The proportion of cell-free DNA (cfDNA) derived from tumor cells in the plasma of patients with cancer is typically less than 2%. To overcome this limitation, methods have been developed to better distinguish the circulating tumor DNA (ctDNA) signal from the noise we encounter in most current methodologies. While these solutions are successful in minimizing the technical noise, it often requires increased sequencing depth and other advanced analytical techniques. Thus, alternative or complimentary approaches, such as liquid biopsies, would be beneficial for improving noninvasive cancer diagnostics. The fragment length of ctDNA may be leveraged to improve this signal-to-noise challenge since the median length of cfDNA in circulation from healthy tissue is typically about 167bp, while ctDNA is shorter on average. We evaluated whether size selecting cfDNA could enrich for shorter ctDNA fragments and thereby enhance signal for the detection of tumor-specific variants. To test this hypothesis, adapter-ligated libraries were size selected using the Yourgene Health LightBench platform for gel-based electrophoresis and size selection, targeting cfDNA fragment sizes up to 142bp (+/- 15bp). The size selected libraries from each patient were first assayed with low-coverage (~0.3X) genome-wide sequencing and analyzed for insert size to ensure proper enrichment of shorter cfDNA fragments. Libraries prior to size selection yielded, on average, 25.9% of reads with cfDNA fragment sizes shorter than 150bp. After size selection, the proportion of cfDNA shorter than 150bp was significantly increased to 96.4% (p<0.001; Wilcoxon Rank Sum). Copy number alterations (CNAs) were identified in the cfDNA data and characterized using analytical methods originally developed for noninvasive prenatal testing and subsequently optimized for ctDNA. The amplitude of a detectable autosomal CNA represents the relative magnitude of the CNA. When evaluating cfDNA from healthy patients, the amplitudes of CNAs before and after size selection were on average within 6%, consistent with a lack of signal enrichment in the absence of disease. Conversely, detectable CNAs in cancer patients were on average 47% greater in amplitude in size selected samples than in the same samples prior to size selection, consistent with an enrichment of signal. These data demonstrate a proof-of-concept for using size selection to enhance signal for the detection of tumor-specific variants in cancer patients.

Learning objectives:

1.    Discuss current methodology for detecting tumor-specific copy number alterations in cancer patients.

2.    Explain how size selection can enhance signal for the detection of tumor-specific variants in cancer patients. 

Lab-on-a-chip platforms enable advanced processing, manipulation, and analysis of biological samples in miniaturized fluidic devices. Despite the numerous advantages, such as lower reagent and sample volumes, reduced cost, and faster time to result, several hurdles must be overcome to continue to grow and advance this technology in clinical diagnostics. This presentation will include a discussion of (1) the main technologies in the field of lab-on-a-chip platforms for medical diagnostics, (2) advantages and disadvantages of lab-on-a-chip technology in the clinical laboratory, and (3) current commercialized point-of-care devices utilizing lab-on-a-chip technology. The session will conclude by highlighting some future challenges the field will need to address as lab-on-a-chip technology is expanded.  

Learning Objectives: 

1. Explain the advantages and disadvantages of various lab-on-a-chip technologies for diagnostics.

2. Discuss the challenges associated with standardization and commercialization of lab-on-chip platforms.

3. Cite examples of FDA-approved lab-on-a-chip based diagnostic devices.

This session provides an overview of rapid method validation and testing strategies for COVID-19 antibody testing. The current challenges and limitations of COVID-19 antibody testing will be presented along with solutions to improve positive and negative predictive values when testing low disease prevalence populations. The correlation between these antibody tests and the presence of neutralizing antibodies against SARS-CoV-2 will be discussed. Utilization of these assays for the vaccinated patient population will also be discussed. Lastly, a summary of the importance of using a screening and confirmatory approach for COVID-19 antibody testing will be provided.

Learning Objectives: 

1. Recognize the challenges of implementing COVID-19 antibody testing.

2. Explain how COVID-19 antibody testing accuracy is affected in low disease-prevalence populations.

3. Describe the relationship between COVID-19 antibody testing and neutralizing antibodies.

4. Describe which COVID-19 serology assays are applicable to COVID-19 vaccinated individuals.

We describe product development tools combining data science and biochemistry to build more affordable research and diagnostic molecular testing solutions. This high level multiplexing technology leverages the cloud to enable global deployment of robust products using existing equipment and standard workflows to increase qPCR multiplexing by 4x and dPCR multiplexing by 10x to fulfill unmet needs in infectious disease, NIPT, and oncology. In this talk, we discuss approaches to leveraging the data science toolset to improve products, from development through to production and post launch monitoring.
 
Learning objectives
 
1. Discuss ways to integrate data science into product development.

2. Breakdown tools and approaches that can be generalized across industry for monitoring product performance in the field.

3. Discuss other use cases for data science to improve operational efficiency.

Diagnosis, prognostication, and monitoring of child health relies on laboratory testing, including but not limited to key markers of thyroid, hepatic, cardiac, hematology, and renal function. Dynamic physiological processes during growth and development significantly influence paediatric biochemistry, altering expected values of common laboratory tests. In this webinar, we will discuss the importance of age- and sex-specific blood test interpretation in children and adolescents and provide an overview of the Canadian Laboratory Initiative on Paediatric Reference Intervals (CALIPER), including its recent works towards closing this gap. 

Learning Objectives:

1.    Discuss the importance of age- and sex-specific blood test interpretation in children and adolescents.

2.    Introduce the Canadian Laboratory Initiative on Paediatric Reference Intervals (CALIPER).

3.    Discuss recent data closing the gaps in pediatric reference standards on various analytical platforms and future directions.

The Human Gene Mutation Database (HGMD) is a one-of-a-kind resource containing data for hundreds of thousands of variants within the context of associated phenotype(s). Specifically, HGMD provides the genomic coordinates and Human Genome Variation Society (HGVS) nomenclature for variants as well as citations and comments for key publications, which saves users time and effort during variant interpretation.

We will walk through examples from variant interpretation scientists who have derived great value from consulting HGMD in their variant classification workflow:
- Visualization of HGMD entries in tools such as IGV and UCSC Genome Browser
- Literature references with additional comments/notes
- Legacy/alternative variant naming schemes and how HGMD simplifies literature review
- CNVs and “reverse” look-up by phenotype

We will also demonstrate VCF upload and utility in IGV/UCSC Genome Browser

Learning Objectives:

1. Discuss HGMD Professional’s search capabilities.

2. Explain the coordinates and HGVS nomenclature given for published variants with non-standard/legacy names.

3. Discuss how HGMD indicates where a variant is described in a paper- supplemental text.

4. Breakdown CNV-related use cases.

5. Discuss phenotype-focused search ─ multiple genes contributing to a complex phenotype (neuro).

In this webinar, we present a case study on Lynch syndrome (LS), a hereditary condition characterized by a high risk of colorectal cancer, endometrial cancer, and other neoplasia that typically manifests in the context of germline variants in DNA mismatched genes. 
To study whether other germline pathogenic variants of hereditary cancer genes are present in patients previously diagnosed with LS, the researchers analyzed a comprehensive panel of cancer-predisposing genes by NGS among 84 LS probands.

With this study as an example, we will illustrate how you can use your own data and public data to conduct translational research using 3 software solutions from QIAGEN.

Learning Objectives:

1. Analyze how you can efficiently retrieve and process FASTQ data with accurate variant interpretation using CLC Genomics Workbench.

2. Interpret how you can take a set of variants and rapidly assess sample variants for disease relevance and pathogenicity using QCI Interpret Translational.

3. Discover how you can combine results and contextualize variant biomarkers with other public datasets using QIAGEN Ingenuity Pathway Analysis (IPA).

This workshop will focus on the emerging variants and the diagnostic and surveillance strategies (genotyping assays complementing sequencing) for this, as well as the impending COVID-Flu intersection.

Learning Objectives:

1. Discuss recent developments in the SARS-CoV-2 landscape and testing strategies.

2. Discuss the emerging variants and the diagnostic and surveillance strategies.

SARS-CoV-2 testing is now facing increasing challenges in the face of an ongoing pandemic with the emergence of new variants and waning vaccine immunity. Increasing evidence supports the correlation between neutralizing antibody titers and protection from this dangerous virus. Recent studies show that less than 40% of immunocompromised and less than 70% of elderly (over 80 years of age) people who are fully vaccinated elicit these protective antibodies. Furthermore, Israel’s early vaccination program exclusively using the Pfizer vaccine has shown waning population immunity after about six months post-vaccination leading to a dramatic uptick in infections particularly from the Delta variant. Thus triggering a third booster shot for people over the age of 50 in that country. This talk explores the key questions associated with the healthcare implications of SARS-CoV-2 and how a new approach to testing may help in determining individual, neutralizing antibody response to vaccination.

Learning Objectives:

1. Explain the principles of a new cPass surrogate virus neutralization test (cPass sVNT) and how it compares to the gold standard live cell virus neutralization tests such as the plaque- and foci-reducing neutralization tests.

2. Contrast the more traditional and commonly employed SARS-CoV-2 IgG binding assays with the functional cPass sVNT. 

3. Discuss the variation in efficacy of current SARS-CoV-2 vaccines and uncertainties in vaccinated populations concerning protection.

While clinical microbiology laboratories are pivotal in the identification and handling of infectious diseases, the microbiology lab environment is rapidly changing. Conventional testing methods are being challenged as innovative testing methodologies emerge. Molecular testing is an ever-evolving world for the most common disease areas, including respiratory, urinary tract, and vaginal pathogen detection. In the case of testing for urinary tract infections (UTIs)—the second most common type of infection, with nearly half of positive UTI cases polymicrobial—current culture-based methods for detecting UTI pathogens have significant limitations. These include inability to address polymicrobial infections, long time to result, and false negatives due to poor sensitivity. Doubtful cases of UTI are of particular concern.

A molecular alternative that uses real-time PCR technology, however, has the potential to increase the specificity and sensitivity of pathogen detection. Additionally, advancements in UTI testing now include unique multi-omics approaches to detect bacterial interactions and address antibiotic resistance in polymicrobial samples.
Furthermore, while standard culture tests susceptibility on individual isolates, pooled antibiotic susceptibility testing (P-AST)—a unique method in which organisms are grouped together—takes into consideration bacterial interactions and may provide more effective therapy options.

During this webinar, Advancements in UTI Testing: A Multi-omics Approach to Maximizing the Flexibility of Your Molecular Testing Laboratory—sponsored by Thermo Fisher Scientific, in partnership with Pathnostics—will compare the clinical utility of genotypic and phenotypic methods in treatment of UTIs and describe how a multi-omics approach could be implemented in a laboratory.

Learning Objectives:

1. Understand the impact of urinary tract infections (UTIs) in patient care.

2. Evaluate the technical challenges and limitations associated with urine culture.

3. Describe how a multi-omics approach could be implemented in a laboratory.

The routine analysis of steroid hormones is critical in understanding the function of metabolic pathways that impact sexual characteristics, inflammation and blood pressure. Liquid Chromatography-Mass Spectrometry (LC-MS) is fast becoming a sought-after technique in steroid analysis due to the advantages it provides over traditional ligand-binding techniques. These benefits include improvements in analytical sensitivity and selectivity, and the capability of multi-analyte quantitative detection in a single run. However, many LC-MS methods lack harmonization or standardization. The Waters™ MassTrak™ Endocrine Steroid Calibrator and Quality Control Sets (IVD) contain metrologically traceable calibrators, aiding laboratories in their compliance to ISO 15189, and provide confidence in the accuracy of results when using validated LC-MS methods.

In this webinar, the characteristics of the MassTrak Endocrine Steroid Calibrator and Quality Control Sets will be discussed and the performance of an in-house LC-MS/MS method for the analysis of steroid hormones will be demonstrated.

Learning Objectives:

1. Break down metrological traceability that aid laboratories in their compliance to ISO 15189.

2. Describe improvements in laboratory efficiency through the provision of lyophilized materials.

3. Discuss confidence in the accuracy steroid hormones and provide a path to laboratory method harmonization, with excellent lot-to-lot reproducibility.

The Moonshot program was established in the UK by The Department of Health and Social Care to explore novel technologies for the detection of SARS-COV-2. Mass spectrometry was identified as a potential candidate and experts from academia, industry and the National Health Service (NHS) worked in partnership to develop a state-of-the-art targeted proteomic assay, refine the method for use in a routine clinical environment, and validate it to ISO:15189 standards.

Learning Objectives:

1. Demonstration of an LC-MS/MS workflow for the analysis of SARS-CoV-2, with excellent agreement to PCR.

2. Validation of a ready to use SARS-CoV-2 LC-MS Kit, automated on the Andrew Alliance Andrew+ pipetting robot.

3. Differentiation of the SARS-CoV-2 delta variant from previous variants of concern.

To prevent and treat SARS-CoV-2 infections, a comprehensive understanding of both the humoral and cellular immune responses is essential.  One critical component to understanding the fundamental immunological processes to COVID-19 is analyzing rare antigen-specific T cells. Following infection or vaccination, the presence of these cells can also indicate whether or not long-term protection is gained. Yet, working with antigen-specific T cells can prove challenging to many researchers — critically low cell frequencies, inflammatory environments, non-specific labeling, and high background often make enrichment and analysis difficult.

At Miltenyi Biotec, we offer a complete workflow that has been optimized at every step to address key challenges faced by researchers working with these rare cells. The ideal combination of products for sample preparation, cell stimulation, pre-enrichment and flow cytometry ensure successful analysis.

Learning objectives:

1. Discuss our complete workflow for isolation, stimulation, enrichment and analysis of antigen-specific T cells.

2. Explain how to overcome key challenges, including low cell frequencies, unspecific labeling and high background staining.

3. Discuss which technologies enable efficient, gentle, and safe isolation of antigen-specific T cells for subsequent deep profiling by, e.g., single-cell genomics analyses.

The COVID-19 pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective clinical decision support for infected patients, ranging from screening to risk stratification to treatment planning.  Motivated by this and inspired by the open source efforts of the research community, in this study we introduce COVID-Net, a global open source initiative for AI-assisted COVID-19 clinical decision support that is open source and available to the general public. As part of the initiative, we not only introduced deep learning models for different stages of clinical decision support, but also some of the largest COVID-19 related open access datasets to support these models.  Furthermore, we investigate how the COVID-Net models makes predictions using an explainability method in an attempt to not only gain deeper insights into critical factors associated with COVID cases, which can aid clinicians in improved diagnosis and prognosis, but also audit COVID-Net models in a responsible and transparent manner to validate that it is making decisions based on relevant information. The hope is that the open source COVID-Net initiative will aid both researchers and citizen data scientists alike to accelerate the development of highly accurate yet practical deep learning solutions for COVID-19 clinical decision support and accelerate treatment of those who need it the most.

Learning Objectives:

1. Discuss the potential role of artificial intelligence in the context of clinical decision support.

2. Identify risk factors related to the use of artificial intelligence for clinical decision support and ways to mitigate such risks.

3. Explain the role of explainability in artificial intelligence development and deployment.