Artificial Intelligence – An Innovator in the Pharma Industry
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Abstract
Since the late 1980s, artificial intelligence (AI) has advanced quickly. The performance of healthcare datasets has increased, and during the past 20 years, articles on AI have advanced exponentially. On the other hand, more AI devices became available as processing power expanded. Artificial Intelligence consists of two primary tools: machine learning, which analyses structured data (such as pictures, EP, and genetic data), and natural language processing, which analyses unstructured data. Over the previous 20 years, both AI devices' techniques, algorithms, and applications have undergone tremendous improvement. Nonetheless, there have been several recent attempts and novel applications of AI, and a small number of illnesses, including cancer, diseases of the brain system, heart disease, liver disease, congenital cataract disease, etc., may be examined via AI. Deep learning, an advanced technique, is currently driving the AI boom, and significant changes to diagnostic medical imaging systems, including those used in dermatology, pathology, and endoscopic diagnosis, are anticipated soon. Over the past several years, the application of artificial neural networks (ANN) for classification, modelling, and forecasting of various factors linked to cattle productivity in the livestock and associated sectors has led to an exponential expansion in the use of ANN. From determining the milk yield of Deoni Cows to its application in Neurology highlights the growth of application of Artificial Intelligence in the Pharma Industry. Even though there has been such tremendous development and application of AI in the pharmaceutical industry, the laws governing the same are yet not matured. There are questions raised with respect to the ownership and authorship of the work that may be created using artificial intelligence and that may be created by the Artificial Intelligence. The author of this paper has analysed the importance of Artificial Intelligence in the realm of Pharmaceutical industry, highlighting the challenges faced due to the dearth of legal provisions governing this sector. Further, the author has provided recommendations to strengthen the current system of AI for the purposes of better usage, accountability and propagation.