Privacy and ethical challenges in next-generation sequencing.

The use of NGS in clinical and research contexts has features that pose challenges for traditional ethical frameworks for protecting research participants and patients. NGS generates massive amounts of data and results that vary in terms of known clinical relevance. It is important to determine appropriate processes for protecting, managing and communicating the data. The use of machine learning for sequencing and interpretation of genomic data also raises concerns in terms of the potential for bias and potential implications for fiduciary obligations. NGS poses particular challenges in three main ethical areas: privacy, informed consent, and return of results.