While AI/ML was subject to much hype, there

are a broad range of areas where this technology might USEFULLY be applied. What’s on the horizon that will impact bioinfor-

matics? The future will:

● Be driven by companies that either are not well known or do not yet exist. ● Be secure, for cloud-based systems offer advanced security features and alerts (eg UK-OFFI- CIAL security classification is supported by AWS19). ● Require more experiments executed more quickly. ● Demand ease-of-use, eg design thinking and user experience engineering will be increasingly impor- tant20. ● Require more cloud-accessible, software compo- nents, datasets, tools and techniques to build sophisticated applications. ● Require cloud-based scalability of applications. ● Be about data sets, tools and techniques, eg AWS is supporting public-hosted data sets and under- pins many tools (eg Lifebit*) and techniques (eg pywren*, CloudKnot* and Nextflow*).

Conclusion CDx are the sine qua non of precision medicine and CDx needs to conform to the rigorous quality requirements imposed by the EU IVDR, whether by obtaining CE marking or exercising Health Institute Exemption. The capabilities of gene sequencing and its bioinformatics analysis were increasing rapidly, while the associated time and costs were decreasing. When bioinformatics was involved in diagnostics then the bioinformatics sys- tems needed to be validated in accordance with a recognised quality system to demonstrate that their results were robust and repeatable. Bioinformatics was an essential tool to investigate the genetic causes of disease. Data standards and federated approaches to healthcare genetic data needed to be developed and deployed to allow research access to data that was geographically distributed. The

cloud was playing an increasingly important role in bioinformatics analyses by enabling the scalability of systems needing to keep up with increased workload. The cloud also made available a wide variety of tools, including AI/ML-based tools, to increase the capability of bioinformatics analyses. Finally, blockchain technology could contribute strongly to the management, availability and anal- ysis of genomics data allowing the individual to own their data and to make it available for research as and when they choose.


Mike Furness was Founder of TheFirstNuomics and currently works at Qiagen in the Bioinformatics Customer Services Team. He has spent more than 30 years working in genomics and bioinformatics, developing and applying new tech- nologies to understanding disease and drug R&D. He has previously worked for Life Technologies, Cancer Research UK, Pfizer, Incyte Genomics, DNAnexus, Congenica and Lifebit, as well as con- sulting widely for pharmaceutical and technology companies and investors and the Pistoia Alliance.

John Wise specialises in precompetitive collabora- tion in the life science R&D information ecosys- tem. He is a consultant to the Pistoia Alliance, a not-for-profit organisation committed to lowering the barriers to innovation in life science R&D, and also serves as the programme co-ordinator for the PRISME Forum, a not-for-profit biopharma R&D IT/Informatics leadership group focused on the sharing of best practices. John has worked in life science R&D informatics in a variety of organisa- tions, including academia, the pharmaceutical industry and a cancer research charity, as well as in the technology supply side of the industry. John graduated in physiology before obtaining a post- graduate certificate in education.

AgilentTechnologies, Inc Analytik Jena Biostrata Ltd

BioTek Instruments, Inc BMG Labtech GmbH

39 25 29 27



Charles River Laboratories, Inc ELRIG

Eurofins Discovery Services Horizon Discovery Group plc Labcyte, Inc

49 6

4,31 3

Quanterix Corporation Select Biosciences Ltd Taconic Biosciences, Inc



Drug DiscoveryWorld Summer 2019

Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64