Life Sciences

Deep Insights That Power Innovation

From genomics and drug discovery to imaging and instruments, digital transformation is jumpstarting innovation. Enthought shapes how advanced tools and streamlined workflows can strengthen collaboration, leading to accelerated discovery and strategic business wins.

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Transforming Data, Accelerating Progress

Scientific data is complex, context-dependent, evolving and often scattered across an organization in different locations and formats. Enthought streamlines data ecosystems and accelerates workflows to yield objective, tested results and bring solutions to market faster, in a reproducible process that validates outcomes.

Whether it’s chemistry or biology, genetics or genomics, personalized medicine or DNA sequencing, our team’s deep knowledge of science enables us to deliver digital, scientific solutions. Over 90% of Enthought’s team have advanced science, engineering, and math degrees, and 65% hold PhDs.

Experts Who Understand

Enthought brings together life sciences expertise with computational excellence.

By leveraging the full affordances of digital technologies applied to a deep understanding of the scientific domain, we can expand the range of what’s possible and deliver holistic, integrated solutions to achieve better business outcomes.

 

Enthought | Powering Digital Transformation for Science
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The Challenges of Scaling Digital Advances in Life Sciences

Many of the improvements in life sciences R&D labs today come through introducing digital technologies to existing processes, with an evolution that provides measurable, incremental improvements. The real challenge for management is how to scale orders of magnitude R&D lab advances across the organization.

In this article, we explore the 10 key "battlegrounds" that represent significant opportunities for value creation within life sciences and explore why scientists must be equipped with the power of the rapidly advancing scientific software tools and techniques to conquer them.

10X Efficiency Gain and Improved Classification Using Deep Learning

Use AI techniques to efficiently extract mineralogy and grain size statistics from thin sections Thin sections provide the closest examination of in situ rock properties,…

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Integrating Weather and Renewable Energy Sources Data for 2.5 Million Viewers

Educating and developing a culture of responsible energy consumption The EnergizAIR project is presented both to show the innovative technology and methodology to solve the…

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Manual Processes for CSEM Replaced by Computational Tools and Strategies

Shell needed a way to effectively visualize a new scientific measurement Controlled-Source Electromagnetic sounding (CSEM) is a new tool for marine oil exploration. Sensitive electric…

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Predicting Pore Pressure From Very Limited Data Sets

ConocoPhilips wanted to make pore pressure predictions with limited data sets Logs from two wells and a limited set of 2D and 3D seismic were…

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AI/Machine Learning Techniques Quantify AVA Seismic Analysis Uncertainty

Help ConocoPhillips apply advanced AI techniques to Amplitude Versus Angle (AVA), seismic analysis Amplitude Versus Angle (AVA), seismic analysis is a well-established oil exploration tool….

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Model-Based Approach to Rock Physics Improves Predictions

ConocoPhillips wanted a more flexible way to model rock physics An important activity in characterizing reservoirs  is constructing models of rock physics, which represent how…

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Applying Machine Learning to Subsurface Data Reduces Uncertainty

Overcome slow and tedious nature of core analysis Core analysis provides ground truth data of rock properties, and can be time consuming and expensive to…

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Digital Transformation in Practice

For digital leaders who will share a practical framework for digital transformation options, and how to avoid common pitfalls. Gain insights into: Making key strategic…

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Get More From Your Core

What: Presentation, demo, and Q&A with Brendon Hall, Energy Solutions Group, Enthought Oil and gas industry professionals who are looking for ways to extract more…

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Accelerating Seismic Interpretation with Machine Learning

Determine if AI and machine learning techniques can be used to more efficiently analyze seismic volumes Seismic is the first field measurement in the oil…

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Robert Kern

Director, Algorithms and Machine Learning

Behzad Eftekhari

Consulting Manager

Aaron Ayres

Scientific Software Developer

Sai Rahul Poruri

Senior Scientific Software Developer

Sogo Shiozawa

Scientific Software Developer

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