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Artificial Intelligence (AI) revolutionary in biotechnology and molecular biofilm in drug discovery, customized medicine and treatment discovery. AI and advanced analysis help researchers to create new treatments such as antibody-drug links (ADCs), gene editing tools and cell-based treatments.
As far as India is concerned, it is a great opportunity to go beyond the “pharmacy of the world” for common drugs and becomes a leader of biomass invention.
With strong government support in the AI infrastructure, renewed regulations and industrial corporation, India can strengthen its position in the pharmaceutical industry.
However, challenges such as efficiency deficiency, ethical concerns and fair access to these advanced treatments must be solved.
AI’s transformation impact on biotechnology and molecular biology
The AI drug finds quickly and cheaply by improving research methods. Scientists use AI to enrich treatments for diseases such as diabetes and tendon dystropi, and continue to improve results by data analysis.
AI protein structures can also be predicted, helping researchers to find new drug targets without many years of testing and error. It is very useful for complex drugs like ADCS, where AI helps to determine the best antibodies and sizes.
AI also improves genetic-editing techniques such as CRISPR-CAS9 and CAR-T cell therapy by predicting unnecessary side effects, and treatments for diseases such as sickle cell anemia. In India, companies like Biocon and Sun Pharma are using AI to accelerate pharmaceutical screening and find new applications for existing drugs.
The fusion of AI with molecular biology creates customized treatments based on a person’s unique genetic cosmetics. Advanced AI models can analyze large biological data set to detect disease markers, and doctors help to choose the right treatment for conditions such as cancer and rare genetic disorders. For example, AI-running tools can combine genetic data with medical records to quickly diagnose diseases and reduce delays in treatment. India is progressing in genes with projects like the Zenom India project.
However, India needs the best AI systems that can handle large -scale genetic data while keeping the patient’s information safe to benefit from these improvements.
Pharmaceutical Department of India: Current strengths and strategic impacts
India provides 60 percent of the world’s common drugs, which are supported by strong API production skills and low cost production. However, this strength is increasingly threatened by prices and regulatory studies in major markets such as the US and the European Union.
High credibility (75 percent of revenues) on the generics of the sector is under competition in countries such as China and South Korea, which is aggressively investing in AI-motivated drug discovery.
Indian companies are also progressing in biosymillars, more than 100 products in development target cancer and autoimmune diseases. Biogan’s Drastujuma Biosimillar and Dr. Reddy’s Redouximap Biosimillar highlights this progress. However, the novel requires AI tools for target verification and pharmacinetic modeling – it is more than global colleagues.
Although the Rs 10,300 crore allocation of the Indian Mission for GPU infrastructure and database is a favorable step, the inequalities are prolonged. Most drug SMEs do not have access to AI/ML workloads required for high -performance (HPC) clusters.
Regulatory structures are also backward; For example, India’s regulatory structure for AI-based medical examinations is still being developed, and does not have the clarity and structure found in the US Food and Drug Administration (FDA) guidelines. The FDA has established a well-defined structure as a medical device (SAMD) for the software (ML) software, which provides specific rules on how to create, test, recognize and monitor AI-operated medical technologies. This ensures that AI-based medical equipment maintains protection, transparency and efficiency when it is continuously improved.
On the contrary, India has introduced ethical guidelines for AI in Health Safety through the Indian Medical Research Council (ICMR), focusing on policies such as informed approval, data privacy and dependence.
However, these guidelines do not provide specific instructions on how to design, test or recognize AI-running medical devices. The lack of a structured regulatory structure creates uncertainty for researchers and companies, slowing down innovations and making India compete in global AI-driven health advances.
Without clear regulations, AI-based medical tests in India face challenges in consent, compliance and international cooperation. India needs a structured regulatory system that balances novelty with the patient’s safety and ethical AI application, to fully use the AI capacity in the health sector.
Strategic Integration of AI: Paths to India
The Indian database should prioritize the site to manage the anonymous gene, prote, and medical test data from various Indian people. Cooperation with hospitals and research institutions can follow the UK Bio Bank, creating a source of teaching of India’s disease burden (e.g., tuberculosis, diabetes) designed AI models.
India AIVE Innovation Center (IAIC) must be a partner with Pharma Giants and Elementary Companies to create basement samples for drug discoveries. Focusing on Edge computing can be democratic to AI tools in rural areas, which enable disseminated medical tests for neglected tropical diseases.
It is very important to expand AI literacy through programs. Integration of AI blocks in pharmacy and biotechnology curriculum, establishing certification programs for AI-Octat Drug Production and Creating Protocol Review Boards to oversee AI applications in important areas such as Germanline Editing.
What should India do?
First, the government should triple the R&D costs, and the allocation should be increased from 0.7 percent to 2 percent, especially AI and Biotechnology.
Second, to attract international investment, India must modernize its intellectual assets (IP) structure, and fast monitoring patents for drug candidates developed using data uniqueness rules and AI.
Third, domestic innovation must be actively encouraged by providing a tax discount on accepting AI instruments and establishing a Rs 5,000 crore venture fund dedicated to AI-driven biotech startups.
India stands in a crossroad: Innovation economies improves AI to climb a life -value chain or risk space. India emerges as the world’s first AI-running bio-superpass by improving computational infrastructure with pharmaceutical priorities, developing the Education and Education Federation and the principles of forwarding.
Ravishankar is a microbialist, political analyst and commentator. He tweets at Oru_Pavam_Nair.
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