The pharmaceutical industry is set to greatly benefit from the use of artificial intelligence (AI), due to its wide range of applications. Sydney Tierney discusses how machine learning can enhance marketing, manufacturing and drug trials.
Considerable progress has been made in the application of AI in the pharmaceutical industry over the past decade. This past February, the Economist declared that “AI could soon make us all much healthier, even if it does nothing to cure disease.” In the context of personalized medicine, artificial intelligence will be able to make recommendations to a patient, such as which drugs to take or which drugs to avoid. Additionally, technology has been applied to the basic processes of drug discovery, improving processes such as locating compounds and understanding how they interact with cells.
However, due to its current application, it is misleading to claim that AI will fundamentally change the pharmaceutical industry as a whole. However, there are several possibilities.
One of the key applications for AI is marketing. As marketer Sydney Tierney explains, AI in marketing will allow pharmaceutical companies to make it easier for patients to find the right medication. The company Ingenious Med has created an AI-based platform which allows patients to compare the different options available for different diseases.
Pharma companies are seeking to use AI based solutions to improve the engagement between physicians & pharma representatives. AI based compliant text messaging solutions like Zing by P360 improve engagement between Physicians and Pharma Reps by upto 67%. This increased engagement helps you to plan and allocate your resources like manpower, Inventory stocks, promotional messages & other resources more efficiently. This improved engagement also results positively in scheduling & planning meetings with physicians more effectively resulting in higher face to face planned meetings. The better HCP & Pharma rep engagement in return results in better ROI on your marketing spending thus positively. For more information on HCP Engagement you can visit this link.
In the pharmaceutical industry, decision makers and professionals who make important drug decisions, such as pre-approval or full approval decisions, rely heavily on statistical models and models that are used to monitor key performance parameters. However, these are often unable to take into account all of the additional variables and concerns that arise in different markets. Artificial intelligence (AI) is being integrated into factories across the world, enabling robots to have an increased understanding of their environments and the environment within which they operate. From analyzing data, to planning and optimizing equipment performance, the final product can be safer, more efficient, and reach its target market much faster.
The use of AI in drug trials is still fairly limited, but some experiments have already shown promising results. In 2016, a US research group attempted to reduce the risk of dosing error by analysing data from historical drug trials using machine learning algorithms, that is, software that learns with data rather than relying on pre-set functions.
Machine learning can help the researcher to sort through large amounts of data to uncover patterns and trends in patient groups in an attempt to predict drug performance. Such algorithms have been known to outperform human experts when tasks such as classification and regression are concerned.
New technology and software seem to be the norm these days. This is an environment in which the pharmaceutical industry is doing quite well. AI is just one example of a technology that promises to greatly improve the functioning of pharmaceutical companies. This is a technology in which we can expect to see dramatic change over the coming years. Understanding this will help us to understand how this technology is affecting the pharmaceutical industry.
Given the diverse activities of pharmaceutical companies it is no surprise that AI technology is of great importance to the industry. This technology is expected to improve the performance of pharmaceutical companies across many areas like Compliant Communication with Physician, Patient Trials, Patient Data Management Clinical Trials.
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