Don’t be surprised if you wake up tomorrow to discover that AI has taken over another industry you never thought of. Recent AI transformation across different industries is proof that no space can confine artificial intelligence all to itself. Like every other industry that has enjoyed the proliferation of artificial intelligence, Big Pharma is having its fair slice of the AI-pie.
In the healthcare space, healthcare practitioners rely on medications produced by pharmaceutical companies to treat a variety of diseases and to increase the life expectancy of patients. Globally, the biopharmaceutical industry is a multi-billion dollar industry that is always up on its toes towards novel, innovative medicines with major core areas in Drug discovery and development.Â
Drug discovery is the process of how new medicines are discovered. It ensures that a compound is therapeutic in curing and treating diseases. Once the lead compound has been identified via drug discovery, the process of bringing it to the market starts – this is drug development. The process from finding the lead compound to getting it to the market isn’t a walk in the park, either is the associated cost or timeline. It can take a decade for a new medicine to walk that route without factoring in clinical trials with an approval rate of less than 12%, which may span six to seven years. This costs pharmaceutical companies an average sum of $2.6 billion, according to reports by Tufts Center for the Study of Drug Development published in the Journal of Health Economics.
In the last six years, AI has re-invented how medical scientists develop new drugs to tackle diseases. Some pharmaceutical companies now resort to the use of automated algorithms to carry out tasks in drug discovery and development that once depended on human intelligence. The availability of Big Data and data analytics are responsible for this. The manufacturing systems used by pharmaceutical companies utilize the Internet of Things (IoT) to collect data at every stage of the drug development process. By using sophisticated AI tools, medical researchers at the fore-front of drug development get actionable insights from stacks of unstructured data in good time.Â
This makes drug discovery and development faster and accurate. Patients whose lives are dependent on these medications are also able to access them in good time. To maximize the wealth of potential in AI, Big Pharma is going into partnerships with AI start-ups to help it make sense of the many data it is generating. For instance, Moderna is using Amazon’s AWS Cloud to develop messenger RNA medications to fight diseases, including COVID-19.
In drug discovery, new candidate medications are discovered. The process is filled with numerous trials and errors to identify the compound of interest. Target identification is the first step in a drug discovery process and involves high thorough-put screening. A drug target is a molecule in the body that is linked with the particular disease the drug-in-development is expected to act on. Â
The next step is to validate the target. Here, medical researchers must show two things.
