Introduction


introduction T


his number of DDW contains several ‘futuristic’ articles – futuristic in the sense that they explore either improvements which should, could and probably can, be made to existing methodologies, or technologies used in other fields which could, with advantage, be adapted and used to improve the drug discovery and development process.


In one of our articles an astonishing statistic is quoted, namely that in 2009 human beings generated more data than in all the previous 5,000 years combined. Drug researchers are familiar with the issue of feeling overwhelmed by the plethora of data which can now be generated by automated and high throughput techniques. The science of bioinformatics has developed rapidly but there is still a view that maximum useful information may still not be being extracted from these enormous data sets, at least not in a timely manner. A possible solution is offered in this article which describes cloud computing, described by the author as a combination of technologies and service offerings having the potential to increase the speed of basic research projects significantly. In his article he discusses the benefits, negatives and opportunities of the use of cloud computing in pharmaceutical development. It is already being used in another field completely allowing people in various parts of the world to collaborate on virtual mega-engineering projects that are ‘unprecedented in scale or scope’. Apparently, but not really, paradoxically, another of our articles points out that selection of lead molecules for development is often made using a relative scarcity of experimental data. A medicinal chemist can generate ideas concerning numbers of modifications around a given structure but the time taken for the chemists to synthesis, and the biologists to test, large numbers of compounds often means that there is early focus on apparently promising structural types without exploring the broader range of chemical diversity potentially available. However, our authors point out that the emergence of predictive in silico models allows large quantities of data to be generated on large numbers of compounds. Modern ‘multi-parameter optimisation’ methods allow these data to be analysed to assess how well compounds match up to the ideal profile required. An example is given illustrating the use of this approach.


Ion channels have been seen as targets for useful and innovative therapeutic agents for many years but the full potential of this approach has been somewhat limited by the absence of automated high throughput screening methods. Patch clamping, the electrophysiological procedure of choice, requires skilled operators and only relatively small numbers of compounds can be tested. Early attempts to automate this procedure encountered difficulties and scepticism but a review in these pages of currently available systems indicates that they have evolved satisfactorily and are now widely used in most ion channel discovery programmes.


Biomarkers are used especially in the diagnosis and assessment of efficacy of thereapeutic procedures of cancer. Because of its prevalence cancer remains a disease of interest to both big pharma and biotech. And there has been a recent resurgence in in attempts to target the metabolic pathways involved in cancer. Our author describes the recent discoveries which have led to the re-awakened interest in this approach. The assumption is that the requirement for cancer cells to proliferate and survive necessitates a higher demand for metabolic inputs with presumed differences in metabolism between cancerous and normal


Drug Discovery World Fall 2011


proliferating cells. As with all potential cancer chemother- apeutic approaches it will, of course, be essential to ensure that the agent selectively targets the cancerous cells. A new approach to the treatment of both solid tumours and haematologic cancers is described in another article. This involves the use of drugs which mimic the actions of Smac (second mito- chondria-derived activator of caspase) which inhibits pro- teins called IAPs


(inhibitors of apoptosis proteins). The latter encourage cancer survival by protecting cancer cells from death by apoptosis. A number of Smac mimetics, which are in the early stages of clinical testing, are described. The use of stem cells in drug discovery and development and in therapy is seen, at least in the popular press, as a new development but it has, as is pointed out by another of our authors, been around for decades – in bone marrow transplants. However, there is certainly increased interest leading to a rising demand for stem cell products and this, in turn, has led to the formation of contract manufacturing companies to which pharmaceutical companies can outsource their requirements. The author describes a public-private partnership in the US which is for the development and manufacture of stem cell therapies. Wider participation is sought from private and public organisations. Quantitative real-time PCR (qPCR) is used widely in drug discovery laboratories for nucleic acid analysis High throughput platforms are now available but there are still some limitations which could be overcome by the use of digital PCR (dPCR). Looking into the future one of our authors predicts that dPCr is now here to stay and will gain in popularity although its commercialisation may be difficult due to the complex intellectual property situation. We also carry an article on epigenetics with some discussion as to how drugs could be developed to reverse the pathological gene changes brought about by this process which results in changes in gene expression patterns brought about by environmental factors which produce chemical modification of the DNA and chromatin associated proteins. The changes are not, as previously thought, the result of mutations to the DNA sequence itself. Epigenetic targets have been identified and active R&D programmes are in place aimed at producing both therapeutic agents as well as biomarkers.


Dr Roger Brimblecombe PhD, DSc, FRCPath, FIBiol 7

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