On the afternoon of October 26th, the 11th Medidata NEXT China Annual Meeting 2022 Suzhihua Drug Research and Development sub-conference was held online. Medidata NEXT China Annual Conference, with the theme of "Brave to Think ahead, Create the Future", is held by Medidata, a wholly-owned subsidiary of Dassault Systemes, France. It brings together the world's most cutting-edge bioscience innovators, exchanges and collides ideas with foresight, discusses the frontiers of digital medicine, and takes the pulse of the development trend of medicine. It presents a grand event for the exchange of ideas, cooperation and common development.
Among them, Suzhihua Drug Research and Development conference specially invited Dassault BIOVIA life science solutions consultant Hua Peng, Beigen Analytical Research and Development Senior Director Gao Yang, Wuxi HitS Division Director Dr. Yin Jian, Beijing Zhuoya Medical Technology Co., LTD CEO Zhou Zhuang, theme report focused on cutting-edge drug research and development technology.
Digital intelligent drug research and development is one of the key areas that industry personnel pay attention to, effectively avoid the chaos caused by manual management, data statistical errors and other problems, so as to achieve intelligent experimental operation, project operation, research and development management, is an important means to improve the research and development ability of pharmaceutical enterprises, strengthen production capacity. How to use digital intelligent system to help innovative drug research and development? How to improve the efficiency of pharmaceutical R&D by Informatization?
As the first guest speaker, Mr. Hua Peng, Consultant of BIOVIA life Science Solutions of Dassault Systemes, opened the forum with a report entitled "ELN System Assists the Transformation of digital intelligence in pharmaceutical R&D Laboratories". He first analyzed five of the most common challenges in R&D LABS:
● Find data: how to find data and information quickly and accurately when needed.
● Organize and store data: how to classify and store data in a reasonable way to make it easier to access, process and analyze.
● Sharing data: Sharing data with other people or other organizations often takes a lot of time and effort.
● Use too many systems: too many systems and databases increase maintenance costs and reduce data access efficiency.
● Managing large amounts of data: The increasing complexity of research has led to a rapid increase in the volume of research data, requiring more effective means to cope with it.
In this regard, he believes that:
Change the traditional management mode of the laboratory: for example, the BIOVIA Workbook ELN system is used to improve the laboratory management at all levels by using the experimental template, experimental query, data processing, experimental report, audit trail and other functions.
Construction of R&D laboratory ecosystem: Through the establishment of a unified platform including materials management, instrument management, biomacromolecule and compound library, task management and other modules, as well as integration with other kinds of third-party systems and programs, to achieve efficient laboratory information interconnection.
According to Hua Peng, BIOVIA Workbook will help pharmaceutical innovation and accelerate the launch of new drugs
Subsequently, Gao Yang, senior director of analytical research and development of Beigene, made a report entitled "Compliance of ELN Assisted drug process research and Development". Gao Yang pointed out that in drug process research and development, the quality risk assessment (QRA) of the API process is an important part of the product marketing application data, which is very important for the product marketing. In particular, impurity carrying studies (F&P) provide core data to demonstrate the process's impurity removal capabilities, so data integrity and reliability are required. "Complicated experimental design brings great challenges to data integrity". Therefore, experimental design based on ELN is particularly important. As a data collection and processing platform, ELN can reduce human error and improve work efficiency. The audit trail and electronic signature function of ELN also ensure the authenticity and reliability of the data.
Dr. Jian Yin, Director of Wuxi Apptec HitS, presented the report "New Opportunities for CADD and Chemoinformatics in Biomedicine". Dr. Yin points out that with the explosion of deep learning methods and cloud computing in recent years, there is more room for traditional CADD to work. In addition, some cutting-edge technologies of drug discovery, such as DNA coding compound library technology, have been recognized by more users of new drug discovery, and have also generated massive data. Therefore, how to make these data play a better role has become the breakthrough point for CADD and chemoinformatics combined with deep learning technology to really play a role in the field of biomedicine.
In the development of some new models and hot drugs, such as covalent small molecule drugs, antiviral drugs, PROTAC,PPI, etc., the combination of CADD and AlphaFold can also play a magic role.
Finally, Zhou Zhuang, CEO of Beijing Zhuoya Medical Technology Co., LTD., presented the report "BIOVIA Molecular Simulation and Data science software Enabling a New Model of Drug Development". New drug research and development has been recognized globally as a prominent hotspot of "three high and one long", namely "high technology, high investment, high risk, long cycle". In this context, Zhou believes that modeling and simulation techniques offer the possibility of atomic-level interactions that support drug discovery, enabling researchers in the life science industry to test "concept-to-reality" possibilities with minimal risk and lower cost. He said that Dassault Systemes BIOVIA provides the life science industry with excellent molecular simulation and simulation research tools, and can combine data science software to achieve everything from data access and aggregation to complex data analysis, modeling and reporting. The automation of these processes allows scientists to make the most of their data. Helping scientists build better, safer, and more cost-effective products to improve patient outcomes.
As the global pharmaceutical enterprises change the layout faster and faster, innovative technology is constantly introduced, and its application is becoming a sharp tool in the research and development of digital intelligent drugs. BIOVIA will continue to focus on drug discovery and bring more advanced experience and digital solutions to the global life sciences sector.
