Andhra Pradesh Pharmacy Colleges to Introduce AI, Python, Machine Learning in BPharm From 2026-27

Under the revised curriculum, students will be introduced to Python programming during the first semester, followed by subjects covering biostatistics, data analytics and basic computer operations. A dedicated machine learning course will be introduced in the third semester, while the sixth semester will focus on AI applications in pharmaceutical sciences and computer-aided drug design. The curriculum progressively builds technology-related competencies throughout the BPharm programme.

The technology component becomes more extensive during the seventh semester, when students will study AI in clinical applications, pharmaceutical automation and modern analytical techniques. In the final semester, the curriculum will cover the ethical and translational applications of AI in pharmacy. Students will also have an option to study AR/VR-based Pharma 4.0. Other technology-oriented areas incorporated into the programme include process analytical technology (PAT), quality-by-design (QbD) and advanced analytical methods.

The revised curriculum is designed to progressively take students from basic programming and data skills to machine learning, AI, automation and emerging digital technologies used in pharmaceutical research and manufacturing. Prof. L Srinivas, principal of GITAM School of Pharmacy, said the revised programme places greater emphasis on making pharmacy education industry-oriented, with increased focus on automation, quality control and emerging technologies. He said the objective is to provide students with direct practical exposure and develop skills relevant to the changing requirements of the pharmaceutical and healthcare industries.

The curriculum also strengthens the industry and practical training component. Every student will be required to complete at least 240 hours of practical training over two semesters. The training can be undertaken in a pharmaceutical or food industry, hospital or community pharmacy. The structured practical exposure forms part of the revised curriculum's focus on preparing students for professional requirements beyond classroom-based pharmacy education.

Dr Narendra Devanaboyina, a Pharmacy Council of India Central Council member, stated that the coursework has been designed to enable students to handle large healthcare datasets, conduct advanced biostatistical analysis and participate in modern digital drug research. He also highlighted the structured 240-hour internship and mandatory final-year research projects included as other mandates under the revised framework.

To strengthen institutional compliance and accountability, the PCI has also formulated guidelines for implementing Aadhaar-enabled biometric attendance systems across all approved pharmacy colleges, according to Dr Devanaboyina.

The AI component of the revised BPharm curriculum extends beyond basic exposure to artificial intelligence. Students will learn about AI model development, validation, auditing, explainable AI and regulatory requirements. The curriculum will also demonstrate applications of AI in areas such as automated dispensing, inventory forecasting, pharmaceutical supply-chain management and public health data analytics.

The programme will further use guided projects to expose students to practical applications, including adverse drug reaction prediction, quality-control failure prediction and demand forecasting. These areas are intended to connect the technology component of the curriculum with applications relevant to pharmaceutical and healthcare operations.

The revised curriculum also introduces students to precision medicine and advanced drug-delivery technologies. The areas specifically included are nanocarriers, microneedles, targeted drug delivery and controlled-release systems. In addition, quality-by-design, process analytical technology and regulatory science have been incorporated into drug development-related learning.

The curriculum is structured to combine conventional pharmacy education with emerging digital and technological disciplines. From Python and data analytics at the beginning of the course to machine learning, AI-driven pharmaceutical applications, automation, advanced analytical techniques and digital drug research in later semesters, the revised programme introduces technology progressively throughout all eight semesters.

The practical component additionally requires students to undertake 240 hours of training across two semesters, while the programme includes mandatory final-year research projects. The curriculum also addresses areas such as AI model validation and auditing, explainable AI, regulatory requirements, pharmaceutical supply-chain management, public health data analytics and technology-enabled drug development.

ET reports that Andhra Pradesh pharmacy colleges would roll out the AI-integrated BPharm curriculum from the 2026-27 academic year. The report highlighted the PCI-developed curriculum's alignment with NEP 2020 and its integration of Python, machine learning, AI applications, automation, data analytics, practical training and emerging pharmaceutical technologies.

The revised BPharm curriculum will consequently bring AI, data analytics, programming, machine learning, automation, advanced drug-delivery technologies, regulatory science and industry-based practical training into pharmacy education across Andhra Pradesh from 2026-27. It also combines a structured 240-hour practical training requirement with final-year research projects and exposure to AI applications ranging from drug development and adverse drug reaction prediction to inventory forecasting, automated dispensing and public health data analysis.