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Informatics


PrecisionMedicine’ inMarch 2019. Both were tar- geted at the interested but non-specialist audience.


Use case: applying bioinformatics in drug discovery and development – Cystic Fibrosis In the EU, Cystic Fibrosis affects one in 2,000- 3,000 new-borns and in the USA one in 3,500. In Asia existing evidence indicates that the prevalence of CF is rare5. CF is a multisystem disease caused by one of several different mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene located in chromosome 76. The CFTR gene provides instructions formaking a pro- tein which functions as a channel across the mem- brane of cells that produce mucus, sweat, saliva, tears and digestive enzymes7. Genetic markers can be used to understand the


disease stratification in terms of symptoms and severity across populations, as well as to enable drugs to be targeted more effectively. More than 1,7008 genetic variants have been


identified in the CFTR gene for patients with Cystic Fibrosis. Only five of these mutations have a frequency greater than 1%. The deletion of phenylalanine in position 508 of the CFTR (F508del-CFTR) is the most common mutation in CF patients9 found in ~90% of CF patients. While six common classes of the disease have


been identified10, based on molecular deficit, there is a move from just genotyping patients towards ‘theratyping’ (matching therapies or medications to specific types of mutations) based on lack of protein (correctors) or lack of function of the pro- tein (potentiators). Development of drugs such as Ivacaftor initially treated specific groups of patients (primarily the G551D mutation), who account for 4-5% of cases of cystic fibrosis. Notably, Ivacaftor was the first medication approved for the management of the underlying causes of CF (abnormalities in CFTR protein func- tion) rather than control of the symptoms of CF. But dual therapies including a combination of Ivacaftor with Lumacaftor have increased the number of patients who can benefit from drug therapy. Furthermore, work is now also under way to use a triple combination of tezacaftor, ivacaftor and an experimental drug VX 455 as well, which has the potential to treat twice as many CF patients. This use case shows the importance of being


able to stratify patients within the overall popula- tion of those suffering from CF. Understanding the details of the genetic abnormalities provides opportunities for drug therapy to address the


58


physiological cause of the disease and not just the symptomatic relief that has been the standard-of- care until recently. Furthermore, such detailed genetic understanding of the abnormalities in the gene will pave the way for gene therapies to be developed.


Some principal concepts of bioinformatics Bioinformatics can be used in clinical diagnostics. The bioinformatics tools can be used to detect the presence of genetic variants that act as markers for a condition or a disease. However, these bioinformatics tools when deployed in Europe must follow the stipulations of the EU IVDR and be CE marked to demonstrate that they are fit for purpose. The EU IVDR includes a specific exemption for


diagnostics that are used in the same health institu- tion as they are made or modified but with some specific requirements as set out in Article 5, para- graph 5. Health institutions wishing to apply the exemption in the new Regulations will need to ensure that products meet the relevant General Safety and Performance Requirements. In addition, health institutions will need to have:


● An appropriate quality system in place eg ISO 15189. ● A justification for applying the exemption including that the target patient group’s specific needs cannot be met, or cannot be met at the appropriate level of performance by an equivalent device available on the market. ● Appropriate technical documentation in place.


Several key issues are present in all bioinformat-


ics and probably one of the most important is how the tools are deployed. This includes managing dependencies, eg other data associated with the analysis, software versions and version control, and operating system compatibility. Source code for the tools is generally stored in repositories (eg Github, BitBucket) and containers (eg Docker) can be used to wrap up all the source code and its dependencies into a standardised format, ready to run. In clinical diagnostics, bioinformatics software,


including the sequencer’s own software, should be validated, ie shown to be robust and repeatable. So, it must be demonstrated that, given identical input (reads from the sequencer), the analysis pipeline will always produce identical output (markers identified). However, this will not be the case when stochastic analysis techniques are deployed, or AI/ML is used. As such, what needs to


Drug DiscoveryWorld Summer 2019


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