Artificial Intelligence (AI) and Biomanufacturing

Syllabus: GS3/Role of IT; Science & Technology

Context

• As global industries increasingly leverage AI for precision-driven bioproduction, India’s efforts are becoming more evident, though challenges remain, particularly in policy frameworks and innovation.

What is Biomanufacturing?

• It involves the use of living cells and biological systems to produce commercial goods — ranging from life-saving vaccines and biologics to biofuels, enzymes, biodegradable plastics, and advanced materials.
• The convergence of synthetic biology, artificial intelligence, and industrial biotechnology has expanded its scope across sectors including healthcare, energy, food processing, and materials science.
• India produces over 60% of global vaccines, showcasing its industrial biomanufacturing strength, and India is often termed as the ‘Pharmacy of world’.

Role of AI in Biomanufacturing

• AI-Powered Process Optimization: AI-driven automation can adjust variables such as temperature, pH, and nutrient supply, improving efficiency and reducing costs.
• Accelerated Drug Discovery & Biopharmaceutical Production: AI expedites molecular modeling, allowing researchers to predict protein structures and optimize drug formulations.
  • In vaccine production, AI helps analyze genetic data to design mRNA-based vaccines more rapidly, improving pandemic preparedness.
• Predictive Maintenance & Smart Manufacturing: AI can forecast equipment failures in biomanufacturing plants, reducing downtime and optimizing resource utilization.
  • AI-enabled robotics assist in precision tasks such as bioassembly and cell culture handling.
• Supply Chain & Logistics Optimization: AI-driven platforms enhance the transportation and storage of biological products by predicting demand fluctuations and optimizing cold-chain logistics.
  • Blockchain integration with AI ensures transparency in biomanufacturing supply chains.

Challenges in Policy and Regulation

• Data & AI Integration Gaps: AI-driven biomanufacturing requires large-scale bioinformatics infrastructure, predictive modeling tools, and real-time analytics.
  • India’s AI in biotech regulations remains fragmented, posing hurdles for seamless integration.
• Funding & R&D Ecosystem: Biomanufacturing demands high capital investment, particularly for AI-driven automation and synthetic biology research.
  • While initiatives like Biotechnology Industry Research Assistance Council (BIRAC) support innovation, private sector participation remains limited compared to nations like the US and China.
• Intellectual Property & Ethical Regulations: AI-generated biotech innovations challenge traditional patent laws.
  • India needs to clarify IP regulations on AI-assisted bioengineering, ensuring ethical practices without stalling innovation.
• Manufacturing Scalability & Workforce Upskilling: AI-powered biomanufacturing requires advanced robotics and computational biology expertise.
  • Upskilling initiatives must align with demand, fostering an AI-ready workforce.

Key Government Initiatives

• National Biotechnology Development Strategy: Focuses on bioindustrial growth, but AI integration requires more direct incentives.
  • India hosts over 5,300 biotech startups (as of 2024), and aims to scale this to 50,000 by 2030.
• National Biomanufacturing Policy (Proposed): The Department of Biotechnology (DBT) has drafted a policy to promote indigenous biomanufacturing capabilities, reduce dependence on petrochemicals, and enhance sustainability.
• Biomanufacturing Mission (2023): It aims to support R&D, scale bio-based industrial production, and attract global investments.
• PLI Scheme for Biotech: It incentivizes domestic production of biopharmaceuticals, enzymes, and fermentation-based inputs.
• Regulatory Framework for AI & Biotechnology: Addressing ethical concerns, data security, and AI-powered genetic research will be crucial.
• Academic-Industrial Collaboration: Leading institutions like IISc, IITs, and DBT-supported Biotech Parks have become innovation engines for biomanufacturing solutions.

Policy Recommendations

• Establish AI-Biomanufacturing Regulatory Framework: A dedicated policy mechanism for AI-driven bioengineering can streamline approvals and address ethical concerns.
• Enhance Public-Private Partnerships: Encouraging private investments in AI-powered biomanufacturing can accelerate infrastructure development.
• Strengthen AI & Biotech R&D Ecosystems: Increased funding in genomic AI, predictive biomanufacturing tools, and quantum-powered bioinformatics can drive next-gen solutions.
• Develop AI-Based Compliance Tools: AI-assisted tracking and regulatory automation can enhance safety protocols while ensuring ethical biotech applications.

Road Forward

• Strengthen biofoundries and shared infrastructure for rapid prototyping.
• Promote public-private partnerships to de-risk R&D and scale-up investments.
• Foster green supply chains using circular economy principles.
• Streamline approval and IP frameworks for synthetic biology and AI-driven innovations.

Source: TH