Dr. Jürgen Regenold, Managing Director and Soundarya Palanisamy, Head of Data Science & Analytics, at Dr. Regenold GmbH give an exciting lecture on this topic at the SAS Forum on 28th May 2020 at 2:00 - 2:20 pm | Channel, https://www.sas.com/de_de/events/20/sasforum/agenda.html.You are invited to participate! Simply use the link provided to learn more about this topic.
Healthcare is a large, growing, complex industry which has the patient at the heart of what it does ensuring they have access to safe, effective and quality medicines. Regulations in healthcare help ensure these three requirements are met and data is key to all three whether it is patient or manufacturing data. Dr. Regenold GmbH has been working with SAS to develop these use cases while bridging the gap between Data Science and clinical/regulatory expertise, which help data extraction and analysis to achieve the three basic requirements for the supply of safe and effective medicines for patients. The use cases cover patient data, regulatory documentation and manufacturing:
Unbiased patient data for your marketing strategy
Obtaining more information about patients’ experiences and what patients talk about on social media (patient forums) is crucial learning for a pharmaceutical company. We explain how new insights gathered by crawling patient voice data on the internet, based on our client´s ‘targeted’ questions, can be discovered.
Regulatory Intelligence - Our approach about how Analytics could change the regulatory operations will be presented
AI allows the regulatory function to increase the speed, accuracy and quality of how they execute certain functions. AI tools are effectively being used to give regulatory affairs new insights into their own decision making ability, to help to improve their operating processes and spot recurring patterns.
Predictive QA – a unique way to control your QA processes in pharmaceutical manufacturing
Dr. Regenold's Predictive QA solution serves to provide companies with a compliant trending service which identifies the degree of the state of control of their pharmaceutical products.
If you have any questions, or would like more information, please contact Soundarya Palanisamy at soundarya.palanisamy(at)regenold.com
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.
The Innovation Challenge 2020 includes the following challenges:
The first Innovation Challenge was due to be held at the US Connect in Orlando in March, however given the unprecedented situation, as a result of COVID-19, the virtualisation of the PHUSE/FDA Data Science Innovation Challenge 2020 has been announced, which will be available to all!
The submissions will be presented as part of a new initiative, Innovation Fridays, where there will be a short webinar to allow people to come together and discuss future digital solutions to healthcare problems.
Consequently, we are proud to announce that we have been selected to present our prototype on Friday 24th April under the challenge topic ‘An approach for predicting drug interactions’. We will be presenting an approach to classify drug interaction in literature articles, and prediction of, drug-drug interactions using Artificial Intelligence methods. Join the event by visiting the PHUSE webpage or PHUSE Blog.
For more information, please contact Soundarya Palanisamy our Team Leader for Data Science and Analytics, at soundarya.palanisamy(at)regenold.com
COVID-19 has been declared a pandemic by the World Health Organisation (WHO). Through our partnership with SAS we are able to provide you with accurate, up-to-date information on the pandemic as it develops. SAS has created a Covid-19 dashboard: https://tbub.sas.com/COVID19/ and we, together with SAS, could offer to analyse social media data from different regions or about symptoms, and predictively recognize connections.
When people with no medical background talk about illnesses and treatments online, they generate mountains of unstructured data. If you want actionable insights, you’re going to need serious automation and, crucially, powerful analytics. Together with SAS we have expertise in developing customised solutions for listening and analysing social media. Currently we are also developing a use case to screen social media data and listening to patient’s comments on the COVID19 topic, therefore if we could be of help please contact us.
In addition, Dr. Regenold GmbH is working intensely on its contribution to the fight against the Covid-19 crisis. We are developing an AI tool, which will support doctors in identifying signs of Covid-19 in X-rays in critically ill patients for whom the PCR test might take too long. Using X-ray images, we are training a neural network to detect signs of Covid-19.
All our use cases are developed to be validated and regulatory compliant.
For more information or answers to your questions, please contact Soundarya Palanisamy our Team Leader for Data Science and Analytics, at soundarya.palanisamy(at)regenold.com
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. Please watch the video we produced on this topic and entered into the SAS EMEA Hackathon.
If you are interested in receiving more information or have questions about this topic please contact our Data Science & Analytics Team: