Medical genome accountability doctrine

Medical genome accountability doctrine is a proposed legal framework for determining responsibility when genomic information, genetic testing, gene-editing technologies, or genome-based medical decisions cause harm, discrimination, privacy violations, or incorrect clinical outcomes. It seeks to establish who is legally responsible among doctors, laboratories, hospitals, pharmaceutical companies, biotechnology companies, researchers, software developers and regulatory authorities.

There is currently no universally recognized standalone doctrine called the “Medical genome accountability doctrine.” Its principles can be developed from medical negligence, constitutional privacy, informed consent, product liability, data protection, biotechnology regulation and human-rights law.

Meaning and scope

Modern medicine increasingly uses genomic information for diagnosis, disease-risk prediction, pharmacogenomics, cancer treatment and reproductive decision-making.

Genome-related medical activities may include:

• whole-genome and whole-exome sequencing;
• genetic disease testing;
• pharmacogenomic testing;
• cancer genomic profiling;
• prenatal and preimplantation genetic testing;
• gene therapy;
• genome editing;
• genetic counselling; and
• AI-based genomic interpretation.

Accountability arises when these technologies produce an inaccurate or harmful outcome.

For example, liability questions may arise if a laboratory incorrectly reports a pathogenic variant and a patient undergoes unnecessary treatment. Similarly, responsibility may arise if a clinically significant genetic finding is wrongly classified as harmless and the patient does not receive appropriate preventive care.

Constitutional protection of genomic information

Genomic information is exceptionally sensitive because it can reveal information about an individual's health, biological characteristics and potential disease risks. It can also indirectly reveal information about biological relatives.

The most important Indian precedent is Justice K.S. Puttaswamy (Retd.) v. Union of India (2017).

The Supreme Court recognized privacy as a fundamental right under Article 21 and connected privacy with dignity, autonomy and informational control.

Under a medical genome accountability doctrine, unauthorized collection, disclosure or misuse of genomic information could therefore constitute a serious privacy concern.

Healthcare organizations should apply principles such as:

• purpose limitation;
• data minimization;
• confidentiality;
• informed consent;
• secure storage;
• controlled access; and
• appropriate deletion or retention policies.

Laboratory accountability

Genomic testing depends heavily upon laboratory accuracy.

A laboratory may be accountable for:

1. sample identification errors;
2. contamination;
3. sequencing errors;
4. inadequate quality control;
5. incorrect variant interpretation;
6. failure to update clinically significant classifications; and
7. negligent communication of results.

Where a laboratory's negligence causes patient harm, ordinary medical negligence principles may become relevant.

In Jacob Mathew v. State of Punjab (2005), the Supreme Court discussed professional negligence and the standard of reasonable medical care. Although the case did not concern genomic medicine, its principles can be applied by analogy to genomic testing professionals.

Physician accountability

Doctors using genomic information must interpret it within the clinical context.

A genetic test is not necessarily equivalent to a definitive diagnosis. A physician should consider:

• the reliability of the test;
• clinical history;
• family history;
• the significance of the detected variant;
• available treatment options; and
• limitations of genetic testing.

Failure to appropriately interpret a genomic result could potentially constitute professional negligence.

The existence of sophisticated technology does not eliminate the doctor's duty of care.

Informed consent

Genomic testing creates distinctive consent issues because genetic information may have consequences extending beyond the individual patient.

Before testing, patients should ordinarily understand:

• what is being tested;
• why testing is being performed;
• possible results;
• uncertain or incidental findings;
• possible implications for relatives;
• data-storage arrangements;
• research use;
• possible commercial use; and
• whether results may be shared with third parties.

Samira Kohli v. Dr. Prabha Manchanda (2008) provides an important Indian authority concerning informed consent in medical treatment.

Its principles support the requirement that patients receive meaningful information before undergoing significant medical interventions or procedures.

Familial implications of genomic information

Unlike ordinary medical information, genomic information may reveal information about biological relatives.

For example, a patient's genetic test may reveal a hereditary cancer risk affecting siblings or children.

This creates a difficult legal question: does the patient's privacy prevail over a relative's interest in receiving potentially life-saving information?

A future accountability framework could establish carefully defined circumstances in which disclosure to relatives is permissible or required, while preserving confidentiality as the default.

Any exception should be based on necessity, serious risk and appropriate legal safeguards rather than unrestricted disclosure.

Gene editing and accountability

Genome accountability becomes even more significant with gene-editing technologies such as CRISPR.

Two broad categories should be distinguished:

Somatic editing affects the treated individual.

Germline editing may potentially affect future generations.

Errors in gene editing could produce medical or genetic consequences extending beyond the immediate patient.

A governance framework should therefore impose stronger requirements for:

• scientific validation;
• clinical authorization;
• informed consent;
• long-term monitoring;
• adverse-event reporting;
• independent ethics review; and
• accountability for foreseeable harm.

The precautionary principle, recognized in Indian environmental jurisprudence, can provide an analogy where scientific uncertainty and potentially serious consequences coexist.

Genomic discrimination

Genomic information may potentially be used by insurers, employers or other institutions to classify individuals according to predicted disease risks.

This creates equality concerns.

In National Legal Services Authority v. Union of India (2014), the Supreme Court emphasized dignity and equality and rejected discriminatory treatment based on identity.

Although NALSA did not concern genetic discrimination, its constitutional reasoning supports the broader principle that biological information should not become an unrestricted basis for exclusion or unequal treatment.

A future genome-accountability framework should therefore prohibit unjustified discrimination based on genetic characteristics.

Genetic data and commercial organizations

Private biotechnology companies may process enormous genomic datasets for:

• pharmaceutical research;
• AI development;
• drug discovery;
• population studies;
• personalized medicine; and
• commercial genetic testing.

Accountability should extend beyond the initial healthcare provider.

Companies should disclose:

• how genomic data will be used;
• whether it will be sold or licensed;
• whether it will be transferred internationally;
• whether it will be used for AI training;
• how long it will be retained; and
• whether individuals can withdraw from secondary uses where legally possible.

AI and genomic accountability

AI systems increasingly assist in genomic interpretation.

This creates an additional accountability problem. If an AI system incorrectly identifies a genetic mutation, responsibility cannot simply be shifted to the algorithm.

A governance model should identify responsibility across the technology chain:

developer → laboratory → healthcare institution → clinician → regulator

The precise allocation would depend on the cause of the error.

AI systems should therefore undergo appropriate validation, monitoring and auditing, particularly when their output can influence diagnosis or treatment.

Relevant case laws

Important authorities for developing the doctrine include:

• Justice K.S. Puttaswamy v. Union of India (2017) – constitutional privacy, dignity and informational autonomy.
• Puttaswamy v. Union of India (Aadhaar) (2018) – proportionality and safeguards concerning large-scale personal information.
• Samira Kohli v. Dr. Prabha Manchanda (2008) – informed consent in medical treatment.
• Jacob Mathew v. State of Punjab (2005) – medical negligence and professional standards.
• NALSA v. Union of India (2014) – equality and dignity.
• Z v. Finland (1997) – confidentiality of highly sensitive medical information.
• S. and Marper v. United Kingdom (2008) – privacy implications of retaining DNA-related information.
• Myriad Genetics, Inc. v. Association for Molecular Pathology (2013) – limits on patent protection for naturally occurring human DNA in U.S. law.

These cases do not establish a standalone medical genome accountability doctrine. They provide analogical legal principles for privacy, consent, equality, medical responsibility and genetic information.

Proposed accountability framework

A comprehensive framework could impose:

1. Laboratory quality standards for genomic testing.
2. Professional duties for physicians and genetic counsellors.
3. Meaningful informed consent before genomic testing.
4. Strict confidentiality for genomic information.
5. AI validation and human oversight for automated interpretation.
6. Mandatory reporting of serious genomic testing errors.
7. Long-term monitoring of gene-editing interventions.
8. Protection against genetic discrimination.
9. Clear liability allocation among manufacturers, laboratories and healthcare providers.
10. Compensation mechanisms for patients harmed by negligent genomic services.

Conclusion

The medical genome accountability doctrine would establish a legal principle that the use of advanced genomic technology does not eliminate ordinary duties of care, consent, privacy and accountability. Responsibility should follow the source of the error or harm rather than being obscured by the complexity of genomic technology.

As precision medicine, genomic AI and gene editing expand, future law will need to combine medical negligence, constitutional privacy, informed consent, data protection, equality, product liability and biotechnology regulation into a coherent accountability framework.