Annual Pharma Manufacturing & Automation Convention

About this event

The 8th Annual Pharma Manufacturing and Automation Convention, co-located with the Pharma Manufacturing & Automation Excellence Awards 2026, is set to take place at the Hyderabad International Convention Centre. This highly anticipated event aims to address the rapid evolution in the pharmaceutical industry, which is driven by technological advancements, regulatory changes, and an increasing demand for quality and innovation. The convention's theme, 'Lean, Clean, and Digitally Mean,' emphasizes the importance of lean manufacturing principles, the establishment of precise processes for consistent quality, and the strategic adoption of digital technologies in the industry.This convention offers a unique platform for over 250 decision-makers and influencers from both international and Indian pharmaceutical sectors to network, share insights, and foster collaboration. Attendees can expect interactive sessions led by expert speakers, real-world case studies, and discussions on the latest advancements in technology. Eminent speakers include industry leaders such as the Global Head & VP of Operations Strategy & Excellence, Chief Information Security Officer of Natco Pharma Limited, and Senior Vice President of various manufacturing sectors. The event promises to engage participants through Q&A sessions, networking receptions, and showcases of advanced technology demonstrations, ensuring that everyone from CxOs to mid-level management can benefit from the discussions and knowledge shared. Participants have expressed high satisfaction with previous events organized by Eminence Business Media, highlighting the quality of the speakers and the organization of the sessions. With a focus on current industry needs, such as automation and advanced analytics, the event aims to provide valuable insights and foster meaningful discussions that can potentially shape the future of the pharmaceutical manufacturing landscape. The positive feedback reflects the event's strong relevance to t