligence

The result: less time spent in data processing, easier data integration, more accurate results for diagnostics and drug discovery, as well as truly autonomous capabilities for precision medicine

Drug

Discovery

& Research

Biopharma, Pharmaceutical, and CRO’s can rapidly leverage the power of AI and ML to enable lead compound discovery and trials.  Easy to deploy, the Augusta™ framework enables faster pre-processing and model interrogation.

Diagnostics &

Precision

Medicine

Utilize advanced artificial intelligence to classify subpopulations and tailor medical treatment to individual characteristics.  The Augusta™ platform analyzes and draws inferences from vast amounts of data points, improving quality of patient care, enabling cost-effectiveness, reducing readmissions and mortality rates.

Value

Based

Care

Hospitals, healthcare systems, and medical groups can improve institutional operations, finance and research programs.  Applying machine learning (ML) to EMR’s, billing, admissions, radiology, cardiology, neurology, oncology and obstetrics (to name a few).

Products

AugustaTM  is a biomedical Machine Learning (ML) framework designed to integrate data pre-processing into model building and interrogation.

Services

We offer turnkey services to our clients and corporate partners, with the aim of assisting organizations and teams in getting the greatest benefit from their data science initiatives. Our track record in massive data analytics including machine learning has been recognized with industry awards and conference speaking opportunities, and ties to our insight and knowledge base about the complexities in biomedical AI.

BioSymetrics services are available in several different ways, from our comprehensive technology solution implementations formalized in licensing agreements, to CRO consulting engagements and ad hoc projects.

Case Studies

“Augusta Architect is unique in its focus on efficient pre-processing, enabling more transparent model building in biomedicine. We’re excited to be users of the platform.”

Dr. Eric SchadtFounder and CEO, Sema4

“Augusta has supported us in a variety of projects in different settings. In health insurance, BioSymetrics saved us months of man hours and approximately $6.4 million (£5-million) annually … the use of Augusta enabled the company to drive faster, more accurate and meaningful innovation.”

Matt HickeyFounder and CEO, Intacare
Recent Blog Posts
February 12, 2020 in Blog Post, Case Study, Drug Discovery

De-noising CMap L1000 Data

As with any assay, L1000 data is noisy. Experimental replicates (the same compound tested on the same cell line under the same conditions) often result in different levels of expression…
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January 28, 2020 in Blog Post, Case Study, Drug Discovery

When are Two Compounds the Same?

When are two compounds the same? The effect of Simplified Molecular Input Line Entry System (SMILES) format on chemical database overlap including best practice for canonicalization and harmonization to understand…
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January 21, 2020 in Blog Post, Case Study, Drug Discovery

Dealing with Missing Values in Healthcare Data

In this post, we highlight the challenges of missing values when modelling with time-series data of EMRs and discuss some techniques to address it.
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January 10, 2020 in Case Study, Drug Discovery

Phenotype/Mechanism Prediction

Use Case: BioSymetrics ML framework generates structure-based activity predictions using phenotypic assays and HCS data to identify protein targets and affected pathways
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See all Blog and News Posts