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Indian pharma faces decline in R&D productivity, patent expiries, turns to AI to mitigate challenges
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Nandita Vijayasimha, Bengaluru
January 29 , 2025
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Indian pharmaceutical companies are grappling with significant challenges, including declining R&D productivity, patent expirations, and increased scrutiny from global regulators. To address these issues, many firms are turning to artificial intelligence (AI) as a strategic tool to enhance operational efficiency and innovation.
According to Pratyush Kumar, senior director, Tiger Analytics, AI is poised to deliver significant value to the pharma industry. From lab to the market, AI is poised to revolutionize how we discover, develop, and deliver medicines.
Accelerating drug discovery, AI can identify promising drug candidates by predicting molecular properties, generating novel molecules, and assisting in preclinical testing. It helps researchers summarize scientific literature, select the most promising indications for drug candidates, and identify optimal patient populations and trial sites. There is improved trial efficiency as it can identify early warning signals, and automate documentation and reporting.
In the area of medical & regulatory compliance, AI can help pharma companies monitor evolving regulatory landscapes and automate regulatory submissions. It improves medical communication.
Coming to manufacturing & supply chain, AI streamlines sourcing processes by generating Requests for Proposals (RFPs), purchase orders (POs), and invoices, while recommending the most suitable sourcing partners and optimizing negotiations. It can improve manufacturing processes through predictive maintenance, deviation management, and adherence to Good Manufacturing Practices (GMP). The AI-powered ‘control towers’ can provide end-to-end supply chain transparency, optimize cash flow, and improve overall service levels, he said.
In commercialization for targeted marketing, AI can identify the most relevant Healthcare Professionals (HCPs) and patients for each brand and personalize engagement through optimal channels. It helps to optimise spending helping companies select the most effective marketing channels and develop the right pricing strategies. It can optimize sales efforts, provide targeted training, and assist with customer service. It can personalize patient support programs and streamline medical and legal reviews, stated Pratyush.
All said, a successful AI implementation requires a well-defined strategy, robust data infrastructure, a skilled AI talent pool, and an effective operating model that fosters collaboration between data scientists, domain experts, and business leaders. Also comprehensive training programs and effective change management strategies can ensure successful AI adoption and scaling, he pointed out.
Moreover implementing AI responsibly is crucial. The key factors to be considered here are data security & privacy of sensitive patient data. There is need for stringent regulatory compliance by adhering to all relevant guidelines. Further, there is a need to mitigate the potential biases in AI models to ensure fair and equitable outcomes.
Noting that AI is not a silver bullet, but it has the potential to transform the pharmaceutical industry in profound ways, Pratyush said by embracing this technology responsibly and strategically. “We can accelerate the discovery of new treatments, improve patient outcomes, and usher in a new era of innovation in healthcare with AI.”
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