The power of AI is the future of pharma

As a part of Express Pharma’s January 2023 cover story, Saransh Chaudhary, President, Global Critical Care, Venus Remedies, and CEO, Venus Medicine Research Centre, shares his views below.

New-age technologies like Artificial Intelligence (AI) and Machine Learning (ML) are poised to play a transformational role in the growth of the Indian pharma industry by expediting drug development and discovery and enhancing efficiencies. While leading global pharma giants have already started using AI in a big way, Indian pharma majors are also fast catching up.

AI, coupled with big data and ML, is veritably the future of pharma. Encompassing all pharma processes ranging from drug research and manufacturing to marketing and supply chain management, AI applications are proving instrumental in bringing down costs, supporting a profit-driven innovative ecosystem and enhancing productivity, thereby, business outcomes, as more and more Indian firms jump on the digital bandwagon.

They have started leveraging the power of AI by analysing vast amounts of data to improve business processes through decisive insights, boost the success rate of new drugs through quality control and address supply chain issues in the production line, thus cutting down on wastage. AI tools also help minimise the scope of human error to ensure greater efficiencies, reduce operational costs through predictive maintenance and make way for more cost-effective drugs by streamlining the working processes. Evidently, AI-powered analytics can go a long way in improving the value proposition by creating innovative business models.

Pharma companies are also increasingly using AI to streamline the drug discovery process by simplifying the practice of identifying complex patterns from datasets to assess the safety and efficacy of drug candidates and applying them to solve problems involving complex biological networks. The predictive and data analytics capabilities of AI enable drug researchers to assess the implications, benefits and success rate of new drugs by analysing dataset patterns.

Likewise, machine learning also plays a crucial role in real-world evidence studies and clinical trials through techniques like few-shot learning, which involves inferring the results on the basis of restricted data in the process of testing experimental drugs and zeroing down on drug candidates with the highest potential. These technological interventions not only do away with the need for large datasets, but also put the drug discovery and development process on fast track.

Going beyond drug discovery, AI can also help analyse and improve upon marketing campaigns by providing measurable results and accurately predicting the success rate of marketing activities. Likewise, it is redefining the scope of interactive digital tools in the consumer healthcare space.

Companies catering to consumer healthcare are increasingly opting for data-driven personalisation and immersive technologies like Virtual Reality (VR) and Augmented Reality (AR) to enhance patients’ experience by interacting with them and providing solutions based on their feedback. Automated patient-decision aids, for instance, employ cognitive AI with evidence-based insights gained from patient history or interactive questionnaires to understand the critical issues that need to be discussed with physicians. Going a step further, we also have technologies like precision health, virtual health assistant and emotion AI, also referred to as affective computing, which will also be crucial in improving targetted and personalised care for critical diseases, another key area that will witness an upward trend in coming years.

To read more stories in the January 2023 edition, read our digital issue at:

pharma playbook 2023Saransh ChaudharyVenus Remedies
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  • soundos

    thanks for sharing for all info!