CDSCO Issues New Guidance on Regulation of AI-Based Medical Devices in India
The Central Drugs Standard Control Organisation (CDSCO) has issued a guidance document clarifying how software-based medical devices, including those using artificial intelligence (AI), will be regulated under the Medical Devices Rules (MDR), 2017. The move aims to provide regulatory clarity for India's growing digital health sector while ensuring patient safety.
The guidance applies to software products that meet the definition of a medical device under the Drugs and Cosmetics Act, 1940 and MDR-2017. It does not cover software intended only for general wellness, promoting a healthy lifestyle, or measuring body parameters for fitness tracking.
CDSCO stated that the document reflects current practices under MDR-2017 and should not be seen as introducing new regulatory controls. It explains how existing provisions apply to medical device software, including in-vitro diagnostic software.
One key clarification is the distinction between Software as a Medical Device (SaMD) and Software in a Medical Device (SiMD). Standalone software that performs a medical function—such as interpreting scans or assisting diagnosis—will be regulated separately from software embedded in medical equipment. The terminology aligns with principles from the International Medical Device Regulators Forum (IMDRF).
The guidance brings AI and machine learning-based software into the medical device framework when intended for diagnosis, monitoring, prediction, or treatment of diseases. Such products will be classified into risk categories A, B, C, and D based on intended use and potential risk to patients, with higher-risk products facing greater scrutiny.
A lifecycle approach to regulation is adopted, requiring manufacturers to address software design, verification, validation, cybersecurity, updates, maintenance, and post-market surveillance. Clinical evidence must demonstrate safe and effective performance for the intended medical purpose.
A senior Health Ministry official noted that for AI companies, the guidance provides a clearer compliance roadmap from product development to market approval. Developers of AI-based diagnostic and clinical decision-support tools now have defined expectations on risk classification, clinical validation, documentation, cybersecurity, and post-market monitoring. While it may increase regulatory responsibilities, it also reduces uncertainty, improves investor confidence, and could facilitate wider adoption of AI products by healthcare providers.
