Informatics


References 1Watson, JD, Crick, FH. Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid. Nature 1953; 171 (4356) 737-738. 2The Epic Investigators. Use of a monoclonal antibody directed against the platelet glycoprotein IIb/IIIa receptor in high-risk coronary angioplasty. The EPIC Investigation. The New England Journal of Medicine. 1994; 330 (14): 956-961. 3Van Arnum, P. New Drug Approvals Reached 21-Year High in 2017. https://www.dcatvci.org/5001- new-drug-approvals-reached- 21-year-high-in-2017. Accessed 3/20/2018. 4 Brown, RD. Advanced Analytics and Visualisation for Biology Big Data. SLAS 2018 Presentation.


experience, the latter approach is likely to lead to a better ultimate outcome. In the case of a small molecule discovery organisation implementing a biologics discovery programme, a scientific infor- matics system is typically already in place. Existing legacy systems, and established vendor relation- ships, are likely to be factors in choosing the sys- tem to support biologics. Existing applications should be used where they can support both small molecules and biologics, and these can then be sup- plemented with software applications specifically tailored to supporting biologics discovery, either from vendors already used or others. As scientific knowledge and supporting experi-


mental technology evolve, opportunities arise for more complex and data-rich experimental methods. High content screening (HCS) has existed for some time, but biologics drug discovery has accelerated the development and adoption of HCS as it pro- vides the opportunity to utilise a richer set of bio- logical processes for the functioning of the candi- date compound. Additionally, the richer biological functioning adds to the complexity of checking for undesirable side-effects. The result is richer, multi- channel data from the instruments, imposing addi- tional requirements on analysis software to handle the larger volumes and complexity of the data. Further challenging analysis and visualisation


capabilities of informatics software is that biologic drugs have a basis in nucleic acid sequences, which in their native form can be exceptionally large. Combined with complex, multi-channel assay data, this imposes severe challenges on informatics systems in general, and analysis and visualisation applications in particular. The volume of data being generated and analysed is growing exponen- tially for a given investigation. For most software applications, performance will scale at best linearly with the size of the dataset being analysed (compu- tational performance) and visualised (display per- formance). So if the data being analysed are 10x, 100x or even larger in scale, the performance char- acteristics of the software, and the associated user experience, will decline dramatically. In the worst (and not uncommon) cases, software applications will be swamped by the data volumes being gener- ated today, and will fail due to memory limits, etc. Providers of biologics software applications must anticipate and respond to increased data volume needs with specific software engineering approach- es and not rely on hardware performance improve- ments to hide performance deficiencies. Analysis and visualisation applications need to perform such that their performance in unaffected or mini- mally impacted as the scale of data increases, a sit-


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uation referred to as zero-order scaling4. This means the applications may need to be recoded with better algorithms, potentially at the machine- code level, and to take advantage of modern hard- ware architectures, graphical programming units and programming languages. Drug discovery com- panies seeking to implement an informatics system must ensure performance metrics are fully estab- lished and verify that proposed solutions meet or exceed these.


Summary Learning from past successes and challenges, and understanding trends and trajectories, are valuable assets in any decision-making. Initial adoption of a discovery informatics system, or making signifi- cant changes to supplement or upgrade an existing one, are major decisions, and will likely impact the organisation, positively or negatively, for many years. Such decisions clearly should not be taken lightly, but at the same time delaying or not mak- ing the decision at all is not a viable option. Doing so will almost certainly negatively impact the busi- ness, as the gaps will be filled by non-standard, ad- hoc solutions that will become harder to replace over time. Here we have highlighted several key elements to


factor into a decision, including lessons learned from small molecule discovery, current and near- future IT trends, key differences between small molecule and biologics entities and considerations to deal with the increasing volumes of data arising in biologics discovery programmes. There are other factors to consider as well, not able to be covered here, but the key takeaway should be that a scientific informatics system is essential and armed with this and additional information an organisation should approach that decision with confidence.


DDW


Dr Andrew LeBeau is Senior Manager of Biologics Marketing at Dotmatics. He joined Dotmatics in October 2017, bringing more than 15 years of experience working in the life sciences industry. At Dotmatics, Andrew leads efforts to highlight and promote the capabilities of Dotmatics software to support the rapidly growing and evolving field of biologics drug discovery.


Drug Discovery World Spring 2018


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