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In the computational chemistry/physics realm, statistical mechanics, electronic structure and multiscale modeling are three of the theoretical tools that enable understanding and modelling of physicochemical processes. Within these frameworks, several theoretical/computational methods have been reported in the literature over the last decades. Despite their remarkable value in terms of novel ideas and theories , such approaches are often far from a practical applicability within industrial settings . This is mainly due to the fact that: i) these algorithms are often written in rather inefficient programming languages and therefore not fully optimized for new generation hardware architectures; ii) these methods can be very accurate from the physics standpoint, being however quite far away from the industrial needs of finding a suitable tradeoff between speed and accuracy . Often, it can happen that experiments can paradoxically be faster (even though more expensive) than computational predictions. Therefore, companies in different areas are actively seeking more reliable, still rather fast, computational methods to reduce the overall costs of industrial R&D pipelines. Just to mention a few examples, this is the case for drug discovery, where companies are looking for innovative approaches to accurate kinetics and thermodynamics predictions, and the material industry, where designing new nanostructures with improved features could greatly benefit from computational simulations . There exists, however, a clear and long-lasting gap between the theoretical chemistry/physics community and industries, which are looking for efficient, user-friendly, and professional software solutions to be utilized in many different areas. Against this scenario, small/medium enterprises (SMEs) that develop simulative software can play an increasingly key role in, not only translating the science developed in academia via a proper technological transfer process, but also in building a scientific bridge between the industry requirements in terms of automation and the new theories and algorithms developed at an academic level, where it frequently happens that a systematic and practical exploitation of the algorithms is overlooked. It is crucial to remark that transforming academic algorithms into usable software is not only a matter of software engineering, but often also means reconsidering the original theories and formalisms, as a new algorithm working rather quickly and accurately on a system of a few hundred atoms, will not necessarily be appropriate for more complex systems with huge numbers of degrees of freedom. In this context, software development SMEs, which have a clear mission towards top level science suitable for industrial settings, may represent the missing link in the pipeline from-theory-to-software.
In the present E-CAM workshop we will discuss and dissect some key issues related to the aspects reported above. First, we will try to answer the question: which is the most appropriate propelling element of innovation, top-level academic science or industrial needs of accelerating R&D towards novel and cheaper products? Traditionally, the approach to technology is conceiving technology as a corollary of scientific research. However, there is compelling evidence that for several mid-term projects an industry-requirements-driven approach is largely feasible if not best suited. A tightly connected topic regards on how to match and synchronize curiosity driven research with industrial needs and how to manage the resulting, possibly academic/industrial mixed, intellectual property. Can this ‘engineering’ or ‘politechnique’ approach to science/technology transfer be the way to boost the technological SMEs European tissue? Furthermore, considering the scale at which economical phenomena happen today, in the workshop we will discuss whether European SMEs shall federate or merge and join efforts to reach the critical mass and create a significant reference point in the simulative domain worldwide (the American way?). Interestingly, universities and research centers throughout Europe could be the seeds, the starting glue, for this aggregation process. To reach such goals, the main keyword is coordination among the various CoE in Europe towards a coordinated scientific and technological strategy for the creation of professional software for industries and commercial exploitation.
In this E-CAM workshop, we aim at creating a forum where top-level scientists of E-CAM with expertise in statistical mechanics, multiscale modeling and electronic structure will discuss with representatives of pharmaceutical and material industries with the final objectives to identify the major gaps which still hamper a systematic exploitation of accurate computer simulations in industrial R&D. The presence of SMEs will also be crucial to understand whether potential gaps can be filled by small high-tech companies, with the final objective to define a clear workflow and build a bridge between new theories and professional software solutions. As anticipated, special attention will be given to the role of SMEs devoted to simulative software development. These may be key bridges between the academic developments and the creation of tools and interfaces easily transferrable to industrial partners. SMEs are, however, players with specific needs in the domain of intellectual property, developing a viable business model, and positioning themselves between academic research and industry. These aspects, and the possible relationship with the CoEs will be addressed in the workshop.
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 Yibing Shan, Eric T. Kim, Michael P. Eastwood, Ron O. Dror, Markus A. Seeliger, and David E. Shaw. “How Does a Drug Molecule Find Its Target Binding Site?” J. Am. Chem. Soc., 2011, 133 (24), pp 9181–9183