Recommendations for robust and reproducible preclinical research in personalised medicine.

BACKGROUND: Personalised medicine is a medical model that aims to provide tailor-made prevention and treatment strategies for defined groups of individuals. The concept brings new challenges to the translational step, both in clinical relevance and validity of models. We have developed a set of recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. METHODS: These recommendations have been developed following four main steps: (1) a scoping review of the literature with a gap analysis, (2) working sessions with a wide range of experts in the field, (3) a consensus workshop, and (4) preparation of the final set of recommendations. RESULTS: Despite the progress in developing innovative and complex preclinical model systems, to date there are fundamental deficits in translational methods that prevent the further development of personalised medicine. The literature review highlighted five main gaps, relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. We identified five points of focus for the recommendations, based on the consensus reached during the consultation meetings: (1) clinically relevant translational research, (2) robust model development, (3) transparency and education, (4) revised regulation, and (5) interaction with clinical research and patient engagement. Here, we present a set of 15 recommendations aimed at improving the robustness of preclinical methods in translational research for personalised medicine. CONCLUSIONS: Appropriate preclinical models should be an integral contributor to interventional clinical trial success rates, and predictive translational models are a fundamental requirement to realise the dream of personalised medicine. The implementation of these guidelines is ambitious, and it is only through the active involvement of all relevant stakeholders in this field that we will be able to make an impact and effectuate a change which will facilitate improved translation of personalised medicine in the future.

Biomarker Research and Development for Coronavirus Disease 2019 (COVID-19): European Medical Research Infrastructures Call for Global Coordination.

An effective response to the coronavirus disease 2019 (COVID-19) pandemic requires a better understanding of the biology of the infection and the identification of validated biomarker profiles that would increase the availability, accuracy, and speed of COVID-19 testing. Here, we describe the strategic objectives and action lines of the European Alliance of Medical Research Infrastructures (AMRI), established to improve the research process and tackle challenges related to diagnostic tests and biomarker development. Recommendations include: the creation of a European taskforce for validation of novel diagnostic products, the definition and promotion of criteria for COVID-19 samples biobanking, the identification and validation of biomarkers as clinical endpoints for clinical trials, and the definition of immune biomarker signatures at different stages of the disease. An effective management of the COVID-19 pandemic is possible only if there is a high level of knowledge and coordination between the public and private sectors within a robust quality framework.

Potential business model for a European vaccine R&D infrastructure and its estimated socio-economic impact.

Background: Research infrastructures are facilities or resources that have proven fundamental for supporting scientific research and innovation. However, they are also known to be very expensive in their establishment, operation and maintenance. As by far the biggest share of these costs is always borne by public funders, there is a strong interest and indeed a necessity to develop alternative business models for such infrastructures that allow them to function in a more sustainable manner that is less dependent on public financing. Methods: In this article, we describe a feasibility study we have undertaken to develop a potentially sustainable business model for a vaccine research and development (R&D) infrastructure. The model we have developed integrates two different types of business models that would provide the infrastructure with two different types of revenue streams which would facilitate its establishment and would be a measure of risk reduction. For the business model we are proposing, we have undertaken an ex ante impact assessment that estimates the expected impact for a vaccine R&D infrastructure based on the proposed models along three different dimensions: health, society and economy. Results: Our impact assessment demonstrates that such a vaccine R&D infrastructure could achieve a very significant socio-economic impact, and so its establishment is therefore considered worthwhile pursuing. Conclusions: The business model we have developed, the impact assessment and the overall process we have followed might also be of interest to other research infrastructure initiatives in the biomedical field.

Evaluating Translational Methods for Personalized Medicine-A Scoping Review.

The introduction of personalized medicine, through the increasing multi-omics characterization of disease, brings new challenges to disease modeling. The scope of this review was a broad evaluation of the relevance, validity, and predictive value of the current preclinical methodologies applied in stratified medicine approaches. Two case models were chosen: oncology and brain disorders. We conducted a scoping review, following the Joanna Briggs Institute guidelines, and searched PubMed, EMBASE, and relevant databases for reports describing preclinical models applied in personalized medicine approaches. A total of 1292 and 1516 records were identified from the oncology and brain disorders search, respectively. Quantitative and qualitative synthesis was performed on a final total of 63 oncology and 94 brain disorder studies. The complexity of personalized approaches highlights the need for more sophisticated biological systems to assess the integrated mechanisms of response. Despite the progress in developing innovative and complex preclinical model systems, the currently available methods need to be further developed and validated before their potential in personalized medicine endeavors can be realized. More importantly, we identified underlying gaps in preclinical research relating to the relevance of experimental models, quality assessment practices, reporting, regulation, and a gap between preclinical and clinical research. To achieve a broad implementation of predictive translational models in personalized medicine, these fundamental deficits must be addressed.

Tackling the translational challenges of multi-omics research in the realm of European personalised medicine: A workshop report.

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

Clinical characteristics of COVID-19 in older adults. A retrospective study in long-term nursing homes in Catalonia.

The natural history of COVID-19 and predictors of mortality in older adults need to be investigated to inform clinical operations and healthcare policy planning. A retrospective study took place in 80 long-term nursing homes in Catalonia, Spain collecting data from March 1st to May 31st, 2020. Demographic and clinical data from 2,092 RT-PCR confirmed cases of SARS-CoV-2 infection were registered, including structural characteristics of the facilities. Descriptive statistics to describe the demographic, clinical, and molecular characteristics of our sample were prepared, both overall and by their symptomatology was performed and an analysis of statistically significant bivariate differences and constructions of a logistic regression model were carried out to assess the relationship between variables. The incidence of the infection was 28%. 71% of the residents showed symptoms. Five major symptoms included: fever, dyspnea, dry cough, asthenia and diarrhea. Fever and dyspnea were by far the most frequent (50% and 28%, respectively). The presentation was predominantly acute and symptomatology persisted from days to weeks (mean 9.1 days, SD = 10,9). 16% of residents had confirmed pneumonia and 22% required hospitalization. The accumulated mortality rate was 21.75% (86% concentrated during the first 28 days at onset). A multivariate logistic regression analysis showed a positive predictive value for mortality for some variables such as age, pneumonia, fever, dyspnea, stupor refusal to oral intake and dementia (p<0.01 for all variables). Results suggest that density in the nursing homes did not account for differences in the incidence of the infection within the facilities. This study provides insights into the natural history of the disease in older adults with high dependency living in long-term nursing homes during the first pandemic wave of March-May 2020 in the region of Catalonia, and suggests that some comorbidities and symptoms have a strong predictive value for mortality.

The Fundamental Characteristics of a Translational Scientist.

Translational science is defined as the field of investigation focused on understanding the scientific and operational principles underlying each step of the translational process. Further development of the field is advanced by describing the key desirable characteristics of individuals who seek to uncover these principles to increase the efficiency and efficacy of translation. The members of Translation Together, a newly launched international collaborative effort to advance translational innovation, present here a consensus representation of the fundamental characteristics of a translational scientist. We invite all stakeholders to contribute in the ongoing efforts to develop the field and educate the next generation of translational scientists.

Addressing Pressing Needs in the Development of Advanced Therapies.

The commercial development of advanced therapy medicinal products (ATMPs) represents great opportunity for therapeutic innovation but is beset by many challenges for its developers. Although the ATMP field continues to progress at a rapid pace, evidenced by the increasing number of clinical trials conducted over the past few years, several factors continue to complicate the introduction of ATMPs as a curative treatment for multiple disease types, by blocking their translational pathway from research to the patient. While several recent publications (Trounson and McDonald, 2015; Abou-El-Enein et al., 2016a,b) as well as an Innovative Medicines Initiative consultation (IMI, 2016) this year have highlighted the major gaps in ATMP development, with manufacturing, regulatory, and reimbursement issues at the forefront, there remains to be formulated a coherent strategy to address these by bringing the relevant stakeholders to a single forum, whose task it would be to design and execute a delta plan to alleviate the most pressing bottlenecks. This article focuses on two of the most urgent areas in need of attention in ATMP development, namely manufacturing and reimbursement, and promotes the concept of innovation-dedicated research infrastructures to support a multi-sector approach for ensuring the successful development, entry, and ensuing survival of ATMPs in the healthcare market.

Putting translational science on to a global stage.

Global collaboration in translational science promises to accelerate the discovery, development and dissemination of new medical interventions. Here, we introduce a new international collaboration of translational science organizations and highlight our initial strategy to reduce or remove bottlenecks in translation.

EATRIS, a European initiative to boost translational biomedical research.

Recent advances in molecular and cellular biology have facilitated the discovery of the key molecular drivers of major diseases. This knowledge raised some optimism in the beginning of this century, yet its impact on disease prevention, diagnosis and targeted intervention remains low. At the same time the pharmaceutical industry is facing the dual challenges of a dwindling drug pipeline and ever increasing cost of drug development. It is against this background that a number of European countries decided to establish EATRIS, the European Advanced Translational Research InfraStructure in Medicine. EATRIS aims for faster and more efficient translation of basic research into innovative products, by providing academia and industry access to the state-of-the-art expertise and highly capital-intensive facilities residing in Europe's top translational research centers and hospitals. To this end, EATRIS formed product groups that provide translational services in the fields of development and supply of (1) molecular imaging and tracing, (2) vaccines, (3) biomarkers, (4) small molecules and (5) advanced therapeutic medicinal products. Herein we describe the background, goals, functions and structure of EATRIS. As an example, it will be described how EATRIS centers involved in imaging and tracing might contribute to more efficient drug development and personalized medicine.