In an effort to increase the return on investment of research and development, pharmaceutical companies are constantly looking for ways to reduce costs. One way to do this is to incorporate technology and minimize human interaction. As a result, scientists will have more time to focus on the design and analysis of experiments. How will the Lab of the Future reflect these changes?
Drug discovery and development are both time and resource intensive since a lot of different compounds need to be screened across a lot of different targets. See how machine learning models can be used to predict screening results and how active learning algorithms can be used to efficiently select which experiments to perform in order to build those models.