Applicable Industries
- Pharmaceuticals
Use Cases
- Time Sensitive Networking
- Track & Trace of Assets
Services
- Cloud Planning, Design & Implementation Services
About The Customer
Lilly is a global healthcare leader that combines caring with discovery to create medicines that improve people's lives worldwide. The company was founded in 1876 by a man committed to creating high-quality medicines that met real needs. Lilly employees work globally to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to communities through philanthropy and volunteerism.
The Challenge
Lilly, a global healthcare leader, faced significant challenges in operationalizing data insights on clinical trials and setting up web-based dashboards to track progress. The team needed to accurately monitor, plan, and forecast patient status across all phases of clinical trials. This required understanding how patients were enrolled in trials and tracking their status over time. Lilly had complex manual processes in place using SQL, MS Access, and XLS to integrate 20 different data sets in S3 for a single study. They were manually executing SQL queries eight times a day to update reports and dashboards. However, these processes were siloed, leading to minimal collaboration. The challenge was to streamline and automate data flows downstream to enable business analysts, while controlling costs and efficiencies across all clinical sites.
The Solution
Lilly leveraged EMR, Amazon S3, and Amazon Redshift for storage and processing to solve this problem. They were able to collect and transform the data with reference data libraries, eliminating redundant data cleansing efforts. This improved data accuracy, eliminated manual data edits, and accelerated development. Designer Cloud enabled business analysts to perform their own aggregations, pivots, max date, and window functions, eliminating dependency on IT to curate data. As a result, Lilly can now track drug efficacy milestones throughout studies to ensure therapeutics are successful.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Case Study: Pfizer
Pfizer’s high-performance computing software and systems for worldwide research and development support large-scale data analysis, research projects, clinical analytics, and modeling. Pfizer’s computing services are used across the spectrum of research and development efforts, from the deep biological understanding of disease to the design of safe, efficacious therapeutic agents.
Case Study
Fusion Middleware Integration on Cloud for Pharma Major
Customer wanted a real-time, seamless, cloud based integration between the existing on premise and cloud based application using SOA technology on Oracle Fusion Middleware Platform, a Contingent Worker Solution to collect, track, manage and report information for on-boarding, maintenance and off-boarding of contingent workers using a streamlined and Integrated business process, and streamlining of integration to the back-end systems and multiple SaaS applications.
Case Study
Process Control System Support
In many automated production facilities, changes are made to SIMATIC PCS 7 projects on a daily basis, with individual processes often optimised by multiple workers due to shift changes. Documentation is key here, as this keeps workers informed about why a change was made. Furthermore, SIMATIC PCS 7 installations are generally used in locations where documentation is required for audits and certification. The ability to track changes between two software projects is not only an invaluable aid during shift changes, but also when searching for errors or optimising a PCS 7 installation. Every change made to the system is labour-intensive and time-consuming. Moreover, there is also the risk that errors may occur. If a change is saved in the project, then the old version is lost unless a backup copy was created in advance. If no backup was created, it will no longer be possible to return to the previous state if and when programming errors occur. Each backup denotes a version used by the SIMATIC PCS 7 system to operate an installation. To correctly interpret a version, information is required on WHO changed WHAT, WHERE, WHEN and WHY: - Who created the version/who is responsible for the version? - Who released the version? - What was changed in the version i.e. in which block or module of the SIMATIC PCS 7 installation were the changes made? - When was the version created? Is this the latest version or is there a more recent version? - Why were the changes made to the version? If they are part of a regular maintenance cycle, then is the aim to fix an error or to improve production processes? - Is this particular version also the version currently being used in production? The fact that SIMATIC PCS 7 projects use extremely large quantities of data complicates the situation even further, and it can take a long time to load and save information as a result. Without a sustainable strategy for operating a SIMATIC PCS 7 installation, searching for the right software version can become extremely time-consuming and the installation may run inefficiently as a result.
Case Study
Drug Maker Takes the Right Prescription
China Pharm decided to build a cloud-based platform to support the requirements of IT planning for the next five to ten years which includes a dynamic and scalable mail resource pool platform. The platform needed to have the following functions: all nodes support redundancy, ensuring service continuity and good user experience, simple and easy-to-use user interfaces for end users and administrators and good compatibility and supports smooth capacity expansion.
Case Study
ELI LILLY ADOPTS MICROMEDIA’S ALERT NOTIFICATION SYSTEM
Pharmaceutical production is subject to a strict set of enforced rules that must be adhered to and compliance to these standards is critically necessary. Due to the efforts of WIN 911’s strategic partner Micromedia, Lilly was able to adopt an alarm notification infrastructure that integrated smoothly with their existing workflows and emergency hardware and protocols. These raw energy sources enable the industrial process to function: electricity, WIN-911 Software | 4020 South Industrial Drive, Suite 120 | Austin, TX 78744 USA industrial steam, iced water, air mixtures of varying quality. Refrigeration towers, boilers and wastewater are monitored by ALERT. Eli Lilly identified 15000 potential variables, but limitations compelled them to chisel the variable list down to 300. This allowed all major alarms to be covered including pressure, discharge, quantity of waste water discharged,temperature, carbon dioxide content, oxygen & sulphur content, and the water’s pH.