Secure Data Is FAIR(er) Data
公司规模
Large Corporate
国家
- Worldwide
产品
- Genedata Profiler
技术栈
- Data Management
- Data Security
- Data Integration
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Innovation Output
技术
- 平台即服务 (PaaS) - 数据管理平台
- 网络安全和隐私 - 数据库安全
适用行业
- 药品
- 生命科学
适用功能
- 产品研发
服务
- 数据科学服务
- 系统集成
关于客户
The customer in this case study is the biopharmaceutical industry at large. Biopharmaceutical companies are involved in the research, development, and production of pharmaceutical drugs based on biological sources. These companies generate a large amount of R&D data, which is a strategic asset used to build a more accurate and meaningful picture of targets, molecules, patients, and their responses to drugs. The data originates from a variety of sources, including internal databases, external collaborations, and public repositories. The industry is recognizing the value of sharing and reusing data for multiple analyses, which requires breaking down data silos. However, the data generated in biopharmaceutical R&D is complex and requires the implementation of the FAIR principles for scientific data management and stewardship.
挑战
Biopharmaceutical companies are facing the challenge of managing and utilizing their R&D data, which is often siloed within different functions of the company. This siloed data structure hinders the effective federation of distributed data, which is crucial for increasing clinical trial success rates. The industry is recognizing the value of sharing and reusing data for multiple analyses, which requires breaking down these data silos. Furthermore, the data generated in biopharmaceutical R&D is complex and originates from various sources, making it crucial to implement the FAIR (Findable, Accessible, Interoperable, and Reusable) principles for scientific data management and stewardship. However, making data FAIR is not an easy task and requires the right infrastructure that can handle the data volume and privacy of patient-level information.
解决方案
The solution to these challenges is a three-step process. The first step is to break down data silos to build an institutional memory for all data and make data-informed decisions. This can foster early go/no-go decisions, reduce drug development times, and decrease the number of costly late-stage failures. The second step is to make data FAIR. This involves implementing new data management approaches to centralize and massively harmonize the enormous amount of R&D data, which provides human access to high-quality integrated data and digital technologies. The third step is to keep data secure. This is particularly important for clinical trials that must comply with informed consent policies. The Genedata Profiler software solution is used to break down data silos and serve as the single source of truth for all translational and clinical research data, keeping data secure and FAIR.
运营影响
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
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.
