Biotech & Pharma

Bring the code of life to life.

Bring algorithmic decision-making to drug development, diagnostics, and clinical trials with a data science platform.

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Transform biotech and pharma with machine learning.

Data science is quickly becoming a game changer for the pharmaceutical and biotech industries. From drug discovery to getting the right treatments to the right patients at the right time, artificial intelligence is making medical research and treatment faster and more successful on a massive scale.

 

The DataScience.com Platform sets pharmaceutical and biotechnology firms up for success by simplifying the process of getting valuable predictions — such as the likeihood a patient will develop a condition based on his or her genetic information  off of a data scientist’s laptop and into the hands of doctors and clinical researchers. Predictive models can be built in a Jupyter, RStudio, or Zeppelin session in the platform, shared with teammates or decision makers in a report or project, and deployed as APIs for easy integration.

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A data science platform for biotechnology.

The DataScience.com Platform makes machine learning-powered biotechnology applications scalable with features that foster reproducibility and enhance security.

Stay compliant 

Easily manage project access and permissions. Track project changes with version control solutions like GitHub, Bitbucket, or GitLab.

Power applications

Deploy cancer detection or patient risk models as APIs for easy integration with diagnostic applications or other systems.

Support discovery

Get vital information to stakeholders, fast. Generate interactive reports from Markdown files or notebooks in one click.

DataScience Register

Accelerate healthcare innovation with a powerful data science platform.

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Using Data Science to Guide Drug Development and Predict Disease

Using Data Science to Guide Drug Development and Predict Disease

The Importance of Data Science in Biotech

The Importance of Data Science in Biotech

Assessing Evidence for Causality Using the E-Value

Assessing Evidence for Causality Using the E-Value

Q&A: Using Artificial Intelligence to Identify Genetic Variants

Q&A: Using Artificial Intelligence to Identify Genetic Variants