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Beeindruckende Fortschritte im Bereich der Kunstlichen Intelligenz (KI) haben in den letzten Jahren fur Aufsehen gesorgt, aber auch Angste geweckt. Fur Gesetzgeber stellt sich damit die Frage, ob und wie sie den Herausforderungen von KI begegnen wollen. Am 21. April 2021 hat die EU-Kommission einen Vorschlag fur eine Verordnung zur Regulierung von KI prasentiert. Dieser Beitrag zeigt den Handlungsbedarf auf, der im Schweizer Recht besteht, und versteht sich als Anstoss fur eine vertiefte Diskussion und als Aufruf an den Schweizer Gesetzgeber, die Erarbeitung eines Rechtsrahmens zur Erfassung der Herausforderungen von KI zeitnah anzugehen.

ObjectiveTo characterize the therapeutic value of new drugs approved by the US Food and Drug Administration (FDA) and European Medicines Agency (EMA) and the association between these ratings and regulatory approval through expedited programs.DesignRetrospective cohort study.SettingNew drugs approved by the FDA and EMA between 2007 and 2017, with follow-up through 1 April 2020.Data sourcesTherapeutic value was measured using ratings of new drugs by five independent organizations (Prescrire and health authorities of Canada, France, Germany, and Italy).Main outcome measuresProportion of new drugs rated as having high therapeutic value; association between high therapeutic value rating and expedited status.ResultsFrom 2007 through 2017, the FDA and EMA approved 320 and 268 new drugs, respectively, of which 181 (57%) and 39 (15%) qualified for least one expedited program. Among 267 new drugs with a therapeutic value rating, 84 (31%) were rated as having high therapeutic value by at least one organization. Compared with non-expedited drugs, a greater proportion of expedited drugs were rated as having high therapeutic value among both FDA approvals (45% (69/153) v 13% (15/114); Pv 27% (65/240); PConclusionsLess than a third of new drugs approved by the FDA and EMA over the past decade were rated as having high therapeutic value by at least one of five independent organizations. Although expedited drugs were more likely than non-expedited drugs to be highly rated, most expedited drugs approved by the FDA but not the EMA were rated as having low therapeutic value.

To evaluate the diagnostic performance of bone texture analysis (TA) combined with machine learning (ML) algorithms in standard CT scans to identify patients with vertebrae at risk for insufficiency fractures. Standard CT scans of 58 patients with insufficiency fractures of the spine, performed between 2006 and 2013, were analyzed retrospectively. Every included patient had at least two CT scans. Intact vertebrae in a first scan that either fractured (“unstable”) or remained intact (“stable”) in the consecutive scan were manually segmented on mid-sagittal reformations. TA features for all vertebrae were extracted using open-source software (MaZda). In a paired control study, all vertebrae of the study cohort “cases” and matched controls were classified using ROC analysis of Hounsfield unit (HU) measurements and supervised ML techniques. In a within-subject vertebra comparison, vertebrae of the cases were classified into “unstable” and “stable” using identical techniques. One hundred twenty vertebrae were included. Classification of cases/controls using ROC analysis of HU measurements showed an AUC of 0.83 (95% confidence interval [CI], 0.77–0.88), and ML-based classification showed an AUC of 0.97 (CI, 0.97–0.98). Classification of unstable/stable vertebrae using ROC analysis showed an AUC of 0.52 (CI, 0.42–0.63), and ML-based classification showed an AUC of 0.64 (CI, 0.61–0.67). TA combined with ML allows to identifying patients who will suffer from vertebral insufficiency fractures in standard CT scans with high accuracy. However, identification of single vertebra at risk remains challenging. • Bone texture analysis combined with machine learning allows to identify patients at risk for vertebral body insufficiency fractures on standard CT scans with high accuracy. • Compared to mere Hounsfield unit measurements on CT scans, application of bone texture analysis combined with machine learning improve fracture risk prediction. • This analysis has the potential to identify vertebrae at risk for insufficiency fracture and may thus increase diagnostic value of standard CT scans.

Zusammenfassung. Der Begriff «Klinische Leitlinien» (Clinical Practice Guidelines, CPG) wird in der Schweiz nicht einheitlich verwendet. Die FMH definierte «Guidelines» im Jahr 1999. In der Praxis werden Dokumente, die diese Definition nicht erfüllen, teilweise trotzdem als Leitlinien bezeichnet, und andererseits Empfehlungen, die die Definition erfüllen, nicht immer. Auch Umschreibungen wie etwa «(klinische) Richtlinien», «Empfehlungen» oder «Stellungnahmen» werden verwendet. Diese Heterogenität kann zu Unsicherheiten in der Medizin und zu potenziell unerwünschten (oder zumindest unerwarteten) rechtlichen Konsequenzen führen. So können «klinische Leitlinien» zur Konkretisierung des Sorgfaltspflichtmassstabes in einem strafrechtlichen, zivilrechtlichen oder öffentlich-rechtlichen Verfahren herangezogen werden. Eine einheitliche Verwendung des Begriffs «Klinische Leitlinien» könnte in der Schweiz zur Verbesserung von Qualität und Rechtssicherheit führen.

Historically, patient experience, including symptomatic toxicities, physical function, and disease-related symptoms during treatment or their perspectives on clinical trials, has played a secondary role in cancer drug development. Regulatory criteria for drug approval require that drugs are safe and effective, and almost all drug approvals have been based only on efficacy endpoints rather than on quality-of-life (QoL) assessments. In contrast to Europe, information regarding the impact of drugs on patients’ QoL is rarely included in oncology drug labeling in the United States. Until recently, patient input and preferences have not been incorporated into the design and conduct of clinical trials. In recent years, a more in-depth understanding of cancer biology, as well as regulatory changes focused on expediting cancer drug development and approval, has allowed earlier access to novel therapeutic agents. Understanding the implications of these expedited programs is important for oncologists and patients, given the rapid expansion of these programs. In this article, we provide an overview of the role of QoL in the regulatory drug–approval process, key issues regarding trial participation from the patient perspective, and the implications of key expedited approval programs that are increasingly being used by regulatory bodies for cancer care.

As COVID-19 spreads across the globe, crowdsourced digital technology harbours the potential to improve surveillance and epidemic control, primarily through increased information coverage, higher information speed, fast case tracking and improved proximity tracing. Targeting those aims, COVID-19-related smartphone and web-based health applications are continuously emerging, leading to a multitude of options, raising ethical and legal challenges and potentially overwhelming end users. Building on an existing trustworthiness checklist for digital health applications, we searched the literature and developed a framework to guide the assessment of smartphone and web-based applications that aim to contribute to controlling the current epidemic or mitigating its effects. It further integrates epidemiological subject knowledge and a legal analysis, outlining the mechanisms through which new applications can support the fight against COVID-19. The resulting framework includes 40 questions across 8 domains onldquo;purposerdquo;,ldquo;usabilityrdquo;,ldquo;information accuracyrdquo;,ldquo;organisational attributes / reputationrdquo;,ldquo;transparencyrdquo;,ldquo;privacyrdquo; andldquo;user control / self-determinationrdquo;. All questions should be primarily answerable from publicly available data, as provided by application manufacturers. The framework aims to guide end users in choosing a transparent, safe and valuable application and suggests a set of information items that developers ideally make available to allow a balanced judgement and facilitate the trustworthiness of their products.

ObjectiveTo determine differences in the characteristics of cancer drugs designated as orphan drugs by the Food and Drug Administration (FDA) and European Medicines Agency (EMA).Design and settingIdentification of all cancer drugs (initial or supplementary indication) with orphan status approved by the FDA between 2008–2017 based on publicly accessible reports. The European public assessment reports (EPAR) was searched to determine whether these FDA-approved drugs were also approved by the EMA.Main outcome measuresExtraction of active ingredient, trade name, approval date and approved indication from two FDA data sources (Orphan Drug Product Designation Database, Drugs@FDA) and comparison with the same data from EPAR.ResultsThe FDA approved 135 cancer drugs with orphan indications that met our inclusion criteria, of which 101 (75%) were also approved by the EMA. 80/101 (79%) were first approved in the USA. Only 41/101 (41%) also received orphan designation by the EMA. 33/101 (33%) were approved for biomarker-based indications in the USA, however, only nine approved cancer drug indications by the EMA were biomarker-derived drugs. 78% (47/60) of approved cancer drugs that were only approved in the USA with orphan status were indicated for solid tumours, 22% (13/60) had indications for non-solid tumours. By contrast, out of those approved cancer drugs that received orphan designation by both agencies, 20% (8/41) were indicated for solid, and 80% (33/41) for non-solid tumours.ConclusionsOrphan designation was intended to encourage drug development for rare conditions. This study shows that the FDA approves more cancer drugs with such designations compared with the EMA, especially for subgroups of more prevalent cancers. One reason for the difference could be that the European Union requires demonstration of significant benefit for drugs that target the same indication as a drug already on the market to earn the orphan designation.

Federal Supreme Court Decisions in Medical Law (2000-2017) - Overview and Selected Case Reports Abstract. Within the framework of an empirical and casuistic analysis of Federal Court decisions in medical law between 2000 and 2017, the goal was to describe tendencies and patterns of Federal Court decisions in medical law. Among other things, our results show that specialists in internal medicine, psychiatry, gynecology, obstetrics and surgery are more frequently involved in federal court proceedings. By contrast, pathologists, forensic specialists or (diagnostic) radiologists are rarely represented. This may be explained by the fact that the first group consists of more physicians than the other specialties. Furthermore, in the first group, either stronger action may be taken against the will of the patient (e.g. in the context of compulsory medication in psychiatry) or a possible breach of the duty of care is more obvious for the patient or his relatives or at least recognizable even without medical knowledge.