Code distribution of siRNA for cancer genes such as p53 and Bcl2 family genes has demonstrated efficacy in killing cancer cells. Nanoparticles can produce a surface where numerous drugs may be coupled, allowing combinatory treatment

Silencing RNA (siRNA) is a promising next-generation approach to correcting genetic defects that predispose people to cancer. The move from the lab to the clinic as a standard cancer treatment still has a long way to go, with a number of limitations, including poor delivery, targeting and internalization efficiency, low stability, mutation susceptibility, quick renal clearance, and significant immunogenicity. In combination with existing chemotherapy therapies, SiRNA technology may also be employed, giving it a feasible choice for overcoming chemoresistance and enhancing apoptotic rates in a range of cancers. Codelivery of siRNA for genes involved in cancer progression, such as p53 and Bcl2 family genes, as well as genes involved in multidrug resistance, with current chemotherapeutic drugs such as doxorubicin and cisplatin, has shown incredible success in killing cancer cells. Nanoparticles can create a surface where several medications may be conjugated, allowing combination therapy. Nanoparticles can also aid by increasing the size of siRNA, which limits too rapid removal of glomerular filtration, blocking the 3 'end of siRNAs to protect against circulatory exonuclease damage, and boosting intestinal absorption. Several nanoparticles have been used, including liposomes, nanoemulsions, cationic polymers and dendrimers. However, the safety and biocompatibility of these particles remains a tough issue to resolve and should be considered in picking the proper nanoparticles. Overall, these applications provide chances to overcome cancer therapy challenges and assist to erase existing barriers to this global health concern in the near future.

AN INITIATIVE FOR THE DEVELOPMENT AND APPLICATION OF OPEN-SOURCE MULTI-PHYSICS SIMULATION IN SUPPORT OF R&D AND E&T IN NUCLEAR SCIENCE AND TECHNOLOGY

Modelling and simulation (M&S) have gradually become irreplaceable tools in the field of Nuclear Science and Technology (NS&T), including nuclear energy systems. This is partly due to growing computational resources and advances in computational science and partly to the difficulties to finance, build and license new experimental facilities. However, the utilization of M&S for research and development (R&D) and education and training (E&T) applications is somewhat hampered by limited accessibility to controlled and sensitive nuclear M&S tools as well as by the desires of the developers of these tools to retain their intellectual property (IP). Open-source software and open-access data are growingly perceived as means to accelerate innovation by promoting synergistic collaborative developments while lowering the barriers associated to code distribution, modification, and sharing. Open-source software development is ideal for R&D and E&T purposes because it permits the enhancement of understanding, the use of advanced computational methods and it promotes the cooperation among researchers and scientists, without rigorous constraints on quality assurance or reliance on proprietary data for technology-specific validation. As a fundamental research tool, this helps to mitigate constraints related to dual use of such technology. It is in this context that an initiative is being launched under the aegis of the International Atomic Energy Agency (IAEA) to promote the development and application of open-source multi-physics simulation in support of R&D and E&T in NS&T. This paper presents scope and objectives of this initiative.

A review of available software for adaptive clinical trial design

Background/aims: The increasing cost of the drug development process has seen interest in the use of adaptive trial designs grow substantially. Accordingly, much research has been conducted to identify barriers to increasing the use of adaptive designs in practice. Several articles have argued that the availability of user-friendly software will be an important step in making adaptive designs easier to implement. Therefore, we present a review of the current state of software availability for adaptive trial design. Methods: We review articles from 31 journals published in 2013–2017 that relate to methodology for adaptive trials to assess how often code and software for implementing novel adaptive designs is made available at the time of publication. We contrast our findings against these journals’ policies on code distribution. We also search popular code repositories, such as Comprehensive R Archive Network and GitHub, to identify further existing user-contributed software for adaptive designs. From this, we are able to direct interested parties toward solutions for their problem of interest. Results: Only 30% of included articles made their code available in some form. In many instances, articles published in journals that had mandatory requirements on code provision still did not make code available. There are several areas in which available software is currently limited or saturated. In particular, many packages are available to address group sequential design, but comparatively little code is present in the public domain to determine biomarker-guided adaptive designs. Conclusions: There is much room for improvement in the provision of software alongside adaptive design publications. In addition, while progress has been made, well-established software for various types of trial adaptation remains sparsely available.