Date: Tuesday 12th September 2023 Time: 12:00-13:00 BST | 13:00-14:oo CEST Location: Online Speakers: Kleio Kipourou (GSK), Andy Nicholls (GSK), and Tom Fisher (UCB).
Who is this event intended for? Anyone who is interested in learning more about AI advances and its potential uses in the pharma industry and the associated challenges. There are no expectations or requirements on the previous experience on using ChatGPT or AI for this session. What is the benefit of attending? This session will cover the incredible advances in AI and how they are going to shape the future of medical statistics within the pharmaceutical industry. It will raise awareness of opportunities, challenges and changes that lie ahead for the roles of programmers and statisticians.
Registration
Registration for this webinar is free for both Members of PSI and Non-Members.
To register for this event, please click here.
Overview
This PSI Lunch & Learn series focuses on career-related topics through a panel discussion, hosted by Claire Brittain & Chetan Mistry.
Upcoming session:- In the upcoming event – “ChatGPT & Beyond” – we will be discussing the advances of AI and its applications to medical statistics and programming within the pharmaceutical industry.
We asked ChatGPT to briefly describe the benefits and challenges of ChatGPT and AI in the context of careers for Statisticians and Programmers working in the healthcare industry. Here’s what it came out with….
ChatGPT output: Benefits of ChatGPT and AI for Statisticians and Programmers in healthcare include efficient data analysis, predictive modelling, and automation, leading to optimized patient outcomes and personalized medicine. AI can process vast amounts of data, uncover valuable insights, and enhance decision-making.
Challenges involve ensuring data quality and privacy protection due to the sensitive nature of healthcare data. Interpretable AI models are crucial for transparent decision-making. Regulatory compliance can be complex, and integrating AI into existing systems may face obstacles. Addressing bias and fairness concerns is vital to prevent disparities in patient care. Upskilling in data science and AI is necessary for successful implementation in the healthcare industry. Careful consideration of these challenges is essential to fully harness AI's potential benefits.
Did ChatGPT meet your expectations? Could we have prompted more effectively? Was ChatGPT even the best tool? Come to our panel session and hear the discussion from our deepfake experts.
Speaker details
Speaker
Biography
Kleio Kipourou
Kleio is a pharmacist and biostatistician/data scientist with an extensive background in both academia and the pharmaceutical industry. Currently, she is working for GSK focusing on large scale projects that have complex challenges and require analytical solutions. Prior to her role at GSK, Kleio worked for AstraZeneca, where she successfully delivered a fully automated predictive tool for over 90 active clinical trials. This innovative tool not only ensured patient safety but also maximized trial success and significantly reduced cycle times.
In addition, Kleio's commitment to promoting patient diversity and addressing the impact of socioeconomic inequalities on health outcomes led her to engage in extensive research under the sponsorship of Cancer Research UK. During this time, she developed novel methods that quantify individuals risks as well as differences in cancer survival. Through her contributions, Kleio has played an essential role in advancing our understanding of these disparities and their implications for cancer patients.
Presently, Kleio is leading an exciting initiative at GSK that emphasizes the ethical use of statistical models and AI. This initiative not only raises awareness but also provides essential recommendations to ensure the responsible and ethical implementation of cutting-edge technologies in pharma.
Andy Nicholls
Andy Nicholls has been a Data Scientist for as long as people started calling themselves Data Scientists. He currently serves as the Head of Data Science at GSK Biostatistics' Statistics and Data Science Innovation Hub. In this role, he leads a team dedicated to developing data science capabilities within Biostatistics and providing innovative Data Science solutions for R&D business partners in areas such as Clinical Operations, Resource Management, HR, and Finance.
Before re-joining GSK in 2017, Andy held the position of Head of Data Science Consultancy at Mango Solutions, a specialised data science consultancy with a focus on the R programming language. During his tenure at Mango, he supervised various consultancy projects across multiple sectors, delivered technical training, and implemented a wide range of technical solutions, from simple analytics to extensive IoT projects.
Andy's professional background also includes experience as a clinical trial statistician at GSK. He holds an MMath in Mathematics from the University of Bath and an MSc in Statistics with Applications in Medicine from the University of Southampton.
Tom Fisher
Tom is a machine learning researcher at UCB, where he one of his roles involves working as part of a team exploring the utilisation of large language models (LLMs) within the company.
After studying maths at Cambridge, he pursued an MSc in Machine Learning from UCL, where he published a paper on gender bias in LLMs.
During his time as a research associate at Oxford, he focused on applying machine learning techniques to remote sensing in international development before shifting his focus to electronic health records. This involved investigating the potential of BERT-like models to enhance cardiovascular disease risk prediction.
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