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Nowadays, the fast development of hardware for IoT-based systems creates appropriate conditions for the development of services for different application areas. As we know, the large number of multifunctional devices, which are connected to the Internet is constantly increasing. Today, most of the IoT devices just only collect and transmit data. The huge amount of data produced by these devices requires efficient and fast approaches to its analysis. This task can be solved by combining Artificial Intelligence and IoT tools. Essentially, AI accelerators can be used as a universal sensor in IoT systems, that is, we can create Artificial Intelligence of Things (AIoT). AIoT can be considered like a movement from data collection to knowledge aggregation. AIoT-based systems are being widely implemented in many high-tech industrial and infrastructure systems. Such systems are capable of providing not only the ability to collect but also analyse various aspects of data for identification, planning, diagnostics, evaluation, monitoring, optimization, etc., at the lower level in the entire system's hierarchy. That is, they are able to work more efficiently and effectively by generating the knowledge that is needed for real-time analytics and decision-making in some application areas.

Objectives: To analyze the rationality of central nervous system fixed dose combinations used in a tertiary care hospital. Methodology: The study was an hospital based observational study. The data was collected from an annual drug compendium entitled “Hospital Drug List”. Fixed dose combinations (FDCs) enlisted in central nervous system (CNS) sections were selected for the study purpose. The active pharmacological ingredients (APIs) in FDC was checked for approval by Drug Control General of India (DCGI), World Health Organization (WHO) and essential medicine (EML)/national essential medicine list (NEML),both or none and all the ingredients (molecule, excipients) present in the FDC was checked whether banned or under any controversies in India as well as worldwide.  Efficacy and safety of the individual active pharmacological ingredients (APIs) and their combination were searched. Details of each drug were collected [Generic name, Pharmacokinetics, Interaction affected, Pharmacodynamics, and Advantages of FDCs]. The data collected was analyzed by a tool to assess the rationality of fixed dose combinations which is pre-tested and validated by Shah et al., based on WHO guidelines. Result and Discussion: A total of 25 CNS FDCs were taken, on assessment of CNS FDCs 21 (84%) were found to be rational and 4 (16%) were found to be irrational with the mean rationality score of 7.2. By winding up, state of nonbeing, absenteeism of legality and effectiveness of the formulations appeared in to a peculiar combinations and inadequate practice. The approval process of these combinations by various committees should be robust. Keywords:  Rationality; Fixed Dose Combinations; CNS Drugs; Safety and Efficacy.

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