Since the dawn of the third industrial revolution in the late 1940s, mammoth industries like the pharmaceutical sector have been exploring avenues to not just collect data but to harness it and use it as a powerful tool for driving efficiency, improving decision-making and accelerating innovation. Connected devices and the Internet of Things (IoT) have made it possible to harvest large amounts of data from each stage of production using sensor-equipped hardware and smart factories to collect, sort, and analyze this data in real time. The adoption of Artificial Intelligence and Machine Learning (AI/ML) technologies has catapulted pharmaceutical research, testing, and production to new frontiers, offering even better predictive capabilities, enhanced accuracy, and accelerated development cycles.
Also, the volume of data continues to expand, ensuring its quality remains paramount to the pharmaceutical industry as regulatory bodies have highlighted the necessity of adhering to industry-standard data practices to ensure data integrity, product quality, and patient safety. With the introduction of 'traceability' to the ALCOA+ principles, now enhanced to ALCOA++, maintaining comprehensive and transparent records has become even more critical, ensuring that every data point can be tracked and verified throughout the production process.