Publications

A Bayesian Adaptive Design for Phase I/II Clinical Trials in Oncology

Published in the Journal of Clinical Oncology, this paper introduces a novel adaptive design that improves the efficiency of early-phase clinical trials.

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Machine Learning for Predictive Modeling of Cancer Patient Survival

This article in Nature Medicine showcases the application of machine learning algorithms for predicting patient survival and treatment response.

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Statistical Methods for the Analysis of Real-World Evidence in Oncology

A comprehensive review of statistical methods for analyzing real-world data, published in the Annals of Oncology.

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Datasets

Simulated Clinical Trial Data for Adaptive Design

A collection of simulated datasets for testing and validating adaptive clinical trial designs. Available for download in various formats.

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Anonymized Genomic Data from Pan-Cancer Analysis

A large-scale, anonymized genomic dataset from a pan-cancer analysis, suitable for biomarker discovery and validation studies.

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Guidelines

Statistical Guidelines for Cancer Clinical Trials

A set of best-practice guidelines for the statistical design and analysis of cancer clinical trials, developed in collaboration with international regulatory agencies.

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Data Sharing and Anonymization Policy

Our policy and guidelines for the responsible sharing and anonymization of clinical trial data.

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Training

Workshop on Adaptive Clinical Trial Design

An annual workshop for statisticians and clinical researchers on the theory and practice of adaptive clinical trial design.

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Online Course in Medical Statistics for Oncologists

A self-paced online course designed to provide oncologists with a solid foundation in medical statistics.

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