Defining the critical hurdles in cancer immunotherapy

Scientific discoveries that provide strong evidence of antitumor effects in preclinical models often encounter significant delays before being tested in patients with cancer. While some of these delays have a scientific basis, others do not. We need to do better. Innovative strategies need to move into early stage clinical trials as quickly as it is safe, and if successful, these therapies should efficiently obtain regulatory approval and widespread clinical application. In late 2009 and 2010 the Society for Immunotherapy of Cancer (SITC), convened an "Immunotherapy Summit" with representatives from immunotherapy organizations representing Europe, Japan, China and North America to discuss collaborations to improve development and delivery of cancer immunotherapy. One of the concepts raised by SITC and defined as critical by all parties was the need to identify hurdles that impede effective translation of cancer immunotherapy. With consensus on these hurdles, international working groups could be developed to make recommendations vetted by the participating organizations. These recommendations could then be considered by regulatory bodies, governmental and private funding agencies, pharmaceutical companies and academic institutions to facilitate changes necessary to accelerate clinical translation of novel immune-based cancer therapies. The critical hurdles identified by representatives of the collaborating organizations, now organized as the World Immunotherapy Council, are presented and discussed in this report. Some of the identified hurdles impede all investigators; others hinder investigators only in certain regions or institutions or are more relevant to specific types of immunotherapy or first-in-humans studies. Each of these hurdles can significantly delay clinical translation of promising advances in immunotherapy yet if overcome, have the potential to improve outcomes of patients with cancer

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Accuracy of probabilistic and deterministic record linkage: the case of tuberculosis

ABSTRACT OBJECTIVE To analyze the accuracy of deterministic and probabilistic record linkage to identify TB duplicate records, as well as the characteristics of discordant pairs. METHODS The study analyzed all TB records from 2009 to 2011 in the state of Rio de Janeiro. A deterministic record linkage algorithm was developed using a set of 70 rules, based on the combination of fragments of the key variables with or without modification (Soundex or substring). Each rule was formed by three or more fragments. The probabilistic approach required a cutoff point for the score, above which the links would be automatically classified as belonging to the same individual. The cutoff point was obtained by linkage of the Notifiable Diseases Information System – Tuberculosis database with itself, subsequent manual review and ROC curves and precision-recall. Sensitivity and specificity for accurate analysis were calculated. RESULTS Accuracy ranged from 87.2% to 95.2% for sensitivity and 99.8% to 99.9% for specificity for probabilistic and deterministic record linkage, respectively. The occurrence of missing values for the key variables and the low percentage of similarity measure for name and date of birth were mainly responsible for the failure to identify records of the same individual with the techniques used. CONCLUSIONS The two techniques showed a high level of correlation for pair classification. Although deterministic linkage identified more duplicate records than probabilistic linkage, the latter retrieved records not identified by the former. User need and experience should be considered when choosing the best technique to be used

Is belief larger than fact: expectations, optimism and reality for translational stem cell research

<p>Abstract</p> <p>Background</p> <p>Stem cell (SC) therapies hold remarkable promise for many diseases, but there is a significant gulf between public expectations and the reality of progress toward clinical application. Public expectations are fueled by stakeholder arguments for research and public funding, coupled with intense media coverage in an ethically charged arena. We examine media representations in light of the expanding global landscape of SC clinical trials, asking what patients may realistically expect by way of timelines for the therapeutic and curative potential of regenerative medicine?</p> <p>Methods</p> <p>We built 2 international datasets: (1) 3,404 clinical trials (CT) containing 'stem cell*' from ClinicalTrials.gov and the World Health Organization's International Clinical Trials Registry Search Portal; and (2) 13,249 newspaper articles on SC therapies using Factiva.com. We compared word frequencies between the CT descriptions and full-text newspaper articles for the number containing terms for SC type and diseases/conditions. We also developed inclusion and exclusion criteria to identify novel SC CTs, mainly regenerative medicine applications.</p> <p>Results</p> <p>Newspaper articles focused on human embryonic SCs and neurological conditions with significant coverage as well of cardiovascular disease and diabetes. In contrast, CTs used primarily hematopoietic SCs, with an increase in CTs using mesenchymal SCs since 2007. The latter dominated our novel classification for CTs, most of which are in phases I and II. From the perspective of the public, expecting therapies for neurological conditions, there is limited activity in what may be considered novel applications of SC therapies.</p> <p>Conclusions</p> <p>Given the research, regulatory, and commercialization hurdles to the clinical translation of SC research, it seems likely that patients and political supporters will become disappointed and disillusioned. In this environment, proponents need to make a concerted effort to temper claims. Even though the field is highly promising, it lacks significant private investment and is largely reliant on public support, requiring a more honest acknowledgement of the expected therapeutic benefits and the timelines to achieving them.</p