Example Of Personalized Medicine Research Articles

The Roadmap toward Personalized Medicine: Challenges and Opportunities

In 2019, the International Consortium for Personalised Medicine (ICPerMed) developed a vision on how the use of personalized medicine (PM) approaches will promote “next-generation” medicine in 2030 more firmly centered on the individual’s personal characteristics, leading to improved health outcomes within sustainable healthcare systems through research, development, innovation, and implementation for the benefit of patients, citizens, and society. Nevertheless, there are significant hurdles that healthcare professionals, researchers, policy makers, and patients must overcome to implement PM. The ICPerMed aims to provide recommendations to increase stakeholders’ awareness on actionable measures to be implemented for the realization of PM. Starting with best practice examples of PM together with consultation of experts and stakeholders, a careful analysis that underlined hurdles, opportunities, recommendations, and information, aiming at developing knowledge on the requirements for PM implementation in healthcare practices, has been provided. A pragmatic roadmap has been defined for PM integration into healthcare systems, suggesting actions to overcome existing barriers and harness the potential of PM for improved health outcomes. In fact, to facilitate the adoption of PM by diverse stakeholders, it is mandatory to have a comprehensive set of resources tailored to stakeholder needs in critical areas of PM. These include engagement strategies, collaboration frameworks, infrastructure development, education and training programs, ethical considerations, resource allocation guidelines, regulatory compliance, and data management and privacy.

Are there any differences in the regulations of personalized medicine among the USA, EU and Japan?

In their cautious review, Shah and Shah [1] emphasized differences in regulations of personalized medicine (PM) among the three major authorities, the US Food and Drug Administration (FDA), the European Medicines Agency (EMA) and the Pharmaceuticals and Medical Devices Agency (PMDA) in Japan. Specific points regarding the differences, however, were not raised for the drugs they selected for discussion in their review. Given that the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) brings together the regulatory authorities and pharmaceutical industries of the USA, Europe and Japan, scientific and technical aspects of drug registration should be harmonized. To identify differences, if any, in regulations of PM, we investigated approvals of PM drugs in the three regions. As a typical example of PM, we focused on PM [2] drugs whose pharmacogenomic biomaker is required on the label. We also studied ivacaftor and pertuzumab, which were omitted in the list [2] simply because they were approved after publication of the list. The US, European and Japanese approval data on these drugs were obtained from Drugs@FDA (http://www.accessdata.fda.gov/Scripts/cder/DrugsatFDA/), European public assessment reports (http://www.ema.europa.eu/ema/index.jsp?curl=pages/medicines/landing/epar_search.jsp&mid=WC0b01ac058001d125) and the PMDA website (http://www.info.pmda.go.jp/approvalSrch/PharmacySrchInit?), respectively. We defined submission/approval delay as the difference between the date of submission/approval in the USA and that in the EU or in Japan. Of 17 FDA-approved drugs and 18 indications whose biomarker is labelled as required, 13 drugs and 14 indications were approved in the EU, whereas 12 drugs and 12 indications were approved in Japan (Table 1). The median submission delay from the submission in the USA was 0 months in the EU and 21 months in Japan. The median approval delay from the approval in the USA was 6 months in the EU and 28 months in Japan. Table 1 US, EU and Japanese data on the approval of personalized medicine drugs whose pharmacogenomic biomarker is required on the label One would expect that labels would not differ significantly among countries, given that regulatory authorities evaluate the same scientific data. Both biological and nonbiological factors, however, can affect regulatory decisions. For example, a much lower incidence of cystic fibrosis [3] and melanoma [4] in Japan compared with the West could discourage the makers of ivacaftor and vemurafenib to file an application to the PMDA. Denileukin diftitox and tositumomab, which were approved for lymphoma by the FDA in 1999 and 2003, respectively, remain unavailable in both the EU and Japan, probably because better treatment modalities are available now. The approval delay in Japan was observed in other therapeutic areas [5]. The present study shows that three-quarters of the approval delay consisted of delays in submission. The approval delay without submission delay in the EU indicates that the reviews took longer for the EMA than for the FDA. The cross-sectional design of our study makes causal inference of these delays difficult. Our results show some similarities and differences in the approvals of PM drugs among the three regions of the ICH. Further studies are needed to investigate differences in postmarketing regulations of PM drugs, because such regulations are important for risk–benefit assessment of PM and are greatly affected by local factors, such as health polices, culture and financial settings.

Patient-specific modelling of blood flow dynamics in intra-cranial aneurysms: an example of image-based personalised medicine

The visualisation of blood flow dynamics in intracranial aneurysm using computational fluid dynamics is an example of personalised medicine based on biomedical image analysis. A small percentage of these aneurysms rupture. Blood flow dynamics is thought to play an important role in the rupture process by exerting Wall Shear Stresses (WSS) on the endothelial cells. In this study, the effects of instabilities in the velocity waveform in the parent artery of an aneurysm of the Internal Carotid Artery (ICA) and variations of the computational mesh are investigated with respect to WSS at the aneurysm wall.