下载PDF
LabGenius and Antha: Combining active learning with Antha’s multifactorial optimisation for a single-stranded DNA (ssDNA) extension reaction
技术
- 分析与建模 - 机器学习
- 功能应用 - 远程监控系统
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 生命科学
- 药品
适用功能
- 产品研发
- 质量保证
用例
- 数字孪生
- 质量预测分析
- 过程控制与优化
服务
- 软件设计与工程服务
- 系统集成
挑战
LabGenius faced the challenge of optimizing the single-stranded DNA (ssDNA) extension process, a critical step in their DNA library generation method. The process required different priming oligonucleotides for each ssDNA extension reaction, making it necessary to re-optimize the extension process for every new DNA library fragment. This repeated context-specific optimization was extremely challenging to execute manually due to the number of experimental runs and the complexity of the experimental designs. The need to recover maximum diversity during the single strand extension of DNA fragments encoding degeneracy was critical to the EVA platform. Manual execution within the expected time frames of DNA library generation was not feasible, necessitating an automated solution.
关于客户
LabGenius is a biotechnology company that has developed EVA, an autonomous AI-driven evolution engine for the discovery of next-generation protein therapeutics. They use their cutting-edge platform technology to develop new protein-based drugs in collaboration with world-leading pharmaceutical companies. The EVA platform utilizes an AI-driven DNA library design strategy to plan, optimize, and physically execute the production of superior quality DNA libraries encoding a host of evolved therapeutic proteins. These proteins range from enzymes to antibodies, with engineering objectives that include improved or altered binding affinity, specificity, thermostability, or resistance to proteases. LabGenius started working with Antha in 2017 and has since automated upwards of 20 unique workflows of value to them.
解决方案
LabGenius integrated Antha into their EVA platform to automate and optimize the ssDNA extension process. Antha enabled LabGenius to physically execute multifactorial experimental designs in an automated and autonomous manner. This integration allowed LabGenius to autonomously design, plan, and execute process optimization as part of their end-to-end platform. Antha's rapid and flexible digital interpretation and physical execution of complex multifactorial experimental designs provided a reusable framework to identify robust experimental conditions. This framework achieved double-stranded DNA (dsDNA) recovery efficiencies above the required minimum threshold for maximizing DNA library diversity. The automated multifactorial design interpretation, experimental planning, and execution by Antha provided significant time savings compared to manual execution. Antha's DoE suite of elements allowed LabGenius to rapidly and flexibly define an automated liquid handling protocol, simulating all low-level liquid handling instructions interpreted from a DoE design file. This facilitated the execution of experimental runs on a Gilson PIPETMAX™ liquid handling platform, providing extensive time and resource savings.
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.
