AI is also affecting largely unseen aspects of BioTech and Pharmaceuticals. Things like marketing, lab assistants, and administrative work take up considerable resources. Marketing is a direct contributor to the success of new drugs, at least in the United States, and AI could provide better insights into those campaigns AI can also assist in administrative …
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Sentiment Analysis
Among the tools of Big Data, sentiment analysis is one that helps to analyze social networking posts and comments. Organizations primarily use it for marketing, advertising, and public relations research. For example, many companies use it to find the reaction of the consumer and get their feedback. Benefits for the company Some companies are creating …
Loss of Exclusivity
When the company loses exclusive brand rights to a drug, they can effectively use data to maintain patient loyalty and prevent churn. Benefits for the company Companies can still tap the benefits of having the loyal customer base and prevent from losing them. Feasability High Type of expertise/ AI domain Data Management and SQL Internal …
Supply Chain and Manufacturing/ Advanced Supply Chain Optimization
Identifying the most efficient supply system by optimizing and automating steps of production will become even more important as drugs are increasingly customized to small numbers of patients with certain genetic profiles. When it comes to manufacturing, pharmaceuticals can harness machine learning to control rising equipment maintenance costs and pave the way for self-maintenance through …
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The Future of Computational Biochemistry
Computational biochemistry allows drug-makers to cut out a significant portion of the test tube experiments. Instead, a computer simulates the protein and tests all of its atomic interactions. That analysis will yield a far conscise list of leads that researchers can take to the next stage of testing Benefits for the company Deep learning truly …
Identifying Compounds
Instead of throwing darts at the wall and hoping to land on an eventual hit—an expensive and inefficient process—pharmaceutical companies can leverage Deep Learning techniques to not only cull through literature and journal publications but also to pre-screen for the most effective potential compounds to prioritize their time. There are software solutions that allow researchers …
Identifying patients for clinical trials
ML/AI can help introduce efficiencies to the clinical trial process in two ways. First, by more quickly and precisely identifying patients who would be a good fit for a particular trial via advanced analysis of medical records or by exploring geographically- and symptom-distinct patients at scale. Secondly, these techniques can examine the interactions of potential trial …
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 …
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 …