ASCPT Members-Only Webinar Presented by the Quantitative Pharmacology (QP) Network
: Application of Machine Learning in Drug Development (Two-Part Series)
Date and Time:
– Friday, November 2, 2018,
2:00 PM EDT
: Jagdeep Podichetty, PhD
: Daniela J. Conrado, PhD
: Machine learning (ML) is a computationally intensive approach with foundations in statistical theory. Broadly, machine learning integrates data from heterogeneous sources into a model that predicts an outcome. ML is being applied to a range of different areas including self-driving cars, practical speech recognition, effective web search, and drug development.
of this webinar series covered acquiring data and formulating problem statement, data curation and visualization, feature selection methods, supervised ML approach, unsupervised ML approach, and real-world applications of ML in drug development. Recording and slides available in the ASCPT Webinar Library
of the series will take a deep dive into development of an ML algorithm for predicting improvement in patients with schizophrenia using CATIE clinical trial data. The process of ML step-by-step per the ML workflow will be reviewed as well as some widely-used ML algorithms such as Random Forest, Naïve Bayes and Logistic Regression. Outcome prediction techniques will also be identified.
Registration Link for Part 2