Generics must not be imperiled over data protection: Satish Reddy, Chairman, Dr Reddy's Laboratories

India shouldn't accept regulatory data protection in a way that weakens its globally competitive generics industry only to attract investments, Dr Reddy's Laboratories chairman Satish Reddy told ET. He also spoke about India's innovation gap with China, AI-driven drug discovery, and reforms needed to accelerate R&D. Edited excerpts:

Where does India's pharma innovation ecosystem stand now?
The Indian pharmaceutical industry is largely generics-based, but India has also shown promise in innovation capability. We are increasingly seeing positive outcomes with novel drugs like Wockhardt's Zaynich and Zydus's desidustat and saroglitazar. But the larger innovation ecosystem still requires more development. We have issues like funding, infrastructure, regulatory, and talent. So, while we have strengths, the ecosystem is still a work in progress.


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What is the biggest bottleneck in building this ecosystem?
Funding is available through ANRF (Anusandhan National Research Foundation), PRIP (Promotion of Research and Innovation in Pharma MedTech Sector), and other schemes, but what is required is stage-appropriate capital. The problem is not just more money. The problem is how that money is structured at different stages. Startups, for example, go through initial discovery, then lead optimisation, then preclinical, and clinical stages. When they move into that transition, that is where the difficulty starts. They have made progress in the initial stages, but to move to the next stage, they get stuck.

What structural changes are needed most urgently?
We have all the elements, but they are not connected. We have research institutions, industry, and funding schemes. But is there continuous dialogue between institutions and industry? Frankly, no. Even large institutions like AIIMS, Tata Memorial, CMC Vellore do good work.

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India-China Collaboration
But are they integrated into drug discovery in a structured way? Not really. Even within hospitals, there isn't enough collaboration with industry on drug discovery. The issue is fragmentation. Unless these things come together, industry alone cannot anchor it. It requires orchestration. China and South Korea treated it as a national mission. In India, we are still not organised at that level.

What is your view on regulatory data protection and FTAs?
As far as regulatory data protection is concerned, we have taken a position through industry associations. We are saying India should not accept it in a way that weakens our ability to compete in generics. We are a generics-based industry. We don't want that strength to be compromised. As long as safeguards are in place for generics competitiveness, then only we can consider next steps. Otherwise, there is always a risk that it can be used to block competition. From the multinational side, it cannot be framed as "we will bring innovation only if this is sorted out." Innovation is already coming into India. It does not stop them from launching products here. They're more worried about our generic competitiveness, because we're way ahead in that. So, why would we want to compromise?

What role can reimbursement or public procurement play?
It is one of the important elements. If you look at China, they created a system where once innovation happens, there is a defined market through government procurement. That gives certainty. In India, we have CGHS (central government health scheme) and state procurement, but it is not structured to incentivise innovation. If you develop a product, there must be at least a predictable market, especially for innovative products.

Why are listed companies constrained in investing more in innovation?
Listed companies have a primary duty towards shareholders. Even if they invest in innovation, shareholders expect returns. But early-stage R&D doesn't generate immediate returns. So, there is a mismatch. Innovation is long-term, but capital markets are short-term in evaluation. We have taken big steps in drug discovery for decades, but success takes time. So, the limitation is structural. It is not about intent. It is about how markets reward risk.

Why is industry-academia collaboration still weak?
The issue starts with objectives. What is the common objective between academic institutions and listed companies? Industry wants discovery, development, clinical trials, and commercialisation. That is a very focused objective. Academic institutions may have different goals. There is no natural alignment. Even within government institutions, governance and financial systems are not structured for scale. Unless objectives align, collaboration will remain limited.

You mentioned the idea of "affordable innovation" for India and China. Could this be an area for deeper collaboration?
Yes. My father (DRL founder Dr Anji Reddy) spoke about this 15-20 years ago - can India and China innovate for one-third of the world's population with affordable products, instead of relying on expensive multinational innovation? That thought came back after reading a recent paper. We already collaborate at the company level on innovative assets. Perhaps there's scope for country-level collaboration too, especially for diseases unique to our region where affordable innovation is essential.

What will be your ambitious number of products at scale and in how many years?
There is an industry aspiration of 100 innovative launches by 2047. But that will not happen unless we fix regulatory systems, build regulatory science capability, and create an integrated ecosystem. China took that responsibility, started everything from 2015 onwards and orchestrated the whole thing. The biggest advantage it has is in terms of the regulatory system and pathways to get to a global clinical trial. All these things are something that we need to put into place before we can say we can get to the scale like what China's been able to do.

What is the role of AI in drug discovery?
AI is expected to have a significant impact, but it will take time. Initially, it is already helping in clinical trials-patient recruitment, regulatory processes, efficiency improvements. Next stage will be discovery and development, including AI-designed drugs. But regulatory systems have to evolve. You cannot bypass human judgment. You still need oversight at every stage. So, it will be transformative, but not overnight.