既存薬の用量比較を、新薬の用量選択にどこまで借りてよいか
既存薬の用量比較を頑健な混合事前分布として新薬の用量選択に借りると、同等なら得は小さく、逆向きなら正選択率が大きく下がった。1群40例では事前分布との食い違いをほぼ検出できない。借用の重みは0.25〜0.5が目安。
Daiki Kumakura
I am a mathematical biologist and a bioinformatics researcher in the pharmaceutical industry. I received my Ph.D. in Life Science from Hokkaido University in March 2025.
I study biological dynamics using mathematical models and data analysis, with an interest in pharmacometrics and systems biology.
Recent writing
When patients stop being measured: how much does dropout change a tumor-shrinkage estimate?
Most tumor-scan dropout was death. A mixed model removed most of the survivor bias in 48-week shrinkage; a joint model and delta adjustment showed the 24-week arm difference was robust but the 48-week difference was fragile.
From public T-cell engager evidence to the next experiment
Public PopPK and efficacy reconstruction, Bayesian CRS sensitivity, and hypothetical measurement value and sampling design.