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.
Our Life Sciences team has expertise in Foundation Models, Large Language Models (LLMs), Graph Neural Networks, Bayesian Optimization, Deep Learning, Generative Adversarial Networks (GANs), Natural Language Processing (NLP), Open Data, MD, DFT, Multi-scale Modeling, Mathematical Modeling, Molecular Representation, Cloud, Databases, Data Pipelines, Data Ops, ML Ops, Web and Desktop UI.
AI-Driven Drug Discovery & Development
Life sciences companies are investing heavily in artificial intelligence—and for good reason. Pharmaceutical and biopharma R&D labs that leverage AI and machine learning are accelerating discovery and getting to clinical trials faster. However, many companies today are still entrenched in traditional methods of scientific research. Enthought helps pharmaceutical companies and CROs of all sizes harness the power of scientific computing to expedite drug discovery and development, all centered around their unique IP.
Our Insights
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.
Industry Leaders Innovate with Enthought
Cheat Sheet | Large Language Models+ For Scientific Research
Large Language Models+ For Scientific Research Updated August 2023 LLMs and Tools for R&D To help scientists and researchers navigate the increasing number of advanced…
WEBINAR: What Every R&D Leader Needs to Know About ChatGPT and LLMs
View Webinar-on-Demand Live webinar held on June 27, 2023 Overview ChatGPT and the explosion of advanced Large Language Models (LLMs) are disrupting every industry. We…
Unlocking the Value of High Throughput Screening Pipelines in Small Molecule Drug Discovery
Transforming High Throughput Screening Data into Actionable Insights with Data Modeling and Visualization A mid-size small molecule cancer therapeutics biotechnology company using a custom high…
[eBook] Digital Transformation in the Life Sciences Industry
The Lab of the Future: Barriers to Digital Transformation in the Life Sciences Industry Experts predict over the next two years, life sciences companies will…
5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab
5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab Despite an increase in digital transformation efforts across all industries, 70% fall short…
[White Paper] Optimized Workflows in the Life Sciences
Optimized Workflows: Towards Reproducible, Extensible and Scalable Bioinformatics Pipelines A bioinformatics pipeline is an analysis workflow that takes input data files in unprocessed raw form…
3 ways to identify digital transformation opportunities in your R&D lab
Is your R&D lab digitally mature? Do you use data and code to create value at every step of your R&D program? This webinar will…
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…
Python for Professionals
What: Presentation and Q&A with Dr. Michael Connell, VP, Organizational Transformation, Enthought Who Should Watch: Anyone who wants to develop proficiency in Python for scientific, engineering,…
The Power of Automation
What: An introduction to the possibilities provided by automation in business and scientific workflows Who Should Watch: Scientists, engineers, and group leaders who have repetitive…