1. Introduction

A Digital Twin Patient (DTP) is a computer-generated virtual representation of an actual human patient. It is created using medical records, diagnostic reports, genetic information, medical imaging, wearable-device data, laboratory results and artificial intelligence (AI).

The digital twin attempts to reproduce the patient's biological condition, medical history and physiological behaviour in a virtual environment. It may be used to predict diseases, simulate surgical procedures, test medicines, monitor treatment outcomes and support clinical decision-making.

For example, a hospital may create a digital twin of a cancer patient using MRI scans, genetic information, tumour characteristics and treatment history. Doctors can then simulate different chemotherapy or radiation-treatment strategies before applying a selected treatment to the actual patient.

The central legal question is: Does a digital twin patient acquire an independent legal identity, or does it remain a digital representation of the real human patient?

Under existing legal frameworks, a digital twin patient does not ordinarily possess independent legal personhood. It is generally treated as a data-based technological representation, while the real patient retains legal rights concerning privacy, consent, bodily autonomy, medical confidentiality and access to appropriate healthcare.

This issue is particularly important because digital twins can influence decisions concerning life, health, medical treatment, insurance and patient rights.

2. Meaning and Legal Nature of a Digital Twin Patient

A digital twin patient may be understood through five principal characteristics:

Digital identity: A virtual representation associated with an identifiable individual.

Medical-data identity: It contains personal health information, diagnostic records and biological characteristics.

Predictive capability: It uses computational models to estimate future health conditions.

Simulation capability: It allows doctors to test possible medical interventions virtually.

Decision-support capability: It may influence clinical decisions, treatment recommendations and medical risk assessments.

Legal classification

The legal classification of a digital twin patient involves several overlapping legal concepts.

The important distinction is between the patient's legal identity and the patient's digital representation. A digital twin may reproduce certain biological characteristics, but it does not become the human being it represents.

3. Constitutional and Fundamental Rights of a Digital Twin Patient

The legal rights of a digital twin patient are primarily derived from the rights of the actual patient.

A. Right to privacy – Article 21

Article 21 of the Indian Constitution protects life and personal liberty. The right to privacy is an essential component of this protection.

A digital twin may contain:

Genetic and genomic information.

Medical history and disease records.

Mental-health information.

Reproductive-health information.

Biometric and physiological information.

Predictions about future diseases.

Unauthorised access, disclosure, commercial exploitation or discriminatory use of this information may violate the patient's privacy rights.

Important case:

Justice K.S. Puttaswamy (Retd.) v. Union of India (2017), (2017) 10 SCC 1

The Supreme Court recognised privacy as a fundamental right under the Constitution.

Legal principle: Informational privacy, personal autonomy and control over personal information are constitutionally significant.

Application: A hospital or technology company developing a patient's digital twin must respect the patient's privacy and protect identifiable health information. The judgment does not specifically decide digital-twin rights, but provides an important constitutional foundation for them.

B. Right to informed medical consent

The creation and use of a digital twin may require processing highly personal information and may influence medical treatment.

A patient should be informed about:

What medical information will be collected.

Why the digital twin is being created.

Which organisation will operate it.

Whether information will be shared with third parties.

Whether AI predictions will influence treatment.

Whether information will be used for research or commercial purposes.

How long the information will be retained.

Consent to medical treatment should not automatically be treated as consent to every secondary use of digital-twin data.

Important case:

Samira Kohli v. Dr. Prabha Manchanda (2008), (2008) 2 SCC 1

The Supreme Court of India explained the importance of informed consent in medical treatment.

The Court emphasised that consent must be voluntary and based on adequate information concerning the nature and purpose of the proposed procedure.

Application: If a hospital creates a digital twin for treatment simulation, it should explain the purpose and material risks of that process. Consent for one medical procedure does not necessarily authorise unrelated experimentation or commercial exploitation of the patient's digital representation.

C. Right to bodily autonomy and dignity

A digital twin can predict a patient's likely response to medication, surgery or other treatment. However, a prediction cannot automatically override the patient's decision-making rights.

For example, an AI system might recommend a particular surgical procedure because its model predicts a higher probability of survival. The patient must still receive appropriate information and retain the right to make an informed decision, subject to applicable law.

Digital representations cannot independently exercise the bodily autonomy of the actual patient.

4. Digital Twin Patient Under Indian Statutory Law

Several Indian legal frameworks are relevant to digital twin healthcare.

A. Digital Personal Data Protection Act, 2023

The Digital Personal Data Protection Act, 2023 provides a framework for processing digital personal data.

A digital twin containing information relating to an identifiable patient falls within the broad concept of digital personal data.

Relevant legal concepts include:

Data Principal: the individual to whom personal data relates.

Data Fiduciary: the entity determining the purpose and means of processing.

Data Processor: an entity processing personal data on behalf of a Data Fiduciary.

Consent: a lawful basis for processing where applicable under the Act.

Data protection obligations: requirements concerning lawful processing, security and individual rights.

A hospital may act as a Data Fiduciary, while an external AI company may act as a Data Processor. The actual classification depends on who determines the purposes and means of processing.

Important current-status qualification (6 November 2026): The DPDP Rules were notified in November 2025, but commencement is phased. The principal operational obligations concerning consent, security, individual rights and related processing requirements are scheduled for May 2027. Therefore, they should not all be described as already enforceable.

India Code+3

Until the relevant provisions commence, existing applicable legal requirements remain important, including Section 43A of the Information Technology Act, 2000 and the Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011.

B. Information Technology Act, 2000

Section 43A and the SPDI Rules are relevant to the protection of sensitive personal information handled by covered body corporates.

Unauthorised access, disclosure and security failures involving patient information may also raise issues under other applicable provisions of the IT Act.

C. Digital Information Security in Healthcare Act (DISHA)

The proposed DISHA framework sought to establish specific protections for electronic health information, including confidentiality, privacy, security and controlled exchange.

However, DISHA should not be treated as an enacted, independently enforceable statute. It is important as a policy and legislative proposal rather than an operative source of digital-twin patient rights.

D. Medical Devices Rules, 2017

Under India's medical-device regulatory framework, software intended for specified medical purposes may fall within medical-device regulation.

A digital twin used merely for visualisation or administrative purposes may be treated differently from software that predicts disease, evaluates treatment or provides clinically significant recommendations.

Where the relevant software qualifies as a medical device, applicable requirements concerning classification, licensing, quality, safety and performance become important.

5. Important Case Laws Relating to Digital Twin Patient Legal Status

There is currently no established landmark judgment in India or elsewhere that grants an autonomous legal personality to a digital twin patient. However, several judicial decisions provide principles that can be applied to this emerging field.

Case 1: Justice K.S. Puttaswamy v. Union of India (2017)

Citation: (2017) 10 SCC 1
Court: Supreme Court of India.

Facts and legal issue: The case concerned the constitutional status of privacy and the relationship between personal liberty, dignity and informational privacy.

Judgment: The Supreme Court unanimously recognised privacy as a fundamental right under Article 21 and other freedoms protected by Part III of the Constitution.

Application to digital twin patients:

Medical data requires appropriate privacy protection.

Patient identity should not be unnecessarily disclosed.

Digital health profiling raises constitutional privacy concerns.

Unauthorised exploitation of identifiable medical information may attract legal consequences.

Significance: This case provides the constitutional foundation for protecting the real person whose biological and medical characteristics are reproduced in a digital twin.

Case 2: Samira Kohli v. Dr. Prabha Manchanda (2008)

Citation: (2008) 2 SCC 1
Court: Supreme Court of India.

Facts: The case concerned the scope and validity of consent for medical treatment.

Judgment: The Court explained that valid consent must be voluntary and based on adequate information about the proposed treatment.

Application:

A patient agreeing to ordinary medical treatment should not automatically be considered to have agreed to:

Creation of a digital twin for unrelated research.

Commercial use of the patient's biological information.

Sharing medical data with external technology companies.

Experimental testing using the patient's digital representation.

Significance: The decision supports meaningful patient consent in digital-twin healthcare.

Case 3: Jacob Mathew v. State of Punjab (2005)

Citation: (2005) 6 SCC 1
Court: Supreme Court of India.

Facts: The case involved allegations of medical negligence and the criminal liability of medical professionals.

Judgment: The Supreme Court discussed the standards for establishing medical negligence and distinguished ordinary civil negligence from criminal negligence.

Application:

Suppose a doctor relies on an inaccurate digital twin prediction and administers an unsuitable treatment.

Potential legal questions include:

Did the doctor exercise reasonable professional care?

Was the digital twin scientifically validated?

Did the doctor independently evaluate the patient's condition?

Was the system's limitation known?

Did the error cause the patient's injury?

Significance: The doctor cannot necessarily escape responsibility merely by stating that the AI-generated digital twin supplied the recommendation.

Case 4: Kusum Sharma v. Batra Hospital & Medical Research Centre (2010)

Citation: (2010) 3 SCC 480
Court: Supreme Court of India.

Legal principle: The Court discussed the standards applicable to medical negligence and the need to assess professional conduct against the standards of a reasonably competent medical practitioner.

Application: A hospital deploying digital-twin technology must consider professional standards, system reliability, appropriate clinical supervision and patient safety.

The mere use of advanced technology does not establish that the medical treatment was reasonable.

Case 5: Snitem and Philips France v. Premier ministre (2017)

Citation: Case C-329/16, ECLI:EU:C:2017:947
Court: Court of Justice of the European Union.

Facts: The dispute concerned medical software that processed patient-specific information to identify contraindications, drug interactions and excessive medication doses.

Judgment: The Court held that software performing such patient-specific medical functions could qualify as a medical device even if it did not directly act on the human body.

Application:

A digital twin system that analyses patient-specific data to:

Predict medical complications.

Recommend medication.

Evaluate treatment options.

Detect contraindications.

Assist diagnosis.

may fall within medical-device regulation, depending on its intended purpose and applicable regulatory framework.

Significance: This is an especially relevant judicial authority for determining the regulatory status of digital-twin software.

Case C-329/16+1

Case 6: Dinerstein v. Google LLC (2023)

Citation: 73 F.4th 502 (7th Cir. 2023)
Court: United States Court of Appeals for the Seventh Circuit.

Facts: The University of Chicago and Google collaborated on developing predictive healthcare software using historical patient medical records. The records were described as anonymised. A patient challenged the transfer and use of the records.

Judgment: The appellate court upheld dismissal of the patient's claims, finding that the alleged potential risk of future identification did not establish the required concrete injury in the circumstances presented.

Application:

This case is particularly relevant to digital twins because it raises questions concerning:

Use of patient records for AI development.

Anonymisation of medical information.

Hospital–technology company research agreements.

Patient confidentiality.

Legal injury arising from data disclosure.

Significance: The case illustrates that the legal consequences of using medical records for predictive systems depend on the facts, applicable privacy rules, contractual commitments and proof of legally recognised injury. It does not create a general permission to use patient data without appropriate legal authority.

media.ca7.uscourts.gov+1

Case 7: Montgomery v. Lanarkshire Health Board (2015)

Citation: [2015] UKSC 11
Court: Supreme Court of the United Kingdom.

Legal principle: The Court emphasised the importance of informing patients about material risks of recommended treatment and reasonable alternative treatments.

Application: If a digital twin recommends a high-risk surgical procedure, the doctor should not simply rely on the model. The patient should receive appropriate information about material risks and available alternatives.

Significance: Digital-twin predictions do not remove the obligation to communicate material treatment risks.

6. Ownership and Control of a Digital Twin Patient

One of the most complicated legal questions is who owns a patient's digital twin.

Consider the following example:

A hospital collects a patient's medical records and creates a digital twin using software developed by a private technology company.

Three parties may have different interests:

It is important to distinguish between ownership of software and rights over personal information.

A technology company may own its proprietary algorithm, but that does not automatically give it unrestricted rights to exploit the patient's identifiable medical information.

Similarly, a hospital's possession of medical records does not mean that the patient loses all rights concerning their personal information.

Principal legal issues

1. Patient data ownership

Indian law does not create a simple universal ownership rule under which all medical data automatically belongs exclusively to either the patient or the hospital.

The patient's privacy and data-protection rights must be distinguished from the hospital's rights and duties concerning medical records.

2. Algorithm ownership

The company developing the digital twin may have copyright, trade-secret or other intellectual-property interests in the underlying software, subject to applicable law.

3. Model ownership

A digital twin generated using patient information raises questions about the legal status of the resulting model. Whether the model itself contains personal data depends on its content, identifiability and potential to reveal information about the patient.

4. Commercial exploitation

Selling access to patient-specific predictions, licensing the model or using it to develop commercial products may raise additional contractual, privacy, confidentiality and regulatory issues.

7. Medical Negligence and Liability for Digital Twin Errors

Digital twins can produce inaccurate results because of incomplete records, incorrect measurements, defective software, biased training data or changing biological conditions.

Legal responsibility may arise at several levels.

Illustrative digital twin liability structure

Digital twin generates incorrect prediction

Doctor

Failure to exercise reasonable clinical judgment.

Hospital

Inadequate supervision or unsafe deployment.

Manufacturer

Defective or misleading software.

Data provider

Incorrect or incomplete patient information.

Possible legal consequences

Compensation, regulatory action, contractual liability or professional disciplinary proceedings, depending on the facts.

Different categories of liability

A. Doctor's liability

A doctor may be liable if the doctor fails to exercise reasonable professional care, blindly relies on an unreliable prediction or ignores clinically relevant information.

B. Hospital's liability

A hospital may face liability for inadequate staff training, defective clinical protocols, inappropriate deployment or failure to maintain patient-data security.

C. Manufacturer's liability

A software manufacturer may face liability for defects, misleading claims, failure to comply with applicable regulatory obligations or other actionable misconduct.

D. Data-provider liability

If incorrect patient records are supplied and cause foreseeable harm, liability may arise depending on the provider's duties, contractual arrangements and applicable law.

Important: Liability is not automatic merely because a digital twin makes a wrong prediction. The claimant must establish the applicable legal elements, such as duty, breach, causation and legally recognised damage.

8. Digital Twin Patients and Children's Legal Rights

Digital twins may be created for newborn children, patients with rare diseases and children suffering from chronic medical conditions.

This creates special legal issues because children may not have the legal capacity to independently consent to every form of data processing.

Important considerations include:

Parental or guardian authorisation where legally required.

Protection of children's genetic and medical information.

Best interests of the child.

Appropriate safeguards against commercial exploitation.

Respect for the child's developing autonomy.

Reassessment of consent when the child reaches the relevant age of legal capacity.

A digital twin created during childhood may remain technically accessible throughout adulthood. Therefore, long-term storage and future use require careful governance.

9. Digital Twin Patients and Medical Research

Digital twins can be used for clinical trials, drug development, personalised medicine and experimental treatment simulations.

For example, a pharmaceutical company may create thousands of virtual patient models to study how a proposed medicine could affect different biological characteristics.

This raises three important legal questions.

First: Is the digital twin a research participant?

Ordinarily, the digital model itself is not a legal research participant. The human patient whose data is used remains the relevant rights-holder.

Second: Is separate research consent required?

This depends on the nature of the research, applicable ethical guidelines, the legal basis for processing, the original consent and whether identifiable personal information is involved.

Third: Can digital twins replace human clinical trials?

Not automatically. Virtual simulations may support research and regulatory evidence, but their scientific validity and suitability must be established. They cannot simply be assumed to replace all human clinical investigations.

In India, the New Drugs and Clinical Trials Rules, 2019, applicable amendments, ICMR ethical guidelines and institutional ethics requirements may be relevant.

10. Digital Twin Patient and Discrimination

Digital twins can generate predictions about future medical conditions. These predictions may create risks of discrimination.

For example:

An insurer may classify a patient as high-risk based on predicted illness.

An employer may misuse health predictions when making employment decisions.

A financial institution may use health-related profiling inappropriately.

A healthcare provider may prioritise patients according to algorithmic predictions.

Such conduct may raise questions under privacy, equality, consumer protection, employment and other applicable laws.

Article 14 of the Indian Constitution protects equality before the law and equal protection of the laws, while Article 21 protects life, dignity and personal liberty.

A digital twin prediction should not automatically become a legally conclusive determination of a patient's future health.

11. Digital Twin Patients and Evidentiary Status

Another important issue concerns whether a digital twin can be presented as evidence in court.

Consider a medical negligence case in which a patient suffers serious injury following treatment recommended by an AI-based digital twin.

The parties may wish to introduce:

Digital twin simulation reports.

Medical prediction records.

AI-generated treatment recommendations.

Software validation reports.

Audit logs.

Clinical decision records.

Expert testimony.

In India, electronic records are governed by the Bharatiya Sakshya Adhiniyam, 2023, including its provisions on electronic and digital records and the conditions for their admissibility.

A digital twin report is not automatically conclusive proof of medical negligence or causation. Its reliability, authenticity, methodology and relevance must be assessed.

Courts may need to consider:

Whether the underlying medical information was accurate.

Whether the simulation was scientifically validated.

Whether the software version can be established.

Whether the report was altered.

Whether the expert can explain the model's limitations.

12. International Legal Frameworks

Digital twin patients may involve international hospitals, cloud providers, pharmaceutical companies and research institutions.

Different jurisdictions have different regulatory approaches.

European Union

The General Data Protection Regulation (GDPR) is particularly important.

Health data generally receives special-category protection under Article 9.

Relevant provisions include:

Article 5: Data-processing principles.

Article 6: Lawfulness of processing.

Article 9: Processing of special-category data.

Article 15: Right of access.

Article 17: Right to erasure, subject to exceptions.

Article 22: Certain safeguards concerning solely automated individual decision-making.

The EU Medical Device Regulation may also apply when digital-twin software meets the legal definition of a medical device.

United States

The Health Insurance Portability and Accountability Act (HIPAA) establishes privacy and security requirements for protected health information handled by covered entities and their business associates.

However, HIPAA does not automatically cover every company or every digital health application. Its applicability depends on the organisation and information involved.

13. Major Legal Challenges in Recognising Digital Twin Patient Status

The following unresolved questions are particularly significant:

14. Proposed Legal Framework for Digital Twin Patient Recognition

A comprehensive legal framework could establish the following safeguards.

1. Recognition of digital representation

The law should recognise a digital twin as a patient-linked medical representation without automatically granting it independent legal personality.

2. Patient-controlled information

Patients should have appropriate rights to access information, understand its use and exercise applicable data-protection rights.

3. Specific consent mechanisms

Separate and understandable permissions should be considered for clinical care, research, commercial development and third-party disclosure where required by law.

4. Medical accountability

Hospitals and doctors should maintain clear clinical responsibility for treatment decisions.

5. Algorithmic transparency

Medical institutions should document the digital twin's purpose, limitations, validation and significant updates.

6. Independent audits

High-risk systems should undergo appropriate clinical, technical and security assessments.

7. Protection against discrimination

Digital twin predictions should not be used as an unquestionable basis for denying healthcare or other legally protected opportunities.

8. Post-death governance

Rules should clarify retention, deletion, research use and access to a deceased patient's digital representation, subject to applicable confidentiality and data-protection requirements.

15. Conclusion

The legal status of a digital twin patient represents an emerging intersection of constitutional law, medical jurisprudence, artificial intelligence, data protection, intellectual property and healthcare regulation.

At present, a digital twin patient does not automatically become an independent legal person. It is better understood as a virtual medical representation of a real individual.

The actual patient continues to enjoy legal protection concerning privacy, dignity, informed consent, bodily autonomy and medical confidentiality.

The decisions in Puttaswamy, Samira Kohli, Jacob Mathew, Kusum Sharma, Snitem and Philips France and Dinerstein v. Google provide important principles for developing this area of law.

Ultimately, the law must ensure that digital representations improve medical treatment without reducing the human patient to a collection of data points or allowing algorithmic predictions to replace human dignity and legal rights.

16. Important Case Laws – Quick Revision

17. Important Legal Research Sources

Digital Personal Data Protection Act, 2023 – India Code.

Digital Personal Data Protection Rules, 2025 – Government of India.

Snitem and Philips France – C-329/16.

Dinerstein v. Google – Seventh Circuit judgment.

Legal and ethical issues concerning digital twins in healthcare.

Research conclusion: The most important distinction for future legislation is between the legal personality of a human patient and the legal status of the patient's digital twin. The former is an established legal subject; the latter remains a technologically generated representation governed through existing and developing legal frameworks.

This is an academic legal analysis, not an opinion on a particular patient's legal rights or an individual medical dispute.