Abstract
This article provides a primer on medical device regulations in the United States, Europe, and Canada. Software tools are being developed and shared globally to enhance the accessibility and usefulness of genomic databases. Interactive software tools, such as email or mobile alert systems providing variant classification updates, are opportunities to democratize access to genomic data beyond laboratories and clinicians. Uncertainty over the reliability of outputs, however, raises concerns about potential harms to patients, especially where software is accessible to lay users. Developers may also need to contend with unfamiliar medical device regulations. The application of regulatory controls to genomic software could improve patient and user safety, but could also stifle innovation. Legal uncertainty for developers is compounded where software applications are made available globally (implicating multiple regulatory frameworks), and directly to lay users. Moreover, there is considerable uncertainty over the application of (evolving) medical device regulations in the context of both software and genetics. In this article, criteria and examples are provided to inform determinations of software as medical devices, as well as risk classification. We conclude with strategies for using genomic communication and interpretation software to maximize the availability and usefulness of genetic information, while mitigating the risk of harm to users.
Highlights
INTRODUCTIONPhysicians, clinical laboratories, and public human genetic variant databases (hereafter “variant databases”) all contribute to an interpretive “supply chain” supporting diagnosis and personalized care
Physicians, clinical laboratories, and public human genetic variant databases all contribute to an interpretive “supply chain” supporting diagnosis and personalized care
While we focus on software developed to enhance the interactivity of variant databases in support of precision medicine, our discussion will be relevant to other genomic software tools, including clinical decision support intended to provide users “with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care” (Senger & O'Leary, 2018), risk prediction algorithms (Hall et al, 2018), and in silico prediction tools (Prawira, Pugh, Stockley, & Siu, 2017)
Summary
Physicians, clinical laboratories, and public human genetic variant databases (hereafter “variant databases”) all contribute to an interpretive “supply chain” supporting diagnosis and personalized care. Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (Cambridge University), for example, calculates the individual risk level for developing breast or ovarian cancer, based on their family history and other data These tools join a growing ecosystem of publicly available software (i.e., distributed freely by database or third-party developers on the web or app stores) that supports the sharing and interpretation of genetic data. While we focus on software developed to enhance the interactivity of variant databases in support of precision medicine, our discussion will be relevant to other genomic software tools, including clinical decision support intended to provide users “with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care” (Senger & O'Leary, 2018), risk prediction algorithms (Hall et al, 2018), and in silico prediction tools (Prawira, Pugh, Stockley, & Siu, 2017). Device means an instrument, [...] or other similar article, or an in vitro reagent[...] that is manufactured, sold or represented for use in IMDRF
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