How to Use Machine Learning in Clinical Research Right Now
To watch this webinar, please visit: https://bit.ly/3yUm5pw In machine learning, there are usually one of two distinct objectives: inference or prediction. In analyses involving clinical trial data and/or real-world data, a machine learning solution can be used by data scientists to detect patterns that conventional analysis and statistical methods cannot. Thus, a machine learning practitioner can help to infer which subgroups that respond, either particularly well or poorly, to a treatment. Similarly, machine learning algorithms can be used to predict a discrete or time-to-event outcome. When knowledge increases of subgroups of interest and on outcomes before they occur, the impact on patient care and clinical research is very powerful. In this Expert Insights webinar, attendees will learn: • Why data science and the use of machine learning is essential to pharmaceutical, biotech, and medical device organizations • How to use machine learning to understand outcomes before they occur • Practical approaches for inference or prediction through machine learning • Metrics to evaluate the performance of predictions made Possibilities for the future of machine learning in clinical research
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How to Use Machine Learning in Clinical Research Right Now
- 1. How to Use Machine Learning in Clinical Research Right Now © MMS Holdings 2021
- 2. Our Presenters Chris Hurley Associate Director Data Science Richard Bryant Senior Data Scientist 2 © MMS Holdings 2021
- 3. Company Overview 3 • Leading data-focused CRO, specializing in key steps leading up to regulatory submissions • 650+ highly-experienced, industry-trained staff • Global presence to optimize clientele support ‒ Corporate headquarters in Canton, Michigan ‒ Asia headquarters in Bangalore, India ‒ EU headquarters in London, UK ‒ Satellite Locations in Asia, Europe, South Africa, and throughout the United States • Minority Business Enterprise (MBE) • Privately-owned, no parent or any subsidiaries • ISO 9001:2015 and 27001:2013 certified • Privacy Shield Certified • CDISC Gold-Level Member • PhUSE Sponsor & Board Member © MMS Holdings 2021
- 4. Abstract In this Expert Insights webinar, attendees will learn: • Why data science and the use of machine learning is essential to pharmaceutical, biotech, and medical device organizations • How to use machine learning to understand outcomes before they occur • Practical approaches for inference or prediction through machine learning • Metrics to evaluate the performance of predictions made • Possibilities for the future of machine learning in clinical research 4 © MMS Holdings 2021
- 5. 5 Machine Learning Definition • Common definitions of the term ‘machine learning’ can be vague, such as “training machines to think” • The term is sometimes used interchangeably with “artificial intelligence”, although ML is a specific form of AI • Think of ML as a series of methods that can use complex algorithms to detect novel patterns in a dataset • An example of simulated data using R will be used to demonstrate the capabilities of ML © MMS Holdings 2021
- 6. 6 Regulation • Statistical Software Clarifying Statement (2015) • 21st Century Cures Act (2016) • Framework for RWD and RWD (2018) • Draft Guidance for Clinical Decision Support Software (2019) © MMS Holdings 2021
- 7. 7 Demonstration Topics • RStudio Environment • Demonstration Use Case – Simulated Mini-Mental State Examination data – Time to first dermatological event • Data Preparation – ETL Load datasets/Manipulate datasets • Inference • Prediction • Conclusion © MMS Holdings 2021
- 8. 8 Conclusion Much more is possible • With machine learning algorithms applied to end goals of inference or prediction, knowledge can increase of subgroups of interest and on outcomes before they occur • Combining real-world data with clinical trial data can grant endless possibilities © MMS Holdings 2021
Editor's Notes
- Title slide only
- Don
- Chris MMS is a global data CRO supporting all aspects of data for your clinical program. This is our 12th yr. in business and we are a leading submissions CRO averaging various aspects including compete submissions of 8-10 applications every year. Our staff has over 2 decades of pharma experience most of our leadership is ex-Pharma from Parke-Davis/Pfizer who used to be in the Ann arbor area Our corporate headquarters as seen in the building is in Canton, MI about 15 mins from Ann arbor and 15 mins from the DTW metro airport…the building you see is where we are located and we welcome you to come visit…on bright sunny day Our Asia headquarters is in its 11th yr. of operation is in Bangalore and we have offices in Hyderabad India as well, other locations throughout the world with a focus of data management in South Africa Globally we are over 500 colleagues (If asked, distribution would be 40 percent US, 40 percent India and 20 percent EU and Rest of world) We are a minority business enterprise More importantly since inception we have been certified for quality and are audited annually by an external auditing body like TUV Rhineland to ensure we maintain quality deliverables. We also maintain the information security management system certification as a data CRO We are active leaders in CDISC and PHUSE establishing standards and criteria with the leaders in the industry and regulators for our data and submissions. Invite the clients to come visit us…in summer…add some humor if capabilities are in winter
- Chris
- Chris
- Chris
- Richard’s slide followed by demo
- Chris