**5. Challenges**

The diversity and rapid evolution of NGS technology causes many challenges associated with data generation, data manipulation and data storage [124]. Some of the major issues with analysis, interpretation, reproducibility and accessibility of NGS data includes: (A) NGS is still too expensive to be accessible by small labs or an individual; (B) data analysis is time-consuming and needs sufficient knowledge of bioinformatics; (C) the short sequencing read lengths supported by NGS is one of the major shortcomings which limit its application, especially in de novo and highly repetitive regions sequencing; (D) data processing steps or bioinformatics is one major bottleneck for the implementation of NGS; (E) routine analysis of NGS data requires multidisciplinary teams; (F) it is critical to standardize the quality metrics for the NGS data generated. These include validation and comparison among platforms, data reliability, robustness and reproducibility, and quality of assemblers; (G) it is crucial to have a complete knowledge of family and personal history of the patient to help define the ideal analysis method, the analysis of the results obtained, and the post-test counselling and management [124–127].

Despite some challenges, it is hard not to be optimistic about the future of personalized genome sequencing and its potential impact on patient care and the advancement of knowledge of human biology and disease.

#### **5.1. Regulation on NGS tests**

Society (HGVS) recommendations, with information of the human reference genome version and transcript information used to variant description [117]. The reference coding sequence

All pathogenic, likely pathogenic and VUS variants have to be reported. Secondary or incidental finding (IF) is one significant matter, especially for WES, WGS and multi-gene panels,

An in-house database containing all relevant variants identified in the laboratory provides an important tool in order to allow for further annotations, which greatly streamline the diagnostic process. Furthermore, an in-house database, linking patients and variants can help when a variant is re-classified. In this case, the laboratory is responsible for re-contacting the clinicians of the patients that are possibly affected by the new status of the variant [38].

Concerning the limitations of technology, the false positive rate for NGS, a second method, as Sanger sequencing, is required to confirm any findings with possible clinical significance. The laboratory must be able to guarantee that report variants are true variants; therefore, it is essential to mention that the variant reports were confirmed by Sanger method. An NGS technology will likely evolve, and within a few years confirmation might prove to be unneces-

In some cases, mainly in large panels, complementing NGS testing with Sanger sequencing is inevitable. This limitation of NGS is dependent on the platform and on the enrichment methods, once that there are a number of strategies available with advantages and disadvantages. Sanger sequencing can also be used to fill regions that fail to amplify for having sequence complexities, such as sequence homology with pseudo genes, highly repetitive regions, GC-rich content, allelic dropout, or regions that are supported by an insufficient number of reads to call variants confidently [34]. However, in practice, the laboratories can opt to apply different settings for NGS tests. Three kinds of tests of multi-genes panel are identified: (A) the lab informs that more than 99% of interest region are covered, and all the gaps are filled with Sanger sequencing; (B) the lab describes which regions are sequenced and fills some specific gaps (core genes) with Sanger sequencing; and (C) no additional Sanger sequencing is offered [38]. It is essential to mention the horizontal coverage acquired in the test and the limitations

The diversity and rapid evolution of NGS technology causes many challenges associated with data generation, data manipulation and data storage [124]. Some of the major issues with analysis, interpretation, reproducibility and accessibility of NGS data includes: (A) NGS is still too expensive to be accessible by small labs or an individual; (B) data analysis is time-consuming and needs sufficient knowledge of bioinformatics; (C) the short sequencing read lengths supported by NGS is one of the major shortcomings which limit its application,

should be preferably from the RefSeq database [123].

304 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

and its report will depend on local practice [38].

**4.1. Sanger sequencing validation**

of these tests in a disclaimer [39].

**5. Challenges**

sary [34, 39].

With the advancement of gene-sequencing technologies, numerous opportunities have arisen in the genetic diagnostic, preventive medicine and other areas of human health. As a result, several life science companies and clinical laboratories started their activities in this field offering equipment and supplies as well as molecular tests using the new-generation (parallel massive) sequencing methodology. However, most manufacturers do not market IVD products (in vitro diagnostic), but, in general, these products are classified as RUO (research use only). In practice, this difference in the classification of products and reagents represents serious implications on health. Products classified as IVD are regulated and therefore follow technical standards in their production and use, and consequently the efficiency must be guaranteed by the manufacturer. The ISO 13485 [128] is often used to ensure the quality of medical products, but other regulatory agencies such as the US Food and Drug Administration (FDA) may require other tests to prove this product is safe and effective, which is necessary for the product be classified as IVD and be commercialized on the American market. The same applies to the CE-IVD Marking in the European Economic Area (EEA). These requirements are part of an effort to ensure that users of these services and devices do not seek unnecessary treatment, delay their treatment or are exposed to inappropriate therapies. In the case of RUO products, none of these situations can be guaranteed, so the manufacturer will only be obliged to replace the product or its cost if it is performing improperly. In fact, some manufacturers may use standards of good manufacturing practice in the production of RUO equipment and supplies, but rarely perform tests to prove their efficiency in a particular case of diagnostic.

In some cases due to the need to respond quickly to the market, especially in areas where the technological advance exceeds the regulatory capacity, some agencies allow the use of tests developed by clinical laboratories. The regulation in these cases is very simpler and favours the development of new technologies as the case of new-generation sequencing (NGS). However, these tests should also be used with caution, and the laboratories must prove its accuracy, or otherwise there may be the same hazards of products classified as RUO. In 2013, the US FDA agency required to genetic testing company 23andME to suspend the marketing of its products until it receives clearance from the agency. In a letter addressed to one of its founders, the agency states its concern about the use of one of its tests and the implications on the health of the patient in case of false results.

guidelines are already available [38, 39, 44, 131–134]. Several NGS validation studies in clinical laboratories have been published and are rich sources of information [135–138]. Improvements

Application of Next-Generation Sequencing in the Era of Precision Medicine

http://dx.doi.org/10.5772/intechopen.69337

307

The high volume of NGS data generated requires a complex computational infrastructure for processing, analysing and storing the data, including sophisticated data analysis pipelines. Cloud solutions such as Google, Amazon and Microsoft can be an alternative to an in-house computational infrastructure. More user-friendly bioinformatics software are desirable for non-bioinformaticians, such as Google Genomics [139], SOPHiA Genetics [140], IBM Watson [141], Illumina BaseSpace [142], Ion Reporter [143], Galaxy [144], CLC Genomics [145]. The variability of data formats generated during the analysis (e.g. FASTQ, UBAM, BAM/SAM and VCF files) and the laboratory must decide the appropriate data to be stored since the cost of

A multidisciplinary team of bioinformaticians, computational biologists, IT technicians, statisticians, molecular biologists, geneticists, genetic counsellors and clinicians is strongly needed and should be properly trained and educated for a successful implementation of NGS into routine diagnostic. Other related areas, such as lawyers, policy-makers, sales representative and investors, also need to be trained. Due to the constant updates of NGS approaches, an ongoing and continuing education about emerging technologies, software, databases and data analysis pipelines that reflect current practice is necessary. Genomic education also

in NGS technologies and data analysis require revalidation before implementation.

managing, analysing and storing is high [124, 130, 146–149].

needs to be incorporated into medical school curriculum [148, 150].

\*, Frederico Scott Varella Malta<sup>1</sup>

1 Hermes Pardini Group/Federal University of Minas Gerais, Vespasiano, Brazil

[1] Langreth R, Waldholz M. New era of personalized medicine: Targeting drugs for each

[2] Ginsburg GS, Willard HF. Genomic and personalized medicine: Foundations and appli-

\*Address all correspondence to: michele.pereira@hermespardini.com.br

2 Progenética Laboratory, Hermes Pardini Group, Rio de Janeiro, Brazil

unique genetic profile. Oncologist. 1999;**4**(5):426-427

cations. Translational Research. 2009;**154**(6):277-287

, Maíra Cristina Menezes Freire2

and

**5.3. Computational infrastructure**

**5.4. Genomic education**

**Author details**

**References**

Michele Araújo Pereira1

Patrícia Gonçalves Pereira Couto1

Some of the uses for which PGS (Personal Genome Service) is intended are particularly concerning, such as assessments for BRCA-related genetic risk and drug responses (e.g., warfarin sensitivity, clopidogrel response, and 5-fluorouracil toxicity) because of the potential health consequences that could result from false positive or false negative assessments for high-risk indications such as these. For instance, if the BRCA-related risk assessment for breast or ovarian cancer reports is false positive, it could lead to undergo prophylactic surgery, chemoprevention, intensive screening, or other morbidity-inducing actions, while false negative could result in failure to recognize an existing risk that may exist. [129]

This example illustrates the importance of evaluating the analytical characteristics of diagnostic tests as well as the reagents and equipment used to perform these tests. In 2013, Illumina was the first company to get FDA approval for the commercialization of four NGS products. It was the first approval for a system based on NGS technology that will allow other companies to develop their own tests using this technology. In 2014, it was the time of SOPHiA Genetics and Vela Diagnostics companies that obtained the CE-IVD Marking of the first products based on the NGS technology for clinical use.

Since then, the number of products that have the classification of IVD has been increasing; however, it is important to note that the classification of an IVD product depends on local regulations, and therefore products that are classified as IVD in a market may not have this classification in other markets. This is due to the regulatory differences between the agencies and the different requirements from each market. Anyway, it is usual that classification process of these products for clinical use must be complex and sometimes elaborated, especially in areas such as genomics. Therefore, initiatives are needed to make the approval process for these products simpler and more flexible, to make the products available, but that ensures the accuracy and usefully testing.

In 2016, the US FDA agency issued two draft guidelines: 'Use of Standards in FDA's Regulatory Oversight of Next Generation Sequencing (NGS) Based In Vitro Diagnostics (IVDs) Used for Diagnosing Germ line Diseases' and 'Use of Public Human Genetic Variant Databases to Support Clinical Validity for Next Generation Sequencing (NGS)-Based In Vitro Diagnostics'. Both are part of an initiative that aims to contribute to new testing using the NGS technology to reach the public with more speed and quality required by the market and health system.

#### **5.2. Clinical validation**

Almost all NGS approaches are still RUO, and validation is necessary before implementation as a diagnostic test. Prior clinical utility, a test must demonstrate analytical and clinical validity. Sensitivity, specificity, robustness, limits of detection, reproducibility, accuracy, precision and concordance between test results and clinical diagnosis should be analysed and measured. The test needs to evaluate patient outcomes and have positive impact on patient care [66, 130]. To assist the usage and implementation of NGS in clinical laboratories, some standards and best practice guidelines are already available [38, 39, 44, 131–134]. Several NGS validation studies in clinical laboratories have been published and are rich sources of information [135–138]. Improvements in NGS technologies and data analysis require revalidation before implementation.

#### **5.3. Computational infrastructure**

founders, the agency states its concern about the use of one of its tests and the implications on

This example illustrates the importance of evaluating the analytical characteristics of diagnostic tests as well as the reagents and equipment used to perform these tests. In 2013, Illumina was the first company to get FDA approval for the commercialization of four NGS products. It was the first approval for a system based on NGS technology that will allow other companies to develop their own tests using this technology. In 2014, it was the time of SOPHiA Genetics and Vela Diagnostics companies that obtained the CE-IVD Marking of the first prod-

Since then, the number of products that have the classification of IVD has been increasing; however, it is important to note that the classification of an IVD product depends on local regulations, and therefore products that are classified as IVD in a market may not have this classification in other markets. This is due to the regulatory differences between the agencies and the different requirements from each market. Anyway, it is usual that classification process of these products for clinical use must be complex and sometimes elaborated, especially in areas such as genomics. Therefore, initiatives are needed to make the approval process for these products simpler and more flexible, to make the products available, but that ensures the

In 2016, the US FDA agency issued two draft guidelines: 'Use of Standards in FDA's Regulatory Oversight of Next Generation Sequencing (NGS) Based In Vitro Diagnostics (IVDs) Used for Diagnosing Germ line Diseases' and 'Use of Public Human Genetic Variant Databases to Support Clinical Validity for Next Generation Sequencing (NGS)-Based In Vitro Diagnostics'. Both are part of an initiative that aims to contribute to new testing using the NGS technology to reach the public with more speed and quality required by the market and health system.

Almost all NGS approaches are still RUO, and validation is necessary before implementation as a diagnostic test. Prior clinical utility, a test must demonstrate analytical and clinical validity. Sensitivity, specificity, robustness, limits of detection, reproducibility, accuracy, precision and concordance between test results and clinical diagnosis should be analysed and measured. The test needs to evaluate patient outcomes and have positive impact on patient care [66, 130]. To assist the usage and implementation of NGS in clinical laboratories, some standards and best practice

Some of the uses for which PGS (Personal Genome Service) is intended are particularly concerning, such as assessments for BRCA-related genetic risk and drug responses (e.g., warfarin sensitivity, clopidogrel response, and 5-fluorouracil toxicity) because of the potential health consequences that could result from false positive or false negative assessments for high-risk indications such as these. For instance, if the BRCA-related risk assessment for breast or ovarian cancer reports is false positive, it could lead to undergo prophylactic surgery, chemoprevention, intensive screening, or other morbidity-inducing actions, while false negative could result in failure to recognize an existing

the health of the patient in case of false results.

306 Applications of RNA-Seq and Omics Strategies - From Microorganisms to Human Health

risk that may exist. [129]

accuracy and usefully testing.

**5.2. Clinical validation**

ucts based on the NGS technology for clinical use.

The high volume of NGS data generated requires a complex computational infrastructure for processing, analysing and storing the data, including sophisticated data analysis pipelines. Cloud solutions such as Google, Amazon and Microsoft can be an alternative to an in-house computational infrastructure. More user-friendly bioinformatics software are desirable for non-bioinformaticians, such as Google Genomics [139], SOPHiA Genetics [140], IBM Watson [141], Illumina BaseSpace [142], Ion Reporter [143], Galaxy [144], CLC Genomics [145]. The variability of data formats generated during the analysis (e.g. FASTQ, UBAM, BAM/SAM and VCF files) and the laboratory must decide the appropriate data to be stored since the cost of managing, analysing and storing is high [124, 130, 146–149].

#### **5.4. Genomic education**

A multidisciplinary team of bioinformaticians, computational biologists, IT technicians, statisticians, molecular biologists, geneticists, genetic counsellors and clinicians is strongly needed and should be properly trained and educated for a successful implementation of NGS into routine diagnostic. Other related areas, such as lawyers, policy-makers, sales representative and investors, also need to be trained. Due to the constant updates of NGS approaches, an ongoing and continuing education about emerging technologies, software, databases and data analysis pipelines that reflect current practice is necessary. Genomic education also needs to be incorporated into medical school curriculum [148, 150].
