AI-based genetic testing has several issues.

• The Human Genome Project, launched in 1990, aimed to document and analyze human DNA, revealing patterns that could indicate the likelihood of developing rare diseases or carrying genetic abnormalities.

• Predictive tests were initially limited to exceptional cases due to their high cost.

AI’s Impact on Genomics

• AI has increased the amount of data processed, leading to the analysis of more than 1,200 distinct types of “junk DNA” elements from tumours.

• Healthcare startup, Gene Box, uses AI to process vast amounts of genetic data swiftly and accurately, uncovering patterns and insights that would be nearly impossible to identify manually.

Potential Pitfalls in Genetic Testing

• Genetics is only 30% of the contributing factor to a child’s success in school or job opportunities.

• A diagnosis could change in the future or may not present the full picture, often falling under the grey zone of significance.

• Genetic testing can identify risky genes, but it doesn’t mean the patient is bound to get it.

• Ethical guidelines are adhered to when dealing with sensitive cases, such as determining genetic predispositions for conditions like depression or heart disease.

Critiques of Genetic Testing Startups

• Nucleus, a genetic testing startup, has promised to analyze cancer, depression, longevity, and more.

• 23andMe, a once popular consumer genetic testing company, was recently involved in a data security breach, leading to a $30 million fine and three years of security monitoring.

• Customers have been urged to delete or withdraw their genetic data before the company goes bust or ownership changes hands.

• Companies like 23andMe don’t fall under HIPAA, which has federal laws protecting consumer data.