下载PDF
Leveraging IoT for Efficient Drug Scale-Up in Pharmaceuticals: A Case Study of Dr. Reddy’s
适用行业
- 生命科学
- 药品
适用功能
- 物流运输
- 产品研发
用例
- 最后一英里交付
挑战
制药行业充满了众多挑战,从药物输送到设备设计优化和规模化问题。原材料成本的增加以及在正确的时间无法获得正确的原材料给满足严格的产品交付期限带来了重大问题。 Dr. Reddy's 是一家全球制药公司,面临这些挑战,并寻求探索工程模拟来有效解决这些挑战。该公司与 ANSYS 合作,利用其在该领域的专业知识,旨在通过在每个尺度上执行稳态和瞬态仿真来开发精确的放大条件。他们试图从一种尺度到另一种尺度研究速度分布、混合时间和物种浓度等参数。
关于客户
Dr. Reddy's 是一家在纽约证券交易所上市的公司,在全球 100 多个国家生产和销售 API、成品制剂和生物制剂。作为一家垂直整合的全球制药公司,Dr. Reddy's 拥有经过验证的研究能力,包括前景光明的药物发现管道和整个制药价值链的影响力。该公司拥有利用一系列建模工具将复杂产品从实验室规模扩大到工厂规模的专业知识。公司的工艺专家帮助降低从实验室到工厂的放大风险。
解决方案
ANSYS 顾问使用模拟来帮助 Reddy 博士了解从实验室规模到工厂规模的微观、细观和宏观混合时间的差异。他们还确定了每个特定转速水平的放大所涉及的风险以及工厂规模模拟中死区的形成。此外,他们使用瞬态模拟研究了单个物种浓度和混合性能的演变。与 ANSYS 进行的工程模拟咨询为放大的物理原理提供了宝贵的见解,并确定了所涉及的风险。它指导 Reddy 博士降低批量放大的风险,并帮助在实验数据极少或难以获得实验数据的情况下做出更明智的决策。
运营影响
数量效益
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.