I am excited to share that one of our recent papers written in collaboration with EMD Serono, Pharmacometric modeling and machine learning analyses of prognostic and predictive factors in the JAVELIN Gastric 100 phase III trial of avelumab, has been recognized as one of the most cited in its publication last year. Reflecting on this achievement, I wanted to provide some insights into why I believe this paper resonated so strongly with the pharmacometrics community and became such a valuable resource.
Matthew Wiens, M.A.
Recent Posts
JAVELIN Recognition: Insights from One of the Most Cited Papers of the Year
Topics: Methodology, Tools, and Computation, Machine Learning, AI
Thoughts on Machine Learning and AI from ACoP: Part Three
Welcome to the final post of a three-part blog series reflecting on the ACoP (American Conference on Pharmacometrics) 13 meeting held October 30th - November 2nd, 2022.
Thoughts on Machine Learning and AI from ACoP: Part Two
Welcome to the second post of a three-part blog series reflecting on the ACoP (American Conference on Pharmacometrics) 13 meeting held October 30th - November 2nd, 2022.
Thoughts on Machine Learning and AI from ACoP: Part One
This is a three-part blog series reflecting on the ACoP (American Conference on Pharmacometrics) 13 meeting held October 30th - November 2nd, 2022.