How to calculate ic50 value in excel?

Hey there! As someone who works in pharmacology research, I can walk you through calculating IC50 in Excel. IC50 represents the concentration where a substance achieves half-maximal inhibition.Here's my step-by-step approach:1. Prepare your data - You'll need concentration values and corresponding response values (usually as percentage inhibition)2. Create a scatter plot with concentration on x-axis and response on y-axis3. Add a trendline - Right-click on data points, choose "Add Trendline," then select "Logistic" or "Sigmoid" fit4. Display equation on chart - This gives you the curve parameters5. Set up calculation - Use the formula = (LOG((50/(100-50)))/-SLOPE) or similar based on your trendline equationThe key is ensuring your data follows a proper sigmoidal curve. I'd recommend checking out this detailed guide from GraphPad which explains the underlying math really well.

I've found that while Excel can do basic IC50 calculations, it's really not the ideal tool for this. The methods others mentioned work, but they're pretty manual and prone to error if you're not careful with the formulas.If you're doing this regularly, consider using:- GraphPad Prism (specifically designed for bioassays)- ** specialized online calculators- R or Python** with appropriate packagesThat said, if you're stuck with Excel, the sigmoidal curve fit method is your best bet. Just be aware that Excel's curve fitting isn't as robust as dedicated statistical software, so your results might have wider confidence intervals. Always run replicates and calculate your error margins!

Oh, I remember struggling with this when I first started in the lab! There's actually a pretty straightforward way using Excel's built-in functions. What worked for me was using the LOGEST function combined with some manual calculations. Basically, you need to:- Transform your concentration data using log10- Plot % inhibition vs. log(concentration)- Use LINEST to get the slope and intercept- Then calculate IC50 using: =10^((50-intercept)/slope)Pro tip: Make sure your response values are normalized between 0-100% for this to work properly. The hardest part is getting good quality data - if your points are all over the place, no calculation will give you accurate results!