Drug Discovery
Pharmaceutical companies use the insights from the patient information such as mutation profiles and patient metadata. This information helps the researchers to develop models and find statistical relationships between the attributes.
This way, companies can design drugs that address the key mutations in the genetic sequences. Also, deep learning algorithms can find the probability of the development of disease in the human system.
The data science algorithms can also help to simulate how the drugs will act in the human body that takes away the long laboratory experimentations.
Benefits for the company
Drug Discovery is a highly complicated discipline. Pharmaceutical industries are heavily relying on data science to solve their problems and create better drugs for the people. Drug Discovery is a time-consuming process that also involves heavy financial expenditure and heavy testing.
Feasability
Medium
Type of expertise/ AI domain
Machine Learning and Statistics
Internal data required
Combination of genetics, Drug protein binding data