Blog

Predicting the difficulty and associated costs for drug development can be a challenge. However, there are efforts to systematically examine the expenditure and probability of success of clinical trials, as related to the study phase and therapeutic area.

We simulated the likelihood of approval and associated expenses for hypothetical pipelines across different therapeutic areas. Emerging from this analysis were indication-related characteristic distributions, but the results could be refined by repeating the approach with a higher quality dataset.

Atomic resolution of intramolecular and intermolecular interactions are highly sought after to better understand biological processes and aid drug development.

DeepMind’s AlphaFold2 outperformed all other groups at the protein structure prediction competition known as CASP. The assessment results are briefly evaluated.

Contrary to mainstream media, protein folding is not yet a solved problem. However, deep learning algorithms have accelerated our ability to accurately predict structures for well-behaved proteins.