{"id":83,"date":"2020-08-27T04:09:09","date_gmt":"2020-08-26T20:09:09","guid":{"rendered":"https:\/\/regask.com\/?p=83"},"modified":"2024-11-19T09:58:03","modified_gmt":"2024-11-19T01:58:03","slug":"samd%e3%83%87%e3%82%b8%e3%82%bf%e3%83%ab%e8%a8%ba%e6%96%ad%e3%81%ae%e8%a6%8f%e5%88%b6","status":"publish","type":"post","link":"https:\/\/regask.com\/ja\/regulating-samd-digital-diagnostics\/","title":{"rendered":"\u30c7\u30b8\u30bf\u30eb\u8a3a\u65ad\u306e\u305f\u3081\u306e SaMD: \u7c73\u56fd\u3068 EU \u306e\u898f\u5236\u306e\u6bd4\u8f03"},"content":{"rendered":"

As the Covid-19 pandemic pummels healthcare institutions around the world, some doctors are turning to innovation to diagnose patients: artificial intelligence (AI).<\/strong><\/p>\n

Despite herculean efforts to do so, governments are still straining to scale up lab-based methods like nucleic acid and antibody testing, but these new\u00a0in silico<\/em>\u00a0tools offer a way to save on both money and time. That means some regions are betting big on AI: the European Commission, for example, is investing money into a tool that analyzes computerized tomography scans to accelerate patient diagnosis.[i]\n

Software diagnostic tools like these have exploded over the past decade, covering conditions that range from melanoma to spinal fracture to, of course, Covid-19. But as the use of those tools has grown, so have the associated regulatory challenges.<\/p>\n

What is SaMD<\/strong>?<\/h2>\n

Most digital diagnostic tools fall under the umbrella of software as a medical device (SaMD), a larger umbrella that includes not just software used for diagnosis, but also for prevention, treatment, and so on.<\/p>\n

According to the International Medical Devices Regulators Forum (IMDRF), SaMD is software intended for a medical purpose achievable through operation of the software itself. Software that only supports a larger piece of hardware (e.g., pacemaker software), in other words, is not SaMD.[ii]\u00a0And software used in a medical context that doesn\u2019t have a specific medical purpose (e.g., image capture software that doesn\u2019t perform analysis) also isn\u2019t SaMD.<\/p>\n

But outside of those caveats, SaMD as a category is quite broad. It runs the gamut from diagnosis to prevention to treatment, addresses all kinds of medical conditions, can be run on specialized medical equipment or general-purpose devices (e.g. phones), and can operate independently or in conjunction with other hardware. Plus, different countries might have different goalposts for what counts as SaMD.<\/p>\n

As you would expect, that creates quite the headache for regulators\u2014and for software manufacturers too.<\/p>\n

SaMD: Safe for Diagnosis<\/strong>?<\/h2>\n

Diagnostically speaking, SaMD comes in several flavors. Some tools are intended to support doctors, particularly radiologists, in a clinical setting, helping to capture what even the trained human eye might miss, and these naturally receive close scrutiny. According to one article in\u00a0Diagnostic Imaging<\/em>, the US Food and Drug Administration (FDA) had approved 28 algorithms in this vein as of October 2019.[iii]\n

But on the flip side, there is also an increasing trend of direct-to-consumer tools, which sometimes receive tens of millions of downloads.[iv]\u00a0Some such apps do their best to fly under the regulatory radar, arguing that they are relatively low-risk and are meant to complement\u2014not substitute for\u2014professional medical advice.<\/p>\n

Whether intended for clinical or consumer use, these diagnostic tools carry their own suite of regulatory challenges. There\u2019s an enormous number of them, for one: 318,000 mobile health apps by one count (although this includes apps that aren\u2019t used for diagnosis, or don\u2019t count as medical devices). Those that are AI-based may continue to change during use, leading them to defy the usual premarket pathways for approval. Also, they blur the lines of liability: if a diagnostic tool goes wrong, who\u2019s to blame\u2014doctor, hospital, or software creator?[v]\n

And as a review by Australia\u2019s Therapeutic Goods Administration (TGA) notes, there is far too little research available on how the use of these tools impacts patient safety.[vi]\u00a0Because journals tend to publish positive results over negative ones, studies that indicate performance failures don\u2019t always see the light, creating the risk that regulators see an all-too-rosy picture. For regulators, this hence implies the importance of post-market surveillance data.<\/p>\n

Direct-to-consumer diagnostic tools also face challenges, as seemingly innocuous as they are. Some of these apps work poorly and may give consumers false assurance\u2014for example, incorrectly telling them that their melanoma is harmless and leading them to delay treatment.[vii]\n

Regulators hence must be discerning when assigning risk levels to diagnostic SaMD.<\/p>\n

To Regulate SaMD, or Not to Regulate<\/strong>?<\/h2>\n

As is common elsewhere, many regulators have adopted a risk-based approach to classifying diagnostic SaMD. The IMDRF\u2019s proposed categories run from I to IV, with IV being the most serious.[viii]\u00a0A device\u2019s category is decided based on two variables: the healthcare condition in question, and the nature of the information provided by the SaMD.<\/p>\n

Significance of information provided by SaMD to health care decision<\/strong><\/p>\n

\n\n\n\n\n\n\n
State of healthcare situation or condition<\/strong><\/th>\nTreat or diagnose<\/strong><\/th>\nDrive clinical management<\/strong><\/th>\nInform clinical management<\/strong><\/th>\n<\/tr>\n
Critical<\/td>\nIV<\/td>\nIII<\/td>\nII<\/td>\n<\/tr>\n
Serious<\/td>\nIII<\/td>\nII<\/td>\nI<\/td>\n<\/tr>\n
Non-serious<\/td>\nII<\/td>\nI<\/td>\nI<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

This framework allows for a relatively flexible approach to SaMD management. According to examples the IMDRF provides, SaMD used to self-assess hearing loss would be Category I, and SaMD that analyzed heart rate data to help clinicians diagnose arrhythmia would be Category II. Malignant skin lesions are \u201ccritical\u201d conditions, so if SaMD provides data (e.g. monitoring growth) that supplements other information to diagnose malignancy, it would be Category III, but if used as the sole tool to build a structural map and calculate dimensions of a lesion, it would be Category IV.<\/p>\n

Of course, countries and regions manage and designate these risk categories in varying ways. For example, both the US and EU take high-risk SaMD quite seriously\u2014an FDA guidance document recommends \u201cindependent review\u201d for higher-risk SaMD.[ix]\u00a0But when it comes to lower-risk SaMD, the two regions diverge in their regulatory approach.<\/p>\n

Under the Trump administration, the US FDA takes a \u201chands off\u201d approach to regulating lower-risk SaMD, stating that it will \u201cexercise enforcement discretion\u201d even though software may meet the definition of a medical device. Former Trump-appointed FDA commissioner Scott Gottlieb has argued that over-regulation of mobile health could stifle innovation, though not all his colleagues may agree.[x]\u00a0Particularly worth watching is FDA\u2019s new PreCert program, which will allow SaMD developers to roll out products by getting FDA approval of the company\u2019s development process\u2014rather than the product itself.[xi]\n

This move toward SaMD liberalization in the US contrasts with the increasingly strict EU approach. For example, the EU\u2019s new Medical Devices Regulation (MDR) will strictly limit the number of SaMD designated as minimal-risk.[xii]\u00a0The EU recognizes SaMD as Class I, IIa, IIb, or III, but the MDR, scheduled to go into effect in May 2021 after a Covid-19-related delay, has a \u201cRule 11\u201d that will push the majority of Class I devices into Class IIa at a minimum.<\/p>\n

Some commentators have criticized this as an undue focus on severity, rather than risk, which will increase the costs of regulatory compliance\u2014in other words, limiting innovation in just the way that ex-commissioner Gottlieb pushed back against.[xiii]\n

Getting Smart<\/strong> on SaMD<\/h2>\n

Regulators have their work cut out for them, as they struggle to balance the need to protect patient safety battling with the drive to foster life-saving innovation. New trends like the increasing adoption of AI will only make it more difficult to design appropriate regulatory frameworks, although they also create opportunities for regulatory advancements. Many countries are trying to evaluate the US PreCert program, for example, to see if they can pilot similar programs in their local markets.<\/p>\n

For now, SaMD for diagnostic will need both technical innovation as well as clear-thinking regulatory innovation.<\/p>\n

<\/div>\n[i]ec.europa.eu \u2013 Using AI to fast and effectively diagnose COVID-19 in hospitals<\/a>
\n[ii]\u00a0fda.gov \u2013 Software as a Medical Devices (SaMD)<\/a>
\n[ii]\u00a0fda.gov \u2013 What are examples of Software as a Medical Devices?<\/a>
\n[iii]\u00a0diagnosticimaging.com \u2013 The State of Radiology AI in 2019<\/a>
\n[iV]\u00a0degruyter.com \u2013 Beyond Dr. Google: the evidence on consumer-facing digital tools for diagnosis<\/a>
\n[v]\u00a0mobius.md \u2013 11 surprising mobile health statistics<\/a>
\n[v]\u00a0fda.gov \u2013 Artificial Intelligence and Machine Learning in Software as a Medical Devices<\/a>
\n[v]\u00a0hbr.org \u2013 AI Will Change Radiology, but It Won\u2019t Replace Radiologists<\/a>
\n[vi]\u00a0tga.gov.au \u2013 Actual and potential harm caused by medical software \u2013 A rapid literature review of safety and performance issues<\/a>
\n[vii]\u00a0bmj.com \u2013 Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies<\/a>
\n[viii]\u00a0fda.gov \u2013 Global Approach to Software as a Medical Devices Software as a Medical Devices<\/a>
\n[viii]\u00a0imdrf.org \u2013 \u201cSoftware as a Medical Devices\u201d: Possible Framework for Risk Categorization and Corresponding Considerations<\/a>
\n[ix]\u00a0fda.gov \u2013 Software as a Medical Devices (SAMD): Clinical Evaluation Guidance for Industry and Food and Drug Administration Staff<\/a>
\n[x]\u00a0mobihealthnews.com \u2013 In past editorials, Trump\u2019s FDA pick advocated hands-off approach for health apps<\/a>
\n[xi]\u00a0deloitte.com \u2013 Software as a medical device \u2013 An agile model for food and drug administration (FDA)-regulated software in health care<\/a>
\n[xii]\u00a0med-technews.com \u2013 How software may be classified under medical device regulation guidance<\/a>
\n[xii]\u00a0blog.cm-dm.com \u2013 MDR: one year left and too late for class I software<\/a>
\n[xiii]\u00a0johner-institute.co \u2013 MDR Classification Rule 11 for Medical Devices Software<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

As the Covid-19 pandemic pummels healthcare institutions around the world, some doctors are turning to innovation to diagnose patients: artificial intelligence (AI). Despite herculean efforts to do so, governments are still straining to scale up lab-based methods like nucleic acid and antibody testing, but these new\u00a0in silico\u00a0tools offer a way to save on both money and time. That means some regions are betting big on AI: the European Commission, for example, is investing money into a tool that analyzes computerized tomography scans to accelerate patient diagnosis.[i] Software diagnostic tools like these have exploded over the past decade, covering conditions that range from melanoma to spinal fracture to, of course, Covid-19….<\/p>\n","protected":false},"author":39,"featured_media":2204,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[511,28],"tags":[],"class_list":["post-83","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-australia-regulations","category-medical-devices-news"],"acf":[],"yoast_head":"\nRegulating SAMD Digital Diagnostics | RegASK<\/title>\n<meta name=\"description\" content=\"Learn how to regulate Software as a Medical Device (SAMD) in the US and EU. 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