IoT systems (Internet of Things) and Artificial Intelligence (AI) have drastically changed and evolved the Pharma Industry in recent years. Connecting patients with healthcare professionals, collecting Real World Evidence (RWE) in real-time, and performing precise analyses to predict trends are some of the benefits of the adoption of advanced technologies. The global pandemic has necessitated an acceleration to this transition and allowed the introduction of tech innovations to improve the Life Science industry.
Healthcare is increasing its focus on patient-centric approaches to improve Clinical Trials and Standard Care. Studies have demonstrated that engaged patients are more compliant with therapy plans and can provide more accurate outcomes about their conditions and drug’s benefits and effects.
The combination of IoT systems and AI technologies creates the perfect ecosystem for Clinical Trials and Standard Care. Smart systems can improve different areas from the patient experience to R&D, from manufacturing to the supply chain.
Application of IoT systems across Pharma Value Chain
IoT can be applied to different areas of the Pharma value chain. In the Research and Development area, wearable devices can be used by study participants to report symptoms in real-time during treatment. In the Manufacturing and Supply Chain, IoT can improve logistics, predict product needs, perform predictive maintenance. For patients, wearable devices can monitor health conditions and can help control therapy adherence by sending push notifications or reminders.
Secure and accessible IoT systems
Data security is a fundamental element in the Pharma industry. Data, collected by IoT sensors, can be remotely accessed through secure platforms to monitor and manage processes and machinery. Privacy and security need to be protected by applying multi-layers measures like isolated networks, blockchain, encryption, firewall integration, and device registration. Using data diodes, that allow unidirectional data flow, is a method to ensure that IoT sensors cannot be affected by outside tampering.
Predictive analysis to improve productivity
Systems failures and machinery breakdowns can negatively impact productivity. But they can be prevented. Sensors located in key positions on machines can collect data that can be reported and analyzed directly by machines. Smart machinery can learn from the collected data and predict failures and prompt operators with the required intervention. By consequence machinery will work more efficiently, reducing time, cost, product wastage, and workforce.
To perform predictive maintenance, smart connected machinery needs to use sensors to monitor key functions and observe if there is a pattern in datasets that can reveal a potential issue for production. Thanks to this, operators can target this pattern earlier and decide how to intervene. Smart machines enable companies to make informed decisions and solve problems in lesser time.
However innovative manufacturing requires complete workforce cooperation to reduce resistance: all the teams need to keep the same pace of technological improvements to ensure a smooth transition from traditional processes to smart and digital manufacturing. Innovate Pharma industry with smart manufacturing can lead it to reach its full potential and improve many lives.
“Predictive analysis is a fundamental topic for manufacturing companies – confirms Sandro Mascetti, CEO at MAS Elettronica – Thanks to IMX8M PLUS and NVIDIA Jetson processors, predictive analysis can be a reality, facilitating its implementation and improving significantly the companies’ results”.
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