<p>Clinical trial is the key approach for studying the effectiveness of a drug or a medical equipment. In the recent years several drugs which were available commercially, were found to be inefficient and they were banned in many countries. These insights point towards the need for cross checking the credibility of clinical trials being conducted. This paper considers the drawbacks in medical data collection. In the proposed work, we have used an improved lion optimized SDN (Software Defined Network) controller for the efficient data collection by the IoT medical devices. A possible architecture for addressing problems related to the data evaluation and analysis is edge computing. For improving the data processing speed of IoT devices in a clinical trial system, edge computing is affordable and can offer low latency data services. Load balancing, network optimisation, and effective usage of resources are precisely carried out in the proposed clinical trial scenario employing adaptive software-defined network (SDN). The low-powered medical IoT IOT devices are susceptible to many safety hazards, as are the information that they are linked to (personal, confidential patient information). The Edge processors of the suggested architecture employ a straightforward method of authentication to confirm the IoT devices and users in order to establish a secure environment for SDN-facilitated computation in an internet of things medical facility. Following identification, the gadgets gather clinical information then send it to nearby servers for handling, storage, and evaluation. The Edge servers have connections to an intelligent SDN controller that controls distribution of load, system optimization, and efficient resource use in the medical sector. Improved Lion Optimization (ILO) algorithm helps the SDN to make intelligent decisions. Performance of the suggested framework is evaluated using software simulations.</p>