Over 10 years experience of Traceability Solutions
By pharmatrax
Category: Technoloy
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The history of Artificial Intelligence (AI) dates back to 1903, when Bertrand Russell published the book The Principles of Mathematics, that depicted the intersection between mathematics and logic in a way that drew resemblance to the manner in which artificiality and intelligence currently exist.
Active research in this field began in 1950s by Minsky and Turing, who later became the fathers of modern AI.
And when John McCarthy first devised the term Artificial Intelligence at a conference in 1955, opinion was divided on its benefits. Many people were also just incredulous and resignedly thought that AI would have no value beyond the frontage of Silicon Valley.
AI systems already play a central role in high tech areas such as the development of driverless cars and facial recognition software.
Data Science (DS) – a limited variation of AI – is a syndicate of mathematics, statistics and computer science, and develops algorithms for extracting insights and knowledge from data.
DS is like “the brick wall” of AI, driving optimal innovations through the discovery of patterns that can be translated into insights as well as determining the statistical likelihood of certain outcomes of a process or operation.
And in the fusion is the Machine Learning (ML), which futurists like Bernard Marr have described as “building algorithms capable of being trained on data, rather than specifically trained by a human on how to carry out a task”.
While the synonymy of the three terminologies often draws a heated debate, consensus exists that each are irreducible minimums in the futuristic workplace. Companies are capitalising on them to tap into their benefits.
The global pharma market is set to be worth $1.6 trillion by 2020.
As a result pharmaceutical companies are scrambling to build momentum with technology.
According to Emerj study on healthcare industry, executives currently using AI revealed, over 50 percent anticipate broad scale AI adoption by 2025.
Pharma companies have developed partnerships with AI companies to, among other things, upscale virtual patient coaching for individuals undergoing joint replacements and spine surgeries and rehabilitation support to improve patient outcomes, improve cancer research by helping through the discovery of new drug targets, and use the machine learning pipelines to convert high volumes of cancer patient data into computer models that can be used to identify novel targets for cancer therapy.
Experience shows that companies that use AI to orchestrate a cohesive customer experience will drive stronger competitor differentiation, better customer access and higher sales impact for benefits like revenue and profit.
In other words, companies that empowers their representatives with technology will gain better insights from patient demographics analysis, market forecasts, predictive market analysis, gaps analysis for drug launches .
Technology “augments” the human intelligence, and “multiplies” the impact of traditional sales skills.