By inverting the question asked in a widely cited 2000 paper, a new metric reveals that dose proportionality is better understood as a continuous property of a compound than as a binary regulatory verdict.

Through the lens of bioequivalence, the study everyone dismisses as cookie cutter, a statistician discovers that the simple and boring can be anything but.

A statistician's argument that biology driven statistical sophistication is worth much more than statistical sophistication alone.

Good regulation solves the problem it was designed for and quietly creates the conditions for a deeper problem. Science and scientists have not been spared.

Precision is a curse until it becomes a virtue. Born from a snarky LinkedIn comment and precision, a useful metric emerges.

MCP‑Mod literally changed the dose response world for inference. Using this as inspiration, I propose a means by which inference can also be applied to multiple concentration response models.

If you think ‘not significant’ means ‘nothing learned,’ this post politely disagrees, and draws the line between uncertainty and inadequacy.

I wrote a series entitled "Why is a Statistician Invited to the Room Late?" This is really saying why is collaboration between scientists and statisticians sub-optimal. I wrote and posted 9 reasons. Here I add reasons why this collaboration matters along with links to the 9 articles that address why this collaboration is sub-optimal. This sub-optimality can lead to a host of issues: from poor decisions to information that is collected but not fully utilized, which ultimately impacts real patients. A problem is fixed by recognizing the problem and then understanding the reasons why the problem exists. Now it is time for each of us (scientists and quantitative scientists) to reflect and move this collaboration towards optimality.

This post shows, both intuitively and mathematically, why adjusting for baseline using ANCOVA is always more efficient than analyzing change from baseline.

A reflection on how drug development and applied statistics have transformed unrealized human potential into longer, fuller lives.

Investment decisions in drug development require different statistical frameworks than regulatory submissions—applying regulatory standards (multiplicity control, single pre-specified estimands) to staged investment decisions cedes control to the most risk-averse stakeholder and kills promising drugs.

Rigorous empirical research using 100 clinical datasets proved we could save 20% on trial costs, but the statistical community dismissed it as irrelevant—here's why 'statistics on statistics' remains valid.

The most effective means of building an exceptional team is through strategic relationship-based hiring rather than reactive resume reviews and references. It uses the field of statistics as an example how.

This essay shows the roles to engage to combat this never-ending concern.

Pharmaceutical statistical organizations have become so focused on regulatory process that they've lost the ability to actually analyze data, and it's setting up failures no one sees coming.

Imagine Billie Bob Thornton portraying a biotech CEO—now imagine learning about drug development risk along the way.

This essay argues that introductory statistics should prioritize numerical literacy and interpretation over mathematical and computational procedures.

Read with last week’s post.

When we have time to think, mathematics can clarify choices that instinct alone cannot resolve.

The history of creatinine clearance shows that scientific progress comes less from refining formulas than from improving the biological quantities they are meant to estimate. A model is useful for conveniently estimating the underlying biology.