Newsletter | October 13, 2022

10.13.22 -- Unlock Scientific Innovation With AI And Machine Learning

Importance Of Integrated Informatics For Life Science Organizations

While the implementation of electronic systems led to reduced cycle times and compliance risk, issues remain with systems existing in departmental silos and nonstandardization of data across the drug development continuum. Read how an integrated informatics solution enables the standardization of data and technology transfer across the entire pharma product life cycle.

Implementing A Unified Lab Management Solution

A biotech company managing several different LIMS and ELN systems needed to unify data collection and management across the different phases of early discovery, R&D, and clinical and commercial manufacturing. By implementing a holistic, unified lab management solution, the company saw increased workflow efficiency, better data quality, and improved decision-making.

Smart Data For Smart Decisions

People in science-driven companies make decisions constantly — from routine day-to-day choices to strategic decisions that may affect the direction of the entire business. With so much at stake, how do company leaders ensure the right decisions are made? Learn how quality of data directly impacts decision-making efforts.

BioPharma Expands 3D Structure Portal

This research-based biopharmaceutical company's R&D team needed a comprehensive and sustainable 3D structure portal that would help to advance and accelerate their growing pipeline of investigational compounds. Discover the competitive advantage that helped close their communication gap between medicinal chemists and modelers.

Creating A Scalable Data Science Framework

While there's a strong desire to improve R&D efficiency and productivity to lower costs and shorten time-to-market, traditional approaches are reaching their natural limit. New methodologies are needed to shake up industry and drive future success.

The Case For AI And Machine Learning In Life Sciences

Unlocking the potential of AI and machine learning can help companies improve productivity, reduce costs, and generate actionable insight. Explore how AI is helping organizations tackle some of their largest challenges in product R&D, as well as build and utilize a scalable data science framework.