Category Archives: Stats and Inference

Uncertainty quantification for ion channel screening and risk prediction

This post accompanies our new paper in Wellcome Open Research. Regular readers of this blog will know that I worry about uncertainty in the numbers we are using to model drug action on electrophysiology quite a lot – see our … Continue reading

Posted in Drug action, Model Development, Safety Pharmacology, Stats and Inference | Tagged , , , , , , , , , | 4 Comments

Should I work with IC50s or pIC50s?

When you are expressing how much a drug inhibits something, it’s common to fit a Hill curve through a graph of concentration against % inhibition as shown here: In our case this is often ‘% inhibition’ for a given ionic … Continue reading

Posted in Drug action, Safety Pharmacology, Stats and Inference | Tagged , , , , , , , , , , , , | 1 Comment

Are 30 compounds enough to test our simulations?

I’ve just contributed to a new review ‘Recent developments in using mechanistic cardiac modelling for drug safety evaluation’, which discusses where we are with using mathematical models of the electrical activity of cardiac muscle cells to predict whether new drugs … Continue reading

Posted in Action Potential Models, Drug action, Ion Channel Models, Safety Pharmacology, Stats and Inference | Tagged , , , , | 7 Comments

Model Complexity

We’ve been thinking about how to parameterise/train/calibrate models, and also how to select an appropriate model to begin with. This raises all sorts of interesting questions on the details, but this post is just about setting out a big overview … Continue reading

Posted in Action Potential Models, Ion Channel Models, Model Development, Stats and Inference | Tagged , , , , , , , , | Leave a comment

If computational biologists did astronomy…

Here is a cheeky post along the lines of Can a biologist fix a radio? (well worth a read). The discovery that Pluto wasn’t the size we expected got me thinking about how we would have tackled it. So in … Continue reading

Posted in Action Potential Models, Silly, Stats and Inference | Tagged , , , | Leave a comment