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Diabetes also called as diabetes mellitus is a health issue which affects more people in a world. Diagnosis of diabetic problem depends on different parameters and requires experience or good algorithm to classify it optimally. Many researchers have found different classification algorithms to diagnose this health issue with promising results. In this paper, combinations of whale optimization algorithm and backpropagation neural network methodology are integrated to diagnose diabetes mellitus. This proposed method supports high convergence speed and improved accuracy. Due to this combination, local minima trapping problem which affects the quality of the solution is totally reduced. In the proposed methodology, Whale optimization technique develops new solutions in solution space and backpropagation algorithm finds the globally optimal solution. Experimental analysis compares the proposed methodology with other algorithms and finally concludes the proposed algorithm outperforms other methodologies.

A swarm is a large number of homogeneous, uncomplicated agents collaborating locally among themselves, and their circumstances, with no central control to allow a global interesting behaviour to emerge. Swarm based algorithms are nature inspired, population based algorithms that are clever in producing optimal solution for several complex and combinatorial problems. In the pharmaceutical industry, the product and other process development problems usually involve a numerous of independent variables and it incorporated with multiple constraints. To solve problems related to pharmaceutical industry requires accurate result and it's very hard to solve using traditional method. Swarm based intelligence technique is a collection of knowledge based algorithms which having capable of solving complex problems and can obtain optimal or accurate solution. This paper discusses swarm based intelligent algorithms to solve different pharmaceutical field related complex problems such as drug design, pharmacovigilance, alignment of sequence etc.