Informatics
Figure 2
Technology adoption curve from Diffusions of Innovations
by Everett Rogers. After a slow transition through the
Innovators and Early Adopters, adoption of cloud computing
in drug discovery organisations is firmly in the Early Majority
have only been available on mobile platforms rela- tively recently. Cloud computing faced many years of resistance
due to data protection concerns and entrenched business practices, but our observation is that the pace of adoption has accelerated significantly in the last two to three years. Utilisation of cloud has followed the typical technology adoption curve, driven initially by the pioneers and early adopters, and now we are well into the early majority (Figure 2). Driving adoption is that cloud computing is inherently logical for many organisations, and an additional dynamic is its utilisation to facilitate collaboration across global companies and in par- ticular for projects involving other organisations, such as CROs and in joint discovery efforts with partner organisations. We anticipate continued adoption and full maturation of cloud computing over the next several years. As with personal com- puting, this technology should remain relatively stable for the next few years. A third major IT trend whose effect and impact
on businesses has been widely theorised is the social element. To what degree will (and has) the widespread consumer adoption of social comput- ing translate to those working in the drug discov- ery industry? Attempts have been made to add ‘social feeds’ to informatics systems to facilitate collaboration and speed projects forward. There is little evidence to conclude that this technology has been broadly adopted. On the other hand, use of instant messaging (IM) apps on laptops and smart- phones for more casual business interactions appears widespread. It seems that doing ‘real sci- ence’ requires informatics support that is more substantial and structured than social feeds allow, but IM is valuable for routine, less intellectually- demanding communication.
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For all three IT trends, we seem to be in a peri-
od of relative stability, with mostly incremental changes and improvements in these and other IT capabilities, without expectations of major inno- vations and disruptions. Disruptive technologies are often observed in the consumer market first. Current major consumer trends include virtual reality (VR), Internet of Things (IoT) and Machine Learning (ML). For any technology to become widely adopted, it must provide a com- pelling advantage over existing capabilities and the drug discovery industry tends to be quite con- servative, so the bar for adoption is particularly high. Considering each of these in turn, it is not immediately obvious what compelling advantage VR could provide. This remains nascent technol- ogy in the consumer space and likely to make major inroads initially in the gaming industry. For IoT, in the consumer space this means mak- ing connections between household appliances, environmental systems, etc with the internet, to allow control and information exchange. In many ways, the drug discovery industry is ahead with this technology, as laboratory instruments are connected (perhaps not always elegantly) to information management systems to allow the data generated by the instruments to be analysed, combined and interpreted. Similarly, the use of ML already has a significant history in drug dis- covery companies, particularly for small molecule discovery, where the development of data models to analyse drug-likeness is well established. Overall we anticipate a period of relative stabil-
ity in IT over the next several years allowing organisations looking to adopt a system to have confidence that the system will not be obsolete or need major upgrading soon after adoption.
Drug Discovery World Spring 2018
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