Dr. Regenold GmbH has entered into a strategic partnership with the analytics market leader SAS to provide organisations with tailored solutions to speed up time-consuming processes. Artificial intelligence, natural language processing, text mining and analytics on data, even if conveyed in multiple languages, all facilitate faster and more targeted knowledge retrieval which help automate processes.
The Regenold AI/Analytics team bridges the gap between regulatory and/or pharmacovigilance requirements and technology, supported by the highly innovative SAS platform.
It is increasingly important for your business to receive the information you are looking for in a speedy and precise manner. We speak your language and know the guidelines and regulations to retrieve and process targeted information as desired. We provide guidance on how to interpret your results and compile reports targeted to the needs of the various departments within your organisation. Some examples of analytics use cases include screening of literature articles, text mining for report automation and social media screening.
9th March 2020
PHUSE/FDA Data Science Innovation Challenge: We challenge you to shape the future of healthcare
The PHUSE/FDA Data Science Innovation Challenge provides a framework and an opportunity for teams in the data sciences arena to come together and collaborate intensively on projects during a defined time frame to create usable scripting that results in a functional approach to answer the scientific questions posed by a number of challenges.
We are proud to announce that we have been selected to present our prototype at the PHUSE/FDA Data Science Innovation Challenge. Our submission included an approach to classify, and even predict, drug-drug interactions using machine learning models. Are you interested? Please contact our Data Science & Analytics Team and see PHUSE webpage or the PHUSE Blog.
In order to safeguard public health, medicines regulatory agencies (e.g EMA, FDA, PMDA, TGA etc.) need ready access to comprehensive data about currently marketed products. This information is used to facilitate rapid response in situations where the health of patients might be at risk (e.g. the recent concerns over products containing valsartan). Data are derived from a wide range of sources, including a variety of document types in different formats and languages. The volume and complexity of data requested by regulators is constantly increasing.
At present, relevant data about licensed medicines are made available to regulatory databases by pharmaceutical companies through manual upload by human experts. This process is time-consuming and resource intensive. Our aim is to automate information gathering for upload into regulatory databases, thus reducing the burden for industry, while contributing to the safe use of medicines. This is our contribution to sustainability.
Are you interested? Please contact our Data Science & Analytics Team and find and watch our videos: