AI In Pharma: A New Perspective

Dipankar Kaul -Head GMP Audits,Asia-Pacific- Novartis Technical Operations, envisages the many ways in which AI can transform pharma manufacturing operations and the present perspective of the science of pharma development, manufacturing and quality assurance

AS THE pharma manufacturing plants operate on computerised/programmable logic-controlled machines, instruments or technologies within fixed operating parameters to produce products of standard quality and specifications, compatibility towards highly automated and robotic machineries is evident. Through integration with AI self-learning machines, these complex operations can be simplified to a greater degree. The further development of these technologies will facilitate ensuring that these operations become more intelligent and efficient; however, they pose a challenge for the policy makers and regulators to redefine our knowledge of the current good manufacturing practices.

Some of the AI applications useful in text, speech, and video recognition can be utilised further to interpret the pattern and convert it into a meaningful and chronological script of events. While this will certainly reduce the time and increase the efficiency, it will also enhance the reporting quality. Machine learning thus employs statistical applications to identify patterns in the data then make predictions using those patterns. The AI lead machine-learning processes are capable of reading and recognising the key process parameters responsible for raising product quality.