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Journal Advances in Precision Medicine

15 articles
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Levent Akyüz
Advances in Precision Medicine, Volume 2; doi:10.18063/APM.2017.02.001

Abstract:The parallel analysis of multiple factors, such as cytokines, from small sample size is an interesting approach for assessment of in vivo activation signatures and functionality after ex vivo stimulation. One interesting application is for therapy monitoring, such as safety data, pharmacodynamics, evidences for mode-of-action and side effects, particularly useful for accompanying early phase clinical trials. There are different platforms for Multiplex analysis of ligands available. We compared in this study the performance of three different platforms (Luminex Bio-Plex® 200, MesoScale Discovery®, Ella®) which use different ways of achieving parallel measurements of biomarkers from small liquid sample size. We show examples of in house assessment of intra- and inter-assay variations, determination of range and recovery for classical immunological serum markers and discuss advantages and disadvantages for these three platforms in relation to the question addressed.
Lilla Landeck, Monika Lessl, Andreas Busch, Matthias Gottwald, Khusru Asadullah
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.007.

Abstract:Precision medicine aims to treat diseases with special consideration for the individual biological variability. Novel biomarkers (BM) are needed to predict therapeutic responses and to allow for the selection of suitable patients for treatment with certain drugs. However, the identification and validation of appropriate BMs is challenging. Close col-laboration between different partners seems to be a key success factor. While the importance of partnerships and larger, well-established consortia in BM discovery such as the pharmaceutical industry and academic institutions is well un-derstood and has been investigated in the past, the use of open-innovation models, also known as ‘crowd sourcing for biomarkers’, is still in its infancy. Crowd sourcing comprises of a —usually via internet— request for problem solution to an open group of users in a kind of an ‘open call’. The community (crowd) is asked to provide solutions. Since the application of the crowd sourcing method offers the possibility to collect as many as possible novel ideas from a broad community with different expertise, this approach is particularly promising for BM development. In this article we de-scribe the first examples of open-innovation models, such as the ‘grants for targets’ (G4T) and biomarkers initiative ‘InnoCentive’ (innovation/incentive) platform. They may be a fruitful basis for collaborative BM development in the future.
Lilla Landeck, Patricia Carrigan, Khusru Asadullah
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.005

Abstract:Tremendous expectations have been connected with precision medicine in the past years. Be-side the advantages that this type of therapy offers we should be aware of its challenges too. In this issue we will highlight on specific challenges that the pharmacological industry is opposed with when de-veloping new targeted therapies. In addition, we will discuss issues with the reproducibility of published scientific data.
Anton Bespalov, Christoph H Emmerich, Björn Gerlach, Martin C Michel
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.001

Abstract:Limited reproducibility of preclinical data is increasingly discussed in the literature. Failure of drug devel-opment programs due to lack of clinical efficacy is also of growing concern. The two phenomena may share an important root cause — a lack of robustness in preclinical research. Such a lack of robustness can be a relevant cause of fail-ure in translating preclinical findings into clinical efficacy and hence attrition, and exaggerated cost in drug develop-ment. Apart from the study design and data analysis factors (e.g., insufficient sample sizes, failure to implement blind-ing, and randomization), heterogeneity among experimental models (e.g., animal strains) and the conditions of the study used between different laboratories is a major contributor to the lacking of robustness of research findings. The flipside of this coin is that the understanding of the causes of heterogeneity across experimental models may lead to the identification of relevant factors for defining the responder populations. Thus, this heterogeneity within preclinical find-ings could be an asset, rather than an obstacle, for precision medicine. To enable this paradigm shift, several steps need to be taken to identify conditions under which drugs do not work. An improved granularity in the reporting of preclini-cal studies is central among them (i.e., details about the study design, experimental conditions, quality of tools and rea-gents, validation of assay conditions, etc.). These actions need to be discussed jointly by the research communities in-terested in preclinical data robustness and precision medicine. Thus, we propose that a lack of robustness due to the heterogeneity across models and conditions of the study is not necessarily a liability for biomedical research but can be transformed into an asset of precision medicine.
Björn Wallmark
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.002

Abstract:The article aimed to give a personal perspective on drug discovery and development. The author has worked both in Big Pharma as a scientist and manager and more recently also in start-up biotech companies. Drug companies have played a major important role in improving population health and will continue to do so. The hurdles and costs for drug development have continuously risen without a parallel enhancement of productivity. There is no single explanation for this and the article outlines success factors and hurdles for effective drug development. Aspects of the external and internal environments that influence Big Pharma productivity is outlined and discussed.
Thorsten Ruppert, Sabine Sydow, Günter Stock
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.004

Abstract:In drug research, a serious transformation has taken place. With increasing knowledge gained from molecular medicine, it became possible to refine and develop new therapies based on the molecular mechanisms of diseases. Medicine and drug development have seen a paradigm shift which can be characterized with the catchword “personalized medicine”, also called “stratified medicine” or “precision medicine”. Personalized medicine is based on defined tandems of therapeutic agents and diagnostic tests. With this addition to the regular medical examination of the patient, specific patient characteristics are determined. The results of such diagnostic tests are then decisive for the choice of therapy or control of the effectiveness of the chosen treatment. The benefit of personalized medicine for the patient is the higher probability of treatment success as well as improved effectiveness and reduced / avoided side effects. Health insurance systems and the public may have the advantage that the health funds can be used more efficiently on this basis. This new paradigm requires also a new debate on the remuneration in health care. In order to bring personalized therapies to patients as quickly as possible, all players in health care should work together to address the challenges associated with personalized medicine.
Christian Loesche, Frank Kolbinger, Marie-Anne Valentin, Philip Jarvis, Melanie Ceci, Grazyna Wieczorek, Edward Khokhlovich, Irina Koroleva, Gerard Bruin, Frank Sinner, et al.
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.003

Abstract:Psoriasis is a well characterized interleukin (IL)-17A-driven skin disease with neutrophil infiltration and epidermal hyperkeratosis. Several biomarkers, most prominently β-defensin-2 (BD-2), have been identified using local and systemic invasive measurements as responsive markers of IL-17A-driven skin pathology. We sought to determine whether measurements of epidermal proteins by tape stripping could offer a minimally-invasive method to assess treatment responses. We compared the expression of 170 proteins in the epidermis (tape stripping) and dermis (open flow microperfusion) of 8 psoriatic subjects before and after administration of a single dose of subcutaneous (s.c.) antiIL-17A mAb secukinumab. Proteomic analyses of tape strips revealed a >3-fold decrease in 32 epidermal and inflammatory cell proteins in response to secukinumab. The epidermal proteins with the largest (>10-fold) decreases were: matrix metalloproteinase-8 (MMP-8, 15.68-fold, p<0.05); myeloperoxidase (MPO, 14.72-fold, p<0.005); IL-8 (11.93-fold, p<0.05); MMP-9 (10.81-fold, p<0.005); and IL-1β (10.35-fold, p<0.05). For these proteins, greater-fold protein changes were detected in the epidermis compared to dermis. Immunohistochemical analysis confirmed that neutrophils are the predominant cell type in psoriatic skin lesions that express MPO, MMP-8 and MMP-9, and that secukinumab treatment dramatically decreases neutrophil accumulation. Thus, tape stripping may be used to assess epidermal neutrophils, and protein biomarker responses to anti-IL-17A therapy in psoriasis.
Bhupinder Bhullar
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.02.006

Abstract:Reproducibility is a hallmark of scientific efforts. Estimates indicate that lack of reproducibility of data ranges from 50% to 90% among published research reports. The inability to reproduce major findings of published data confounds new discoveries, and importantly, result in wastage of limited resources in the futile effort to build on these published reports. This poses a challenge to the research community to change the way we approach reproducibility by developing new tools to help progress the reliability of methods and materials we use in our trade.
Lilla Landeck, Monika Lessl, Joachim Reischl, Andreas Busch, Patricia Carrigan, Matthias Gottwald, Petra Reinke, Khusru Asadullah
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.01.002

Abstract:Precision medicine aims to provide the precise treatment for the patient with the right dose at the right point of time. Biomarkers (BM) are vital for the identification of patients who would benefit the most from individualized treatment. In addition, they help to enable the prediction of prognosis, the detection of early therapeutic and adverse effects, and may serve as surrogate endpoints in clinical trials. BM are becoming essential tools to increase productivity in drug discovery and impressively enhance the way medicine is practiced. However, the identification, sufficient validation and implementation of such BM are challenging. This process requires expertise from different areas and high resource investments. Collaborations of different partners may be helpful to overcome these challenges. In the past decade, collaborations between diagnostics and pharmaceutical companies as well as industrial–academic collaborations have been increasingly pursued. Moreover, public funding may offer support and open new opportunities to form such consortia. Herein we give an overview of the different types of collaborations, their opportunities and challenges, and describe experiences in forming strategic partnerships with other companies.
Robert Leslie Holland
Advances in Precision Medicine, Volume 1; doi:10.18063/APM.2016.01.007

Abstract:The last decade has seen an extraordinary amount of effort devoted in biomedical research to the field of biomarkers. There have been some notable successes with novel markers being adopted into clinical practice bringing clear clinical benefit to some patients — particularly with the increasing numbers of medicines being approved with companion diagnostics. However, it is fair to say that there has not yet been the numbers of clinically valuable biomarkers brought to medical practice that the research effort would seem to warrant. This paper evaluates examples of successful biomarkers, markers which might be considered partial successes and a few problematic examples and ar-gues that more effort spent in the validation phase of marker development, and less in the discovery phase might be a more efficient way to allocate research resources.
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