I've met Lily Wong at Bayer's Global DS&AI F2F Meeting
Experienced leader in development, validation, and implementation of clinical trial software and processes
I had the honor of serving as the DSSS team's subject matter expert for Rave EDC and its integrations in the past. However, I now have the privilege of leading a diverse group of talented senior developers and user access management professionals within the DSSS team. By working together, we aim to deliver innovative solutions that optimize clinical trial performance and drive positive outcomes for our study teams.
The Proprietary Information Management team, PIM, takes care of processes and systems related to either Compliance or Data Governance. Please talk to us if you need help with some cross-functional or collaboration-related topic or if you are interested to learn more about compound-related processes, compliance checks, lab notebook systems and similar things. For more information contact: Friederike Stoll.
The SCLM4Future project together with the PRINCE (Preclinical Information Center) project as well as the CONDAS (Connecting Data for Science) team is an excellent example for a successful cross-functional collaboration between CD&O, RED preMed and DS&AI within Research & Development but also between Platform IT and external partners. Together the team achieved to overcome legacy manual processes, redundant maintenance work, and functional silos by introducing new digital solutions and concepts with a strong collaborative mindset. The newly released SCLM 2.0 (Standard Codelist Maintenance) & PTO (Preclinical Terminology and Ontology) systems will enable our organization to improve the quality of controlled terminologies with regards to standard codelists and codes while reducing maintenance time and effort. This will have a positive impact on the code/codelist consistency across clinical and preclinical, as well as the compliance to regulatory requirements (e.g. CDISC (Clinical Data Interchange Standard Consortium) Controlled Terminology). The approach to share our knowledge as well as our efforts across functions will be an important step to archive our goals to increase data quality, interoperability and reusability – or to make a long story short: to make our data even more FAIR. For more information contact: Daniela Bergann.