The expectation of the R&D computing environment is much diversified. The growth of machine learning and AI convolutes the requirements of computing ecosystem. An uncomplicated, user-friendly computing environment is highly desired with burst computing capacity and robust tools. The infrastructure design needs to address the challenge of distributed enterprise data gravity in a cost-effective way. Here introduces the build of IT infrastructure leveraging the cloud to meet these demands in the pharm R&D field.

In today's fast-paced biotech industry, start-ups need to be able to quickly and securely access the computing resources they need to drive innovation and growth. In this session, we will discuss how to build an AWS cloud landing zone that meets the unique needs of biotech startups. We will cover topics such as designing a multi-account architecture, implementing identity and access management, and deploying security controls and monitoring. By the end of the session, attendees will have a better understanding of how to create a reliable and flexible cloud environment that supports the growth and compliance requirements of their start-ups.

Janssen has leveraged cloud capabilities to implement an ecosystem of platforms and solutions to manage the ever-increasing volume and variety of data and advanced analytical methodologies needed to innovate for our patients. The design offers a community approach, which helps our data scientists learn the latest and greatest techniques from each other and leverage each other’s work. Hence accelerates research and encourages innovation. The flexible and scalable design has resulted in impactful deliverables including AI/ML-driven drug discovery, clinical trial design & clinical operations, and real-world evidence.

PRINCE is Bayer Pharma’s one-stop shop for all preclinical data. Based on AWS infrastructure the system is being developed for intense user interaction while processing, analyzing, and visualizing data. Regular use case sessions with Early Development users are the basis for selecting and prioritizing new product features which are implemented based on an agile development concept. The talk will provide an overview of Bayer’s Cloud transformation journey and introduce selected product features. Some of these features are a role-based access concept, connectivity to secret data sources, chemical structure search using an interactive editor, and integration of ontologies.

This talk will provide some balance to the abundance of cloud adoption success stories. We’ll explore real-world examples from start-ups and big pharma of things that didn’t go quite as expected. Some stories may be familiar, some not, but they all contribute to our understanding of how life science organizations can make best use of the cloud. The experiences presented are with AWS but generalizable to other cloud providers.

Life sciences research environments are rapidly evolving to incorporate increasingly diverse cloud storage and computing resources. Using these multi-cloud environments efficiently requires researchers to integrate multiple components and become familiar with their unique access methods. We present a platform that unifies access to diverse storage and compute resources, both cloud-hosted and on premises, and demonstrate how familiar interfaces allow users to focus on their research and not on technology management.

Manually copying and pasting queries from the Safety systems into various study-specific EDC interfaces is an extremely laborious and error-prone swivel chair exercise. Using Robotic Process Automation (RPA), we have automated the process, removed the swivel chairs, and improved compliance and accuracy of Safety query management while saving significant amount of manual effort.

Tessera Therapeutics is a cloud-native biotech, with a computational strategy at the core of its scientific platform. As the company grows, its digital environment needs to scale and support the increasing computational demand while providing better operational stability, security, and mature toward compliance with industry standards. This session will cover the buildup of the data science platform: how the cloud environment enabled velocity, collaboration, scale, and maturity.